2011-12 north carolina basketball preview

l e t t e r f r o m t h e e d i t o r

Dear Carolina Fan,

Hello and welcome to college basketball season! Let me start by thanking you for purchasing Maple Street Press Tar Heel Tip-Off 2011–12. This is our fifth edition of the Tip-Off and, like always, we strive to provide fresh information and thoughtful analysis about the Heels from cover-to-cover. Many of the statistics (and accompanied analyses) found within are only available in this publication. We re-watch and hand-chart every Carolina game to meticu-lously accumulate the data used in the magazine. It’s a labor of love, and we hope you have as much fun studying our numbers as we did collecting them.

After a couple years of (ever-so-slightly) lowered preseason expectations, this version of Carolina basketball is squarely back to its 2008–09 position as October favorites. Like then, when the return of Lawson/Ellington/Green/Hansbrough made UNC the team to beat, the current Heels welcome back Harrison Barnes, John Henson, and Tyler Zeller—all of whom delayed NBA millions for another crack at a national championship. Those three, along with sophomore point guard Kendall Marshall, give Carolina four of the best players in the ACC, and make the Heels the clear-cut favorites to win a second consecutive regular-season title. And, with the Final Four back in New Orleans (home of the 1982 and 1993 championships; see Nolan Hayes’s story for some Big Easy memories), there’s plenty of reason for optimism.

No matter how loaded a roster, there’s no such thing as a guaranteed championship. Luck and March match-ups will always play a huge role, and teams like Kentucky, UConn, and Ohio State join Carolina as teams with lottery talent and high expectations. So, like always, don’t forget to enjoy the ride. Teams like this one don’t come around all the time, even at a program as storied as North Carolina. Enjoy every Barnes three-pointer, Strickland transi-tion dunk, Henson rejection, Marshall assist, and Zeller jump hook. Enjoy watching highly touted freshmen James Michael McAdoo and P.J. Hairston make their collegiate debuts. Enjoy cheering on Blue Steel as they take the court in pursuit of biscuits. The destination is New Orleans, but the journey should be pretty spectacular, too.

Tip-Off is written with the diehard Carolina fan in mind. If you’re reading this letter, you probably fall into that category. I invite you to contact me on Twitter @FreeportKid with any feedback on the publication, or with any ideas about future content.

Enjoy the season, go Heels, and let’s cut down some nets!

Best Regards,

Adrian AtkinsonOctober 2011

POINTING TO THE PASSERS (ACKNOWLEDGEMENTS)I would like to personally thank a handful of people who helped make this publication possible: my wife Katya for her unconditional love, support, and understanding—thanks for all you do to allow me to pursue my hobby; Jim Walsh for providing me with this opportunity; the authors, who did a great job of writing pieces that were consistent with the vision of MSP Tar Heel Tip-Off; everyone who worked so hard to layout, design, and produce this book—especially Bryan Davidson, Jon Franke, Ryan Bray, and Jeff Powalisz; my parents and sister for a lifetime of love, guidance, encouragement, and wisdom; this edition’s for my daughter Allison—you’re the Michael Jordan of toddlers (sorry I couldn’t work in more panda bear content).

2011–12 Tar Heels

“The only thing I’m addicted to right now is winning.” —Charlie Sheen, 2/24/11

S o who is Charlie Sheen? And what does he have to do with North Carolina basketball? A Hollywood veteran, Sheen has played baseball players (Major League and Major League 2) and football players (Lucas), but never a hoopster (maybe he’d be interested

in the leading role in a Matt Doherty biopic?). Despite this glaring lack of basketball experience, anyone who has followed Sheen’s career or heard an interview with the quotable actor, knows that he’s all about winning.

And so is Roy Williams, although, besides winning, his addictions include Coca-Cola and folksy, down-home colloquialisms. After whetting their appe-tites with a taste of winning last season, Williams’ veteran Tar Heels are ready to join their coach in making it a habit. So let’s preview the upcoming season using the words of wisdom provided by actor-philosopher Sheen.

“I’m not fair game. I’m not a soft target. It’s over. There’s a new sheriff in town. And he has an army of assassins.”

The new sheriff for the 2010–11 Heels was, of course, Kendall Marshall. Replacing incumbent Larry Drew II as the starter after 17 games, the fresh-man point guard gave UNC an instant injection of energy and chemistry. More importantly, he set up his “army of assassins” for a boatload of easy baskets. Carolina fans don’t need an avalanche of numbers to convince them of how big the jump from Drew to Marshall was—it was profound, tangible, and crystal clear, both aesthetically and in the win column. Carolina basketball was back. That said, we’re still going to provide the avalanche of numbers. We’re MSP Tar Heel Tip-Off—that’s just how we roll.

by Adrian Atkinson

A Charlie Sheen–inspired look ahead to 2011–12

Winning!

2011–12 Tar Heels

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2011–12 Tar Heels

Table 1 compares the offensive and defensive efficiencies and “Four Factors” for UNC under the leadership of Drew and Marshall. With Marshall on the court, the Heels were about 11 points better per 100 possessions than with Drew at point guard. However, when adjusting for strength of opponent during each one’s possessions, that gap in efficiency margin ballooned to nearly 17 points/100 possessions. To put that difference into perspective, UNC’s Pythagorean win-ning percentage (i.e., its Pomeroy rating) during Marshall’s minutes ranked #2 in the country. With Drew running the show, it ranked #48.

The disparity in adjusted offensive efficiency was even more staggering: a fourth-ranked offense with Marshall at the helm versus a #79 unit spearheaded by Drew. So what did the Heels do better with the freshman in charge? First, they com-mitted fewer mistakes. With Marshall on the court, 17.7% of UNC’s offensive possessions ended in turnovers. With Drew at point guard, that number jumped to 19.4%. Second, they knocked down more shots. In Drew’s minutes, UNC shot 47.4% on two pointers and 31.3% behind the arc. During Marshall’s minutes on the floor, those numbers improved to 50.8% and 33.9%. It’s certainly no surprise that an upgrade at point guard resulted in fewer turnovers and more easy looks.

Table 2 summarizes the same data as Table 1, only this time it isolates the numbers for Marshall and Drew when paired with the other four starters (Dexter Strickland, Harrison Barnes, John Henson, and Tyler Zeller). These two lineups (Marshall + starters and Drew + starters) were easily the most used by Roy Williams last season, combining for over 500 minutes of court time. Like the team in general in Table 1, the starting unit was clearly better with Marshall in command. This time, the impact was even greater—nearly 26 points per 100 possessions after adjusting for strength of opponent, 25 of them on the offensive end. Sometimes, it takes but one simple change to transform a struggling quintet into an offensive juggernaut.

So we’ve seen that the team (specifically the offense) was significantly better with Marshall on the court. And we’ve seen that the main factors driving that improvement were a reduced turnover rate and an increased field-goal percentage (on 2s and 3s). So which Tar Heels in particular benefitted the most from playing alongside Carolina’s precocious freshman point guard? The answer to this question can be found in Table 3. The final column of this table introduces a metric dubbed the Marshall Premium. It’s an index comparing scor-ing efficiency (measured by True Shooting %, or TS%) when paired with Marshall to scoring efficiency when paired with Drew (during only the minutes when both players were on the team—i.e., before Drew’s departure). A Marshall Premium

Table 1: Marshall vs. Drew ii—A Point guard Comparison (All Minutes)Offense Defense

Pg Min. Pace net Eff. Adj. net Off. Eff. Adj. OE2 eFg% FTA Rate OR% TO% Def. Eff. Adj. DE3 eFg% FTA Rate DR% TOF%

Marshall 921 72.0 16.5 31.7 110.7 120.5 50.9 36.4 37.5 17.7 94.2 88.8 46.2 22.5 69.8 20.1

Drew II 464 73.5 5.4 15.1 100.9 107.3 47.3 42.5 36.8 19.4 95.5 92.2 46.8 28.8 71.1 19.7

Difference1 * -1.5 11.1 16.6 9.8 13.2 3.6 -6.1 0.7 1.7 1.3 3.4 0.6 6.3 -1.3 0.41. A “+” difference means that the team performed better in a given category with Marshall at PG. A “-“ difference means that the team performed better in that category with Drew II at PG.2. On an average possession last season, Marshall faced an opposing Defensive Efficiency of 95.5. Drew II faced an opposing Defensive Efficiency of 97.9.3. On an average possession last season, Marshall faced an opposing Offensive Efficiency of 110.3. Drew II faced an opposing Offensive Efficiency of 107.8

Table 2: Marshall vs. Drew ii—A Point guard Comparison (Minutes with Other Four Starters)

Offense Defense


Marshall 321 70.4 18.5 36.0 111.3 122.5 51.5 32.5 40.8 19.1 92.8 86.5 42.4 18.6 68.3 17.2

Drew II 191 72.6 1.9 10.1 92.4 97.7 44.8 31.3 37.0 19.0 90.5 87.6 44.7 20.4 71.9 19.4

Difference1 * -2.2 16.6 25.9 18.9 24.8 6.7 1.2 3.8 -0.1 -2.3 1.0 2.3 1.8 -3.6 -2.21. A “+” difference means that the team performed better in a given category with Marshall at PG. A “-“ difference means that the team performed better in that category with Drew II at PG.2. On an average possession with the starting lineup, Marshall faced an opposing Defensive Efficiency of 94.4 Drew II faced an opposing Defensive Efficiency of 98.1.3. On an average possession with the starting lineup, Marshall faced an opposing Offensive Efficiency of 111.5. Drew II faced on opposing Offensive Efficiency of 107.1

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of 110 means a player scored 10% more efficiently with Marshall at point guard than he did with Drew; a 90 means he scored 10% less efficiently. Again, the Marshall Premium applies only to the minutes during which both point guards were on the roster.

The third row of each player’s entry (“after Drew”) shows how he performed in the post-Drew era (although it does not separate out the Marshall minutes from the Strickland-at-point guard minutes). Prior to Drew’s departure, each member of the starting line-up was at least 18% more efficient as a scorer when paired with Marshall. However, due to the nature of the substitution patterns (including a staggering amount of 5-for-5 “line shifts”), the starters played between only 30 and 40% of their minutes alongside the freshman floor leader (a percentage that was much lower than that until Marshall took over the starting reins for the final four games of the Drew era). McDonald, Carolina’s top bench scorer, was also significantly more efficient when paired with Marshall. The rest of UNC’s bench (Bullock, Knox, and Watts) actually had slight ef-ficiency gains (7–11%) when paired with Drew. Based on the evidence in Table 3, it’s no surprise that the Heels’ offense (and particularly the starting unit) took off after the move to Marshall. While none of the starters kept up the Marshall-led efficiency they displayed before Drew’s departure (a couple of probable reasons why not: 1. The after-Drew numbers aren’t adjusted for strength of defense; 2. With his move to the starting lineup, Marshall + starters were playing relatively more minutes against opposing starters and relatively fewer against opposing reserves), they still exhibited some healthy Marshall Premiums. Barnes and Zeller—Carolina’s clear-cut top scoring threats—performed especially well in the “after Drew” period.

The loss of Drew, though clearly a net positive, did pose one potential dilemma: how would sophomore

Dexter Strickland fare in the backup point guard role? Strickland, Drew’s reserve at the position as a freshman, is certainly not blessed with pure point guard instincts. His court vision, ball handling, and passing skills—while more than adequate for a complementary playmaker—leave plenty to be desired as a floor general.

And Drew, struggling furiously to make the leap to ACC-caliber starting point guard, did have some flashes of brilliance in his role as a second-stringer (albeit interspersed with the stretches of poor decision making and lackadaisical defense that plagued his career as a starter). As the data in Table 4 supports, the team didn’t miss a beat in transitioning from Drew to Strickland. The adjusted efficiency margin was actually slightly better in Strickland’s point guard minutes than it was in Drew’s (with fairly comparable Four Factors numbers across the board).

The downside was that Marshall was called upon to play 35 minutes per game after Drew’s departure—a number that’s too high for any point guard in Roy Williams’ high-octane system, much less one trying to avoid a crash into the fabled freshman wall. Ideally, Marshall would be

Table 3: The Marshall Premium

Player Minutes % Min. FgA/40 Pts/40 TO/40 TS%On-Court

OEMarshall Premium

Henson: w/Marshall 197 40% 16.7 23.2 2.6 60.7 108.3

Henson: w/Drew 294 60% 13.5 15.3 4.1 45.3 94.2 134

Henson: after Drew 498 * 14.5 16.5 2.7 48.4 105.7

Barnes: w/Marshall 172 31% 19.3 26.3 4.0 59.0 117.6

Barnes: w/Drew 379 69% 16.2 16.4 2.5 44.8 102.0 132

Barnes: after Drew 519 * 19.8 23.4 2.1 53.9 109.2

Strickland: w/Marshall 154 30% 9.3 13.5 2.1 62.4 113.9

Strickland: w/Drew 366 70% 9.5 13.2 2.4 52.2 98.2 120

Strickland: after Drew 474 * 7.0 8.8 2.0 50.1 108.8

Zeller: w/Marshall 188 34% 12.4 20.5 1.9 64.7 119.8

Zeller: w/Drew 363 66% 15.5 21.6 2.0 54.8 101.9 118

Zeller: after Drew 488 * 15.2 23.5 1.9 62.4 112.5

McDonald: w/Marshall 196 68% 18.0 22.1 1.2 56.5 114.6

McDonald: w/Drew 94 32% 16.7 17.5 2.6 50.1 105.2 113

McDonald: after Drew 272 * 14.1 15.1 2.6 49.0 107.2

Bullock: w/Marshall 189 63% 18.4 20.1 0.6 52.0 120.1

Bullock: w/Drew 111 37% 15.9 19.8 3.2 55.9 100.5 93

Bullock: after Drew 94 * 15.7 6.8 0.4 20.8 92.8

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2011–12 Tar Heels

in the 28–32 minutes per game range, with the backup absorbing the remaining time. But during the season’s criti-cal stretch run, Williams was wary of resting Marshall for that many minutes. Even so, Strickland’s apprenticeship as a backup point guard was great experience, and should serve as a springboard for an expanded role (8–12 MPG) in that capacity this season. As the statistics at the bottom of Table 4 show, Strickland, though lacking the eye-popping assist numbers of a true point guard, performed admirably in his lead-guard cameo. In 2011–12, Carolina will certainly take a repeat of that stat line (11.3 pts/40, 5.4 ast/40, 3.67 A:TO) during the minutes when Marshall is catching a breather.

Although the love for the point guard known as “Butter” spread quickly and deservedly throughout Chapel Hill, Marshall still has some areas in need of improvement.

Like virtually all rising sophomores, he must take that next step in overall fitness/conditioning level—especially if he’s going to log one 35-minute game after another in March. He must also expand his offensive arsenal (more off-hand finishes in the paint when required, a more polished floater, etc.) and improve his efficiency as a scorer. He doesn’t need to turn into Ty Lawson overnight; he simply needs to make teams pay for overplaying him as a passer. Obviously, the vast majority of collegians make year-to-year developmental strides. For ACC point guards, how (on average) do those freshman-to-sophomore year improvements differ as a function of one’s location on the “pass-first vs. shoot-first” spectrum? For the answer, look no further than Table 5.

But, first, a brief methodological digression: 77 ACC PGs from 1980–2011 are included in this study. To qualify, they must have played 10+ MPG in both their freshman and sophomore seasons and logged the majority of their minutes (in both seasons) as a point guard. Players are categorized into four bins using two statistics from their freshman year: %Shots (the percentage of a team’s shots a player takes during his minutes) and %Assts (the percentage of teammates’ field goals that a player assists during his minutes). The average freshman point guard in this sample has a %Shots of 16.0 and a %Asst of 23.6 (Marshall’s numbers were 12.8 and 38.7). Pass-first PGs are classified as those with above-average %Assts and below-average %Shots as rookies (like Marshall). The opposite is true for point guards in the shoot-first bin. A third classification includes freshman point guards with above-average rates in both categories, and the fourth includes those with below-average rates in both.

As one might expect, the above-average/above-average bin contains the best freshmen (on average), including Heels like Raymond Felton, Ty Lawson, and Kenny Smith. The below-average/below-average contains the worst (like Adam Boone). The pass-first and shoot-first bins are strikingly simi-lar in average quality (as measured by PER and WORP/35) despite having wildly different styles of point guards. In terms of freshman-to-sophomore development, pass-first point guards don’t seem to make extraordinary leaps—even as scorers (where they have the most room for improvement). Their %Shots number does increase significantly more than the average point. However, neither their scoring rate (Pts/40) nor scoring efficiency (TS%) make a jump that’s

Table 4: The Backup PlanOffense Defense


Drew II 464 73.5 5.4 15.1 100.9 107.3 47.3 42.5 36.8 19.4 95.5 92.2 46.8 28.8 71.1 19.7

Strickland 82 69.0 2.5 17.1 103.2 112.2 45.4 33.1 40.5 17.8 100.7 95.1 45.0 25.2 63.5 19.1

Strickland’s numbers After Drew Left the Program

Min. FgA/40 Pts/40 TS% Asst/40 TO/40 A:TO

As a PG 82 7.8 11.3 53.0 5.4 1.5 3.67

As a SG 393 6.8 8.2 49.3 3.1 2.1 1.431. On an average possession, Strickland (as a PG) faced an opposing Defensive Efficiency of 95.6 Drew II faced an opposing Defensive Efficiency of 98.1.2. On an average possession, Strickland (as a PG) faced an opposing Offensive Efficiency of 110.1. Drew II faced on opposing Offensive Efficiency of 107.1.

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distinguishable from the average point. Shoot-first point guards, conversely, do make a significant improvement in their sophomore-year assist rates (Asst/40) relative to the average point. What does this mean for Marshall? Just that he’s likely to make incremental progress as a scorer rather than having a larger-than-average sophomore-year bump in this facet of his game.

Marshall is a special breed of pass-first point guard, how-ever: his freshman-year %Asst of 38.7 ranks second in the ACC over the 1980–2011 timeframe, behind only Chris Corchiani. And his pass-first quotient (defined as %Asst divided by %Shots) trails only Corchiani, too. To see how other freshman points with high pass-first quotients developed, we looked at the top 10 in this category. Two of the 10, Larry Drew II and T.J. Bannister, transferred out of the ACC. The remaining eight—a group com-posed of Corchiani, Terrell Stokes, Ed Cota, Sidney Lowe, Bobby Hurley, Steve Blake, Muggsy Bogues, and Derrick Phelps—all completed four-year ACC careers. Not a bad group. It includes four national champions (and five total championships) and six guys who had at least a cup of coffee in the NBA. It also includes the three most prolific assist men in NCAA history. (and four of the top five). So how did Kendall Marshall’s freshman campaign compare to this esteemed collection of pass-first ACC PGs? Quite well, thanks (as seen in the final rows of Table 5).

Marshall was clearly a better passer than that group (on average), and arguably a better scorer (slightly higher

rate, slightly lower efficiency). As scorers, the group of extreme pass-first points made steady year-to-year progress without compromising their hoops DNA (the abil-ity/willingness to distribute). If Marshall follows this type of development path (and stays four years, of course), he’ll likely become the fourth member of the 1,000- assist club. Already a fan favorite, he’d one day reside in the thin and rarefied air that slowly transforms reality into folklore. He might even get his jersey in the rafters. But that’s somewhere down the road. For now, Carolina fans can just be grateful that he’s not Larry Drew II.

“I’m different. I have a different constitu-tion; I have a different brain; I have a different heart. I got tiger blood, man.”

One of Charlie’s signature quotes, this one sums up Harrison Barnes neatly. The Ames, IA, sophomore is a different breed than many of his one-and-done, NBA-or-bust contemporaries. As a guy who seems to buy in to the concept of a holistic college experience, he’s determined to enjoy the ride as a student-athlete (while checking off a few personal goals along the way). And, about that tiger blood? As late-game dagger after late-game dagger can confirm, yeah, he’s got it.

Table 5: Development of ACC Point guards—Freshman to Sophomore YearPass-First FR Pgs—Above-Average %Asst, Below-Average %Shots (n = 24)

Class MPg Pts/401 Asst/401 A:TO TS% %Shots %Asst PER WORP/35

FR 22.2 9.1 7.4 1.79 50.2 12.8 28.5 12.9 1.05

SO 28.0 10.5 7.0 1.93 52.2 14.8 28.2 14.3 1.78

% Change +26.1% +15.4% -5.4% +7.8% +4.0% +15.6% -1.0% +10.9% +69.5%

Shoot-First FR Pgs—Above-Average %Shots, Below-Average %Asst (n = 20)


FR 20.3 13.9 4.6 1.36 50.8 20.1 18.8 12.7 0.91

SO 27.2 14.6 5.1 1.67 52.0 20.2 21.2 15.3 1.88

% Change +34.0% +5.0% +10.9% +22.8% +2.4% +0.5% +12.8% +20.5% +106.6%

Pgs with Above-Average %Asst and %Shots as FR (n = 14)


FR 28.4 13.8 6.6 1.67 52.3 19.4 28.6 14.9 1.93

SO 31.0 16.2 6.0 1.66 53.7 21.6 26.3 16.8 2.60

% Change +9.2% +17.4% -9.1% -0.6% +2.7% +11.3% -8.0% +12.8% +34.7%

Pgs with Below-Average %Asst and %Shots as FR (n = 19)


FR 20.8 8.7 4.7 1.53 49.2 13.2 18.7 9.8 0.40

SO 27.1 10.7 5.9 1.90 52.9 14.7 24.0 12.9 1.26

% Change +30.3% +23.0% +25.5% +24.2% +7.5% +11.4% +28.3% +31.6% +215.0%

All Qualifying ACC Pgs (n = 77)


FR 22.5 11.1 5.9 1.59 50.5 16.0 23.6 12.4 1.01

SO 28.1 12.7 6.1 1.81 52.6 17.4 25.0 14.7 1.83

% Change +24.9% +14.4% +3.4% +13.8% +4.2% +8.8% +5.9% +18.6% +81.2%

Extreme Pass-First Pgs: 4-year Development (n = 8)


FR 22.4 8.7 8.2 2.00 53.1 11.0 30.1 15.4 1.58

SO 33.0 10.2 8.3 2.33 54.6 13.3 31.4 17.5 2.87

JR 33.8 11.7 8.3 2.28 53.7 15.8 33.5 17.5 2.99

SR 34.5 13.3 8.7 2.57 57.9 16.2 35.3 19.7 3.69

Marshall (FR) 24.6 9.7 9.7 2.50 51.8 12.8 38.7 16.0 1.411. Pace-adjusted numbers

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But, while Tip-Off loves that Barnes values education and plays the saxophone, we’re here to break down the basketball side of things. And Table 6 is a great place to start.

As the season progressed, the so-called Black Falcon became a more and more prolific scorer. As we learned in Table 3, some of that improvement was attributable to more minutes paired with Marshall. But, as Barnes moved along his own collegiate learning curve, he began to better understand how and when to get his shot within the Carolina system. More importantly, he began to appreciate the distinction between a good early opportunity and one that he could get at any point in the possession. There’s no doubt that Roy Williams wants to play fast, but not at the expense of poor shot selection.

Summarizing Barnes’ scoring progression by month:November: 11.3 PPG, 16.0 Pts/40, 43.9 TS%,

26.3 FTA Rate, 31.3 3PtA Rate, 26.5 %ShotsDecember: 13.0 PPG, 18.9 Pts/40, 48.8 TS%,

36.8 FTA Rate, 42.7 3PtA Rate, 26.2 %ShotsJanuary: 13.3 PPG, 20.7 Pts/40, 53.5 TS%,

27.3 FTA Rate, 33.8 3PtA Rate, 28.1 %ShotsFebruary: 17.0 PPG, 23.8 Pts/40, 50.0 TS%,

18.4 FTA Rate, 40.0 3PtA Rate, 32.8 %ShotsMarch: 21.6 PPG, 24.9 Pts/40, 59.5 TS%,

23.1 FTA Rate, 44.2 3PtA Rate, 30.7 %ShotsHis scoring average (on a per-game and per-minute

basis) went up in every month. Except for a blip in February (associated with a pronounced spike in usage rate), so did his scoring efficiency. His role in the offense (large to begin with) continued to trend upwards, too. When a player can simultaneously combine increased usage with increased efficiency, his scoring rate is going to skyrocket. So how did Barnes pull off this feat? From

the statistical summary, we can infer it that wasn’t at the free-throw line. Barnes’ rate of getting to the charity stripe actually trended down after the non-conference portion of Carolina’s schedule concluded. For answers, let’s turn to Table 6.

Table 6 reveals one area that played a large role in Barnes’ development as a scorer: his ability to get to (and finish at) the rim. After he attempted just 22.7% of his field goals from close range (i.e., lay-ups and dunks) in November–January, Barnes spiked that figure to 26.8% in February–March. In conjunction with this increase in close attempts, his close FG% exploded from a mediocre 54.9% in November–January to an excellent (especially for a wing) 67.1% over the final two months of the campaign. And these numbers don’t even adjust for the

higher caliber of defense that the Heels faced in February and March. To put Barnes’ improvement at the rim into perspec-tive, consider this: in November–January, for every 100 total (close and non-close) field goals he attempted, Barnes scored 25 close points (not including free throws drawn on close at-tempts); in February–March, that number jumped to 36 close points per 100 attempts.

Barnes’ development as a close scorer can be partially tied to Marshall’s play: his percentage of assisted close shots rose from 7.6% (in first three months) to 9.9% (in final two months) of his total attempts. Many of those additional attempts were a direct result of a sensational Marshall pass. But, more significantly, Barnes’ close-scoring progression was related to

Table 6: The Month-by-Month Emergence of Harrison BarnesShot Type nov. Dec. Jan. Feb. Mar. Total% of Close: assisted 7.5% 7.4% 7.8% 14.4% 6.1% 8.9%FG% 66.7% 80.0% 33.3% 72.2% 66.7% 65.9%% of Close: off-the-dribble 8.7% 4.4% 7.8% 9.6% 10.9% 8.9%FG% 42.9% 66.7% 50.0% 58.3% 62.5% 56.8%% of Close: put-backs 8.7% 5.9% 9.1% 8.0% 5.4% 7.2%FG% 42.9% 50.0% 71.4% 50.0% 100.0% 63.9%% of Close: total 25.0% 17.7% 24.7% 32.0% 22.5% 25.0%FG% 50.0% 66.7% 52.6% 62.5% 72.7% 62.1%% of Floaters 8.7% 11.8% 13.0% 6.4% 10.2% 9.7%FG% 14.3% 50.0% 20.0% 37.5% 53.3% 37.5%% of Mid-range jumpers 26.3% 22.1% 26.0% 16.8% 13.6% 19.5%FG% 23.8% 40.0% 60.0% 33.3% 45.0% 40.2%% of Turnaround jumpers/post moves 8.7% 5.9% 2.6% 4.8% 9.5% 6.6%FG% 42.9% 25.0% 0.0% 33.3% 21.4% 27.3%% of 3 pointers: catch-and-shoot 30.0% 35.3% 27.3% 36.0% 34.7% 33.2%FG% 29.2% 20.8% 38.1% 31.1% 37.3% 32.1%% of 3 pointers: off-the-dribble 1.3% 7.4% 6.5% 4.0% 9.5% 6.0%FG% 100.0% 60.0% 40.0% 20.0% 50.0% 46.7%% of 3 pointers: total 31.3% 42.7% 33.8% 40.0% 44.2% 39.2%FG% 32.0% 27.6% 38.5% 30.0% 40.0% 34.4%% of And-ones 2.5% 4.4% 5.2% 4.8% 3.4% 4.0%

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his own ability to attack the rim using the dribble. His percent-age of close attempts off the bounce increased from 7.1% in November–January to 10.3% in February–March.

A second explanation for Barnes’ increased scoring efficiency relates to his (relative) de-emphasis of the inter-mediate game. His mid-range game was extremely polished for a college freshman. Having the ability to create step-back mid-range jumpers or floaters in the paint is an essential skill for an elite scorer—especially one assuming as much of the offensive burden as Barnes did. While a necessary part of any scorer’s repertoire, the intermediate attempts are generally at an efficiency disadvantage compared to higher-percentage close looks and higher-valued ones from behind the arc. In November–January, 58.3% of Barnes’ attempts were either at the rim (22.7%) or behind the arc (35.6%). The additional 41.7%, of course, were in the intermediate range (primarily mid-range jumpers and floaters, with a few turnaround jump-ers/non-close post moves mixed in, as well). In February–March, that distribution of attempts shifted to 69.1% at the rim (26.8%) or behind the arc (42.3%) versus only 30.9% from intermediate distances. As with his close FG% (though not as drastically), Barnes’ efficiency improved from all over the court in February–March. His 3Pt% increased from 32.5% to 35.7% and his intermediate FG% jumped from 36.2% to 38.1%. While the slight uptick in intermediate efficiency helped his overall scoring efficiency slightly, the primary driver was the reallocation of intermediate attempts to close/three-point chances. If this mix of field goal attempts can continue this season (and Barnes can approach the 40.0% from behind the arc that he shot in March), expect Barnes to approach the 59.5 TS% he posted last March. And, if he can start getting to the free-throw line more consistently, maybe he’ll even eclipse it.

A discussion of Barnes’ scoring efficiency segues nicely into an examination of Table 7, which lists the most and least efficient scoring seasons in Carolina history for players who averaged at least 15 points per game. For the least efficient campaigns, the analysis is limited to the modern era (1975–2011) due to fundamental changes in overall offensive

efficiency since the 1950s and 1960s. Since 1975, among those Heels with 15-point per game seasons, only Sean May as a sophomore has scored less efficiently than Barnes did last year. May, of course, bounced back strong as a junior, posting a TS% of 62.0 (up from 51.1% as a sophomore) while leading UNC to a national title. Of the 51 UNC player-seasons with 15 points per game since 1975, 36 of them have coincided with a TS% of at least 60. Another 16 have been accompanied by a TS% in the 55–60 range. In only 5 (including Barnes’ in 2010–11) has a Carolina player’s TS% slipped below 55. In the modern era, the average TS% across all 51 15-point per game player-seasons at UNC is 60.4. By continuing his late-season run of efficiency (as described in the preceding paragraphs), Barnes should elevate himself close to that mark as a sopho-more. And, given his high usage rate, a Harrison Barnes who is scoring that efficiently will spell trouble for the rest of the country (as well as returning the Heels to their rightful place among the nation’s top 10 in adjusted offensive efficiency after a two-year hiatus; the first six of Williams’ UNC teams were all top 10 in this category, including three #1s—the last two squads have ranked 65th on average, including last season’s 38th). Granted, superheroes like the “Black Falcon” are known more for their excesses than their efficiency. But in 2011–12, get ready to meet the new and improved “Sleek Black Falcon.”

“People can’t figure me out, they can’t process me; I don’t expect them to. You can’t process me with the normal brain.”

Table 7: Most and Least Efficient 15-PPg Seasons in Carolina History—ACC EraMost Efficient Least Efficient

Player Year PPg TS% Player Year1 PPg TS%

1. D. Wuycik 1972 18.0 68.1% 1. S. May 2004 15.2 51.1%

2. D. Wuycik 1971 18.4 67.7% 2. H. Barnes 2011 15.7 52.2%

3. M. O’Koren 1978 17.3 67.6% 3. D. Williams 1995 15.9 53.9%

4. B. Daugherty 1986 20.2 66.0% 4. J. Forte 2000 16.7 54.3%

T-5. T. Lawson 2009 16.6 65.9% 5. J. Forte 2001 20.9 54.6%

T-5. V. Carter 1998 15.6 65.9% 6. J. McInnis 1996 16.5 55.4%

7. R. Wallace 1995 16.7 65.7% 7. A. Wood 1981 18.1 56.1%

8. B. Daugherty 1985 17.3 65.6% 8. A. Jamison 1997 19.1 56.4%

9. S. Perkins 1984 17.6 65.4% 9. J. Capel 2002 15.6 56.6%

10. B. Bunting 1968 18.0 64.8% 10. R. Fox 1991 16.9 56.7%1. Only years in the “modern era”—1975-present—are included in this list. In the ’50s and ’60s, when shooting percentages/offensive efficiencies were lower across the board, several Tar Heels would have qualified for this list. Without the necessary data to do an era adjustment, we decided to include only ’75-present.

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2011–12 Tar Heels

This Sheen gem goes out to John Henson, one of the most unorthodox players to ever wear the Carolina blue. Normal-brained opponents are still trying to figure him out; his extreme length has been wreaking havoc on their game plans ever since his move to the post. And, at times, UNC fans are still trying to process their enigmatic power forward.

There’s the version of John Henson that most of us like to recall: the guy with the perpetual smile on his face, the one having more fun on the court than any Heel in recent memory, the super athlete dunking every lob that Marshall throws near the rim and rejecting every shot that comes near the paint—talking trash and grinning the whole time.

Then there’s the other John Henson: the guy who’s casually goal tending Washington’s last-second prayer, the one who tosses up wild shots so frequently that you wonder if he’s training for a H-O-R-S-E tournament, the player whose demeanor is sometimes better suited for pick-up games at the park than primetime in the ACC.

It’s really the same loose and fun-loving guy, of course; it’s just that, at the highest levels of competitive hoops, some-times that mentality is a blessing and sometimes it’s a burden.

Table 8 presents “The Curious Case of John Henson.” According to the +/- data, Henson was Carolina’s top-ranked defender and its bottom-ranked offensive player last season. While it’s indisputably true that the Heels were 11 points per

100 possessions better, offensively, with Henson on the bench (in favor of Watts or Knox, generally) than they were with him on the court, that’s not necessarily the end of the story—especially with a metric as notoriously noisy as +/- (and a sample size as small as a college season). Let’s break down a few possible theories for Henson’s (offensive) +/- malaise.

As mentioned, +/- is statistically noisy and borderline unreliable over such small samples. Throw the data in the trash. Possibly true, possibly the explanation for Henson’s poor numbers, but not especially interesting as a discussion point. Moving on…

Last year’s version of Henson was simply not a good offensive player. Moreover, he was inefficiently using a high number of possessions—possessions that could have been better allocated among his higher-efficiency teammates. Table 9 provides compelling evidence to support this theory. As seen, Henson’s Offensive Rating of 97.6 was easily the lowest of the Roy Williams era among post players who played at least 40% of the team’s minutes. Likewise, his Value Add—a statistic created by CrackedSidewalks.com’s John Pudner that measures a player’s offensive value relative to a replacement-level player—was also at the bottom of the list. Value Add calculates the percentage increase in points that a player is responsible for as compared to an average ninth/10th man who uses an identical amount of possessions in an identical number of minutes. In Henson’s case, the number is 1.09%. For an average Roy Williams UNC post player (who’s played in at least 60% of the team’s minutes), it’s 4.62%. While Henson’s O Rating and Value Add were well below average, the number of possessions he used was not. Simply put, Henson used a disproportionately large share of possessions relative to his level of offensive efficiency last season. Knox and Watts were similarly inefficient offensive players, but both used significantly fewer possessions than Henson (and, thus, more were available to allocate to more efficient Tar Heel scorers during the Justins’ time on the court).

The offense was especially bad when it relied on Henson to be the primary post scorer—that is, when he was on the court without Tyler Zeller. As a secondary post option, Henson was serviceable last season. But when asked to carry the load alongside Knox or Watts, the team’s offensive efficiency took a severe hit. This theory is also supported by

Table 8: On-Court/Off-Court impact (Players with 10+ MPg)—2010-11 +/- DataOffensive impact Defensive impact

PlayerOffensive

PlayerDefensive

On Court/Off Court On Court/Off Court

1. Zeller 12.4 1. Henson 2.9

2. Marshall 11.3 2. Zeller 2.2

3. Barnes 5.9 3. Marshall 2.1

4. McDonald 5.0 4. Barnes 1.5

5. Bullock 2.5 5. Drew II 0.2

6. Strickland -2.6 6. McDonald -0.8

7. Knox -4.6 7. Knox -2.5

8. Drew II -8.0 7. Strickland -2.5

9. Henson -10.9 9. Bullock -3.5

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the +/- data, as presented in Table 10. With both Henson and Zeller on the floor, UNC’s adjusted offensive efficiency was a solid 116.3. With just Zeller on the floor, it exploded to a sensational 126.1. With just Henson, however, the adjusted efficiency plummeted to 98.6. As an aside (and not surpris-ingly), Carolina’s adjusted defensive efficiency was clearly the best with both starting big men on the floor. It was slightly better with only Henson than it was with only Zeller. The bottom of Table 10 shows the offensive splits for Henson and Zeller when paired together versus when on the floor separately. When sharing the court, each used about 23% of the team’s possessions—Zeller much more efficiently than Henson. When not paired with each other, the UNC big men became more involved offensively—Zeller used about 24% of Carolina’s possessions and Henson 26%. Zeller’s scoring efficiency skyrocketed—a TS% of 65.1—in the non-Henson minutes (when he was the true primary post option instead of a co-primary one). Henson’s stayed about the same, quite inefficient for a top option in the paint, and that inefficiency seemed to be reflected in the team’s numbers.

Looking ahead to the 2011–12 season, what can the fan base expect from Henson on the offensive end? If he continues to combine low efficiency with high usage, the

team figures to again struggle (in a relative sense) offensively in his minutes. The remedies to this are, of course, for Henson to: 1. Improve his efficiency, 2. Decrease his usage, or 3. Some combina-tion of the two. A simple way to become more efficient involves nothing more than improving his FT%. If Henson can just maintain the 59.1% he shot from the line during February–March, then that will be a nice step in the right direction.

Another possibility: Henson focuses on becoming the best garbage-man scorer in the nation. He could look to score in transition, off of set play lobs, whenever the defense is broken down by dribble penetration, and by grabbing/converting as many offensive rebounds as humanly

possible. Scrap entirely (or at least severely limit) the mid-range jumpers, the off-balance post moves/jump hooks, and anything off the dribble that doesn’t result in a dunk/lay-up (Henson was 2 of 14 on floaters last season; not a huge number, but probably unnecessary for a post player). This would likely result in both lower usage and higher efficiency, a win-win for the Carolina offense. There’s one more option: Henson puts the entire offensive package together and becomes a force on that end. He starts knocking down his free throws, consistently hitting his jump hooks and mid-range jumpers, and using his burgeoning post footwork and crafty ball fakes to get to the rim from the low block.

Henson’s potential is massive; it’s not out of the question that he could realize a huge jump in offensive efficiency (while maintaining that high usage rate). And, if that happens, Carolina would become an overwhelmingly heavy favorite to cut down the nets in New Orleans. Short of this type of Henson offensive metamorphosis, however, the best-case scenario might be the 2009 low-post model. Instead of the co-alpha dogs Carolina featured last year (Zeller with a %Poss of 23.0, Henson with a 23.7%), Zeller can assume the Hansbrough role (%Poss of 26.7, O Rating of 124.0 in 2009) with Henson sliding into the Deon Thompson

Table 9: Post Efficiency in the Roy Williams EraFrontcourt Starters (%Min. of >60%) Frontcourt “Reserves” (%Min. of <60%)

Player Year O Rating %Poss. %Min.Value Add

Player Year O Rating %Poss. %Min.Value Add

Hansbrough 2008 125.2 26.8 81.4 8.7% M. Williams 2005 119.4 20.7 54.1 3.9%

Hansbrough 2009 124.0 26.7 67.5 6.6% Davis 2010 111.7 21.5 43.3 2.2%

May 2005 118.6 28.0 67.0 6.4% Thompson 2008 104.0 19.7 52.9 1.7%

Hansbrough 2006 118.7 26.6 76.0 6.3% Davis 2009 108.3 17.7 47.0 1.6%

Hansbrough 2007 119.8 26.2 74.2 6.2% Zeller 2010 106.8 24.1 31.5 1.4%

Zeller 2011 120.1 23.0 70.1 5.1% Noel 2004 103.7 14.8 41.6 1.1%

J. Williams 2005 122.9 20.5 60.0 4.8% Thompson 2007 104.3 18.4 30.9 0.8%

Wright 2007 118.9 21.1 66.2 4.3% Stepheson 2008 101.7 15.8 33.9 0.7%

J. Williams 2004 112.1 21.4 63.7 3.8% Knox 2011 96.7 17.1 36.0 0.4%

Noel 2006 109.3 19.5 84.3 3.4% Stepheson 2007 99.5 18.2 15.8 0.3%

May 2004 103.7 26.2 68.5 3.3% Watts 2011 96.9 13.3 21.1 0.2%

Thompson 2010 105.7 24.4 66.8 2.8% T. Wear 2010 93.2 19.8 21.7 0.1%

Thompson 2009 106.4 19.5 61.8 2.1% Sanders 2006 87.0 13.5 30.5 -0.2%

Henson 2011 97.6 23.7 66.6 1.1% – – – – – –

Average – 114.5 23.8 69.6 4.6% Average – 102.6 18.0 35.4 1.1%

Table 10: Carolina’s Big Men—How Zeller and Henson Play With and Without Each Other

Frontcourt Min. Pace net Eff. Adj. net Off. Eff. Adj. OE eFg%FTA Rate

OR% TO% Def. Eff. Adj. DE eFg%FTA Rate

DR% TOF%

Offense Defense

Henson-Zeller 726 71.5 14.3 28.6 107.2 116.3 49.4 36.1 40.2 18.8 92.9 87.7 45.0 20.6 68.6 20.2

Only Zeller 320 74.1 18.8 32.8 116.4 126.1 53.9 49.5 37.1 17.8 97.6 93.3 49.3 32.7 72.4 20.1

Only Henson 269 72.0 -6.4 6.7 90.8 98.6 42.6 33.9 33.9 19.5 97.2 91.9 45.5 24.2 68.6 19.1

Neither 170 73.6 12.7 10.4 108.2 107.2 49.6 31.0 30.6 15.1 95.5 96.8 47.0 29.5 72.8 17.8

Minutes FgA/40 Pts/40 TO/40 TS% %Shots %Poss

Zeller w/Henson 726 14.7 21.4 1.7 57.8 23.4 22.6

Zeller w/o Henson 320 14.6 24.1 2.5 65.1 24.2 23.8

Henson w/ Zeller 726 14.1 16.9 3.0 50.0 22.5 22.8

Henson w/o Zeller 269 16.1 18.8 3.1 50.6 25.8 26.0

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2011–12 Tar Heels

role (%Poss of 19.5, O Rating of 106.4 in 2009). That’s contingent upon Zeller—not cut from the same carve-out-deep-position, demand-the-ball-in-the-post mold of May and Hansbrough—proving he’s capable of shouldering a slightly larger offensive burden, though. It’s also contingent upon Henson demonstrating better decision making, shot selection, and offensive discipline.

While lingering questions might remain about Henson’s offensive role and development, no one should question what he brings to the table defensively. The reigning ACC Defensive Player of the Year, he should collect plenty of national defensive hardware this season, too. A true defensive game changer, opponents made 42.0% of their two pointers with Henson on the floor and 49.6% of them with Henson on the bench. On two pointers defended by Henson, that number dropped to 27.0%. He forced 247 missed two-pointers in 37 games (nearly seven per game), blocking 118, and altering doz-ens of others. His unquenchable appetite to block everything cost the Heels a few weak-side rebounds (despite Henson’s fantastic individual defensive rebounding, the team actually grabbed a higher percentage of defensive boards (72.6%) with him on the bench than they did with him on the court (68.6%)), but that’s a small price to pay for the paint intimida-tion factor Henson provides. On the defensive end, he had the best Stop %, the biggest defensive +/- impact, and used (easily) the highest percentage of Carolina’s defensive possessions (25.2% based on defensive charting data). Add it all up, and

Henson’s defensive impact is profound and undeniable. And, believe it or not, it can become even greater if

Henson can make better decisions on the offensive end. Transition defense, an area in which the Heels are generally susceptible, is hurt by live-ball turnovers and quick or badly missed shots. Henson committed 1.8 live-ball turnovers per 40 minutes last season; UNC’s other post players (Zeller, Knox, and Watts) were all between 1.0 and 1.3. The average live-ball turnover is turned into a fast-break opportunity 64% of the time against Carolina, with an offensive ef-ficiency of 138.8. Likewise, 21% of Henson’s missed field goals were turned into opposing transition opportunities that were converted with an efficiency of 142.4. All non-Henson Carolina misses were turned into fast breaks 19% of the time, but with an efficiency of just 106.4. Slightly better shot selection (which facilitates better defensive transition) might help Henson’s misses lead to fewer easy run-outs. These examples of bad offense leading to bad defense are pretty rare, but are the types of plays that can make the difference between a Final Four flameout and a national championship. For the 2011–12 Heels, the champions vs. close-but-no-cigar distinction might be determined by the size of the strides that Henson makes on the offensive end.

“I’m tired of pretending I’m not special. I’m tired of pretend-ing I’m not a total bitchin’ rock star from Mars.”

In reality, there’s almost no comparison between the opinionated and ostentatious Sheen and Zeller, the

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soft-spoken Midwesterner. But, during last year’s postseason run, Zeller seemed to be channeling his inner Charlie. After being content to fit in for most of the season, Carolina’s talented seven footer broke out in a big way in March. There’s no sense in pretending any more: Zeller is special. And, if he’s as assertive all year as he was in last year’s Tournament run, the Tar Heels will be special, too.

During the regular season, Zeller attempted 23% of UNC’s shots when he was on the court. In the postseason, that number increased to 26%. In the four NCAA Tournament games, it inched up to 27%—Hansbrough/May territory. All the while, Zeller maintained his trademark offensive efficiency; if he can combine last year’s efficiency with last March’s usage rate, he’s staring an All-American senior season squarely in the eyes. Not a space eater or super physical post-up threat like the aforementioned Carolina big men, Zeller became better and better at finding ways to establish deep post position. It helps having an entry passer like Kendall Marshall delivering the ball at the precise instant, too. If Zeller continues to demand paint touches and evolves into a true alpha post, it will give Roy Williams the horse he can ride the whole way to a third title.

Even without fully blossoming until March, Zeller was still Carolina’s best player by just about any metric one prefers. While you can make a compelling case for Marshall as the most valuable/most irreplaceable Tar Heel, it’s hard to make a case for anyone other than Zeller for most outstanding (although Harrison Barnes will likely have something to say about that in 2011–12). He led the team in Offensive Rating in an overwhelming fashion; likewise for Pudner’s Value Add statistic. Zeller also led the team in PER and WORP/35, was first in net on-court/off-court +/- impact (first in offensive on court/off-court, second in defensive on-court/off-court), and trailed only Henson in defensive Stop %.

An underrated defender (overshadowed by Henson’s combination of greatness and flair), Zeller drew 29 charges to go along with his 45 blocked shots. Of the 45 blocks, 22% were rebounded by Zeller himself and 78% were controlled by UNC (with 22% going back to the opponent for only two second-chance points). Henson grabbed 15% of his own blocks, the team gained possession on 53% of them, and 47% went back to the offense (for 50 second-chance points). Zeller’s blocks turned into transition opportunities for Carolina 53% of the time, and the Heels scored 0.53 fast-break points per each of his blocks. For Henson, those num-bers were 32% and 0.44. Due to their incredible frequency (and the intangible/intimidation benefits associated with them), Henson’s blocks were unrivaled in their importance. But one could certainly argue (based on the aforementioned data) that Zeller’s average block was more valuable than Henson’s average block. The bottom line, though, is that Henson/Zeller figures to be the most dominant defensive post duo in the nation. As long as these players are healthy and anchoring the defense, the Heels figure to be among the

top 10 all year on that end of the court (and they’ll probably exceed their #6 national ranking of 2010–11 in adjusted defensive efficiency). If there are any fans out there still pretending that Tyler Zeller isn’t special, it’s time to stop. Charlie says so.

“Because that’s how I roll. I have one speed. I have one gear: Go.”

In addition to sharing an addiction to winning, Sheen and Roy Williams also share a predilection for speed. No high-major coach is as consumed with playing fast as Williams, and the results speak for themselves. Table 11 breaks down Carolina’s offensive efficiency by possession type (primary break, secondary break, halfcourt) over the past four seasons. As seen, UNC is able to use nearly a quarter of its total possessions in the ultra-efficient primary break. Since losing Ty Lawson, however, the primary-break efficiency has declined precipitously; it’s still outstanding, just not otherworldly like in the Lawson era. In fact, the efficiency in all three facets has dropped since the Lawson-Ellington-Green-Hansbrough core left town. That’s not surprising, of course; that group was sensational offensively, and vastly underrated in terms of its half-court execution.

But with a year of shared experience (crucial to mastering Carolina’s freelance passing game, which relies more on

Table 11: Efficiency in Transition and the Halfcourt—2008–112008*

Possession Type % Possessions Offensive Efficiency Points/game

Primary break 23.0% 143.2 24.9

Secondary break 21.1% 115.3 18.5

Halfcourt offense 55.9% 107.4 44.6

Total 100.0% 116.1 88.0

2009





Total 100.0% 118.9 89.8

2010





Total 100.0% 102.5 74.5

2011





Total 100.0% 106.4 77.5

4-Year Average





Total 100.0% 112.5 82.5*Excludes the untelevised SC State game

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2011–12 Tar Heels

reading and reacting rather than running designated sets) and the maestro Marshall sublimely directing the flow, the halfcourt offense figures to make big strides this season. The secondary break, largely neglected by the end of last season, should also really benefit from the added experience.

One lingering question regarding Marshall is his ability to execute at Williams’ preferred speed. The (unadjusted) pace with Marshall in the game was 72.0 possessions/40 minutes last season; a drop from Drew’s 73.5 (although Drew played a higher percentage of minutes against the soft underbelly of the schedule—games in which it’s easier to dictate tempo). But both tempos are a drop from the halcyon days of Lawson, who guided the Heels to a pace of 75.1 in 2008 and 75.2 in 2009. As Lawson can attest to (the shouts of “run!” are probably still echoing in his ears), it’s hard for any point guard to play as fast as Roy Williams wants—much less one who’s a freshman and, like Marshall during the stretch run, called upon for 35 minutes per night. The master of the fullcourt hit-ahead pass, Marshall has plenty of tricks to speed up tempo that don’t involve pure endline-to-endline speed. But the best way to dictate pace might involve defensive pressure and forcing live-ball turnovers (where Felton and the ’05 champs thrived).

That’s not Marshall’s forte as a defensive point guard; he’s more of a contain-and-close-out defender than a ball-pressure one. Of course, forcing missed shots and corralling

defensive boards—an area where the 2011–12 Heels figure to thrive—is another proven strategy for speeding up the game. And, as this group becomes more and more efficient in the halfcourt (the upside is high with Marshall running the show), the need to get out in transition will be lessened, at least theoretically. Practically, however, Williams will demand just as much pushing the tempo as always. The degree to which his team can comply will play a large role in determin-ing just how high their overall offensive efficiency can climb in its effort to join an already championship-caliber defense.

“I am battle-tested bayonets, bro.”In terms of close-and-late clutch experience, last year’s

young Heels became battle-tested in a hurry. They played in 17 games that were decided by seven or less points, compiling a record of 12–5 in those contests. In total, there were 97 clutch minutes last season (margin of seven points or less, less than five minutes left in the game/overtime), as compared to 76 in 2008, 50 in 2009, and 87 in 2010. Obviously, fewer clutch minutes are better if it means you’re dominating teams and winning big (a la the ’09 Heels, with their scant amount of close-and-late action). That’s likely the direction the ’12 Heels will be moving in: fewer nail-biters and more blowout victories. Still, it’s inevitable that there will be several close games along the way, especially as Tournament time rolls around. And that’s when all the close-game experience from last season will start paying big dividends.

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Table 12 details the clutch statistics from last season. Not surprisingly, Harrison Barnes leads the way. His close-and-late numbers are even more amazing considering the rough start to his career in those situations. Against Minnesota, Vanderbilt, UNC-Asheville, College of Charleston, Kentucky, and Long Beach State, Barnes missed all eight of his clutch field-goal attempts (including his only three pointer), his only three clutch free throws, and committed four clutch turnovers. Finally, against Texas, he hit a three pointer with 12 seconds remaining to tie the score. Starting with that dagger, Barnes made 21-of-35 clutch shots, 11-of-21 clutch threes, and 12-of-17 clutch free throws (a staggering TS% of 75.5). He also added four assists against only two turnovers in close-and-late minutes starting with the Texas game.

Clutch highlights included: eight quick points vs. Virginia Tech to turn a 52–50 deficit into a 60–56 lead, a three pointer vs. Clemson to break a 63–63 tie and help preserve Carolina’s Chapel Hill winning streak against the Tigers, five points in the final minute to beat Miami—including the game-winning three with seven seconds left, seven consecutive UNC points at NC State (two tip-dunks and a three) to turn a late four-point lead into an eight-point lead, a last-second, step-back three pointer at FSU to turn a one-point loss into a two-point victory, 17 clutch points vs. Clemson in the ACC tournament—including 14 in overtime, and five consecutive points vs. Washington in the NCAA Tournament to turn a three-point deficit into a two-point lead and a trip to the Sweet 16. Even in the Elite Eight loss to Kentucky, Barnes went down swinging by hitting a three and drawing two “and-1s” to cut the deficit from eight to two. Without question, it was one of the greatest sustained runs of clutch play in Carolina’s rich hoops history.

But right behind Barnes in terms of clutch production was Tyler Zeller. He converted an amazing 67% of his 27 field goals and 89% of his 28 free throws, a clutch TS% of 75.7. His clutch play was pivotal in the regular-season

win vs. Kentucky, and ACC tournament wins against Miami (he scored the final eight points) and Clemson (his late jump hook sent it to overtime, where Barnes took over). Combined, Barnes and Zeller accounted for 56% of UNC’s 224 clutch points. (as compared to 39% of UNC’s non-clutch points). Marshall’s clutch play was also praiseworthy. He knocked down 3-of-5 clutch threes and 74% of his clutch free throws. More importantly, he had a clutch A:TO of 2.43, and averaged 11.2 assists per 40 clutch minutes. Dexter Strickland also deserves recognition for hitting 20-of-24 clutch foul shots, good for 83%. In fact, led by Zeller and Strickland, the Tar Heels as a team shot 75% on 114 clutch chances at the charity stripe—far better than their season average of 67%.

Having two battle-tested performers like Barnes and Zeller should bode well for Carolina in its close games this season; fans should hope, though, for the sake of their fingernails, that there aren’t quite as many of them as last year.

“I don’t have a tuxedo that fits anymore because my chest and my biceps are too big.”

If all goes as planned in 2011–12, the Tar Heels will join Charlie Sheen in busting out of their tuxedoes. But there is still one unresolved issue that might preclude any tuxedo-shred-ding: three point shooting. As a team, Carolina shot just 32.8% from behind the arc last season (see Table 13 for a breakdown of three-pointers by type), trailing a mere 247 teams across the country. Two years ago, the Heels shot an identical 32.8%.

Table 12: 2010–11 Clutch Statistics (Close and Late)

Player Min. Fg-A FT-A 3Pt-A Pts. OR-DR Asst. TO St. Bl. PF PERClutch index1

Barnes 88.7 21-43 12-20 11-22 65 5-16 4 6 2 1 7 23.9 148

Zeller 81.0 18-27 25-28 0-0 61 6-17 1 3 1 3 10 30.9 143

Strickland 75.3 3-10 20-24 0-0 26 4-5 3 2 3 0 9 15.8 132

Marshall 60.8 6-15 17-23 3-5 32 1-8 17 7 4 0 5 29.1 182

Henson 54.4 6-17 1-4 0-2 13 7-6 1 4 3 3 3 8.9 45

Drew II 37.7 2-7 6-8 0-3 10 0-4 3 3 4 0 8 11.3 100

McDonald 26.7 2-6 0-0 0-0 4 0-0 1 0 0 0 3 1.5 12

Knox 23.9 3-5 4-5 0-0 10 4-3 2 1 0 0 3 21.0 202

Bullock 22.4 1-6 0-0 1-3 3 1-7 1 0 0 0 2 5.6 42

Watts 14.6 0-1 0-2 0-0 0 1-1 1 0 0 0 1 2.2 25

Team 97.1 62-137 85-114 15-35 224 37-75 34 26 17 7 51 * *

Most-used Clutch Lineups Minutes +/-

Marshall-Strickland-Barnes-Henson-Zeller 24.0 46-54

Drew-Strickland-Barnes-Watts-Zeller 11.2 24-22

Marshall-McDonald-Barnes-Henson-Zeller 8.1 20-5

Marshall-Strickland-McDonald-Barnes-Zeller 4.4 15-5

Marshall-Strickland-Barnes-Henson-Knox 4.3 9-81. Clutch Index compares a player’s per-minute efficiency in clutch minutes to his per-minute efficiency in all minutes. A Clutch Index of 110 means he is 10% more effective in close-and-late situations. A Clutch Index of 90 indicates he’s 10% less effective.

Table 13: Three-Point Shooting Statistics

Type of Three 3Pt-A 3Pt%% Total 3PtA1 Best % (10+ attempts)

Halfcourt 117-359 32.6% 61.9%Marshall (37.8%)

McDonald (37.2%)

Vs. zone 63-194 32.5% 33.5%Marshall (44.4%) Bullock (35.3%)

Perimeter pass (no screen)

51-161 31.7% 27.8%McDonald (40.4%)

Bullock (35.5%)

Drive-and-kick 48-152 31.6% 26.2%Marshall (53.3%) Barnes (28.3%)

Secondary break

37-122 30.3% 21.0%Marshall (40.0%)

McDonald (36.7%)

Primary break 36-99 36.4% 17.1%McDonald (42.3%)

Barnes (41.9%)

Inside-out 36-97 37.1% 16.7%McDonald (47.1%)

Barnes (42.3%)

Off-screen 24-69 34.8% 11.9%McDonald (44.4%)

Barnes (38.9%)

Skip pass 13-53 24.5% 9.1%McDonald (31.3%)

Barnes (26.7%)

Off-the-dribble 16-42 38.1% 7.2% Barnes (46.7%)

Dribble hand-off 2-6 33.3% 1.0% none qualified

Total 190-580 32.8% *McDonald (38.1%) Marshall (37.7%)

1. Categories are not mutually exclusive ( i.e., a three-point attempt will belong to multiple categories), thus don’t sum to 100%.

16 |

2011–12 Tar Heels

UNC doesn’t need to be as efficient as the ’09 team (38.5%, 24th in the nation) from three-point territory, but it needs to start moving in that direction. Making that task tougher is the loss of Leslie McDonald to a torn ACL. McDonald, a fearless gunner from behind the arc, led the Heels by shooting 38.1% from deep and trailed only Barnes in made and attempted trifectas. Depending on how his recovery goes, he might be back for the stretch run. But any return before mid-February sounds very unlikely at this point.

Even without McDonald’s presence, expect Carolina to improve to around the 35% mark on three pointers. The biggest factor driving this three-point resurgence will be the continued development of Harrison Barnes. He combined volume and accuracy from behind the arc last March, drilling 40% of his 7.2 attempts per game. It was both his highest 3Pt% month and his highest 3PtA Rate month of the season (44.2% of his total field goal attempts were three pointers in March). If he can keep providing this type of efficiency and quantity, it will go a long way towards curing Carolina’s perimeter ails.

Expecting a big perimeter breakout from Dexter Strickland seems far-fetched at this point. Kendall Marshall should make small strides from the perimeter as a sophomore, but won’t be counted on to carry much of the load from a volume standpoint. So who does that leave to help Barnes do the heavy lifting from deep? Sophomore Reggie Bullock, coming off a knee surgery of his own, and freshman P.J. Hairston. Both had reputations as big-time three-point assassins entering college, and neither lacks confidence or is shy about hunting his shot from range. If Barnes plus either of Bullock or Hairston break out from behind the arc, Carolina will be in fantastic shape. If all three develop into con-sistent and dangerous three-point shooters, then, to paraphrase Sheen, there won’t be a tuxedo in the country that will fit around UNC’s bulging biceps and chest.

“Resentments are the rocket fuel that lives in the tip of my saber.”

We’re not sure if this quote was uttered by Sheen or by the G.O.A.T. himself (Michael Jordan) at his Hall of Fame

induction speech. Either way, it’s a well-accepted fact that athletes are driven by criticism. Slights ranging from the real to the perceived to the flat-out imaginary have long inspired that extra hour in the gym or weight room. And, throughout the Roy Williams era at Carolina, his teams have been unjustly criticized for their defensive shortcomings. Just this preseason, Sporting News’ website released the following gem:

“Those college coaches preaching the “defense-wins championships” gospel can’t be all that pleased with Roy Williams. He has won twice with teams that were brilliant on offense and just good enough on defense. This year’s Tar Heel squad looks to be cut from that cloth.”

Never mind that the ’05 Heels ranked fifth in the nation in defensive efficiency and the ’09 Heels ranked 16th, or that last season the Heels had the sixth-ranked defense while the of-fense lagged behind in 38th. It’s understood that pace-adjusted statistics aren’t for everyone. But these types of old-fashioned sportswriters who eschew them should at least consider some factors like defensive FG%, forced turnovers, etc.—not just look at raw points allowed. In the eight seasons since Williams has been back at Carolina, his defenses have been in the top 25 every season except 2010, have an average rank of 17th, and have been among the nation’s top six three times (including last season). His offenses have ranked 19th in the country over this time period (although this is badly skewed by the last two years; from 2004–09, his average offense ranked fourth). Like most great college teams, it’s safe to say that Williams’ best teams get it done with a blend of efficient offense and lockdown defense. The myth that Carolina doesn’t guard people—prevalent in the mainstream media and on message boards alike—gets more and more illogical with each passing season.

Table 14 breaks down Carolina’s individual and team defense by season segment, dividing the campaign into four quarters. As seen, UNC’s defense—dominant over the first three-quarters of the season—wore down a little over the final nine games. Specifically, Henson and Zeller were far less effective (from a Stop % perspective) defensively over the last quarter of the season. With its fast-paced nature and emphasis on feeding the post, Williams’ system is demanding for big men, in general. Moreover, with the ever-increasing national trend of using high ball screens, Carolina posts must engage in more tiring hedge-and-recover action than ever before. Throw in the 32 minutes per game that both Zeller and Henson played in the postseason, and it’s no wonder that their defensive stats took a significant hit over the final quarter of the season.

The addition of freshman talent James Michael McAdoo to the post rotation should afford the starting big men more rest throughout the season and leave them fresher (and more effective on the defensive end) in March. Both Barnes and Bullock (pre-injury) got better defensively as the season pro-gressed. The other freshman, Marshall, improved defensively in his bench role, took a big defensive hit in the third quarter while adjusting to his role as a 35-minute-per-game starter, then improved again in the final quarter of the season after

Table 14: Defensive Breakdown (Stop %) by Season Segment

Player1st 10 games

2nd nine games

3rd nine games

4th nine games

Total

Stop %

Henson 68.8% 67.9% 68.9% 61.0% 66.4%

Zeller 68.0% 64.6% 72.3% 58.7% 65.7%

Bullock 48.1% 66.1% 66.3% DNP 60.8%

Barnes 57.4% 55.7% 63.2% 62.0% 59.5%

Marshall 61.1% 69.8% 52.8% 58.4% 58.9%

Strickland 61.4% 57.1% 54.0% 61.3% 58.5%

Knox 62.5% 65.8% 46.0% 52.0% 57.7%

Drew II 54.8% 58.1% 43.2% DNP 54.9%

McDonald 54.0% 46.2% 58.4% 50.6% 52.6%

Watts 41.9% 61.0% 59.5% 43.0% 52.3%

Team 58.0% 59.7% 58.8% 55.1% 57.9%

Team Def. Eff. 94.5 89.4 92.1 101.9 95.0

Opp. Off. Eff. 108.5 106.0 109.6 113.6 108.8

Adj. Def. Eff. 88.2 85.4 85.1 90.9 88.5

national Rank 5th 1st 1st 20th 6th

| 17

Winning!

making the adjustment. As sophomores, these three players figure to continue their defensive development. After an inconsistent regular season, Dexter Strickland, Carolina’s defensive stopper in the backcourt, was its best defender last postseason. If he can carry over that level of defensive play into 2011–12, UNC will have its best shutdown guard since Jackie Manuel graduated in 2005. This has an outstanding chance of being the best Carolina defense since Roy Williams returned—probably among the top three nationally. Whether that will be good enough to end the pervasive “Carolina doesn’t defend” misconception remains to be seen; it will be good enough to win a third championship since 2005, though (if the offense and luck dragons cooperate).

“Uncertainty is a sign of humility, and humility is just the ability or the willingness to learn.”

We here at Tip-Off are nothing if not humble. And, heeding the wisdom of poet-warrior Sheen, we’re not afraid to admit our uncertainty. In fact, we’ll humbly demonstrate it in the paragraphs that follow.

One area of uncertainty involves how the rotation will shake out in 2011–12. Marshall will certainly get the bulk of the minutes at point guard; likewise, for Barnes, Henson, and Zeller at the 3, 4, and 5. Strickland will start at the 2 and back up Marshall at the 1, with McAdoo joining Henson and Zeller in a (primarily) three-man post rotation. With the injury to McDonald, the biggest question might be: Who will back up Strickland at the 2? Bullock and Hairston are the obvious candidates; both can handle the position offensively, so it comes down to who is better suited to cover opposing shooting guards. We’re guessing that Bullock—longer, leaner, laterally quicker, and more experienced in the system—will do a better job against smaller covers than the bulkier Hairston. Bullock made tremendous defensive strides as his freshman year progressed, albeit mainly against opposing 3s. In addition to the top eight mentioned, senior Justin Watts also figures to see spot minutes—it remains to be seen whether they’ll again be at the 4 or at his more natural wing position.

We’re guessing that freshmen Desmond Hubert, Jackson Simmons, and Stilman White won’t see much action once the ACC season rolls around, although Hubert is the best bet to earn the most minutes among the trio. Table 15 summarizes Roy Williams’ rotations since 2006.

Although he’s sure to do plenty of substituting and lineup experimentation in November and December, he’ll squeeze the rotation (like always, as shown in the final column of Table 15) once March rolls around.

Another area of uncertainty is projecting just how good Carolina will be in 2011–12. Despite last year’s healthy 29–8 record, outright ACC regular-season crown, and Elite Eight appearance, it was one of the least dominant teams of the Roy Williams era. According to adjusted efficiency margin, only the 2010 Heels (+14.2) ranked below last year’s team (+23.6). All of the close wins were nice, but they easily could have ended up in the loss column with some bad bounces or pedestrian clutch performances from Barnes and Zeller. Of course, all the early-season minutes absorbed by Drew really hurt the team’s performance/efficiency, too (as previously discussed). From ’04 to ’05, Carolina made a leap of 11.4 in adjusted net efficiency, essentially returning the entire roster and adding Marvin Williams to the mix. With a full season of Kendall Marshall, plus 82% of its production returning, an efficiency jump like that seems possible—even likely—for UNC in 2011–12.

Assuming a +11.4 change in efficiency margin, this year’s Heels (+35.0) would be right in line with the ’09 Heels (+34.6) in terms of dominance. They’ll almost certainly be stronger defensively and weaker offensively than ’09, but it gets trickier after that. Depending on the progress that Henson makes offensively, whether Barnes can continue his March 2011 efficiency, and whether Zeller can take on a slightly bigger offensive load, Carolina’s offense has the potential to range from very good (#10 to #20 in the nation) to great (top 5). The defense will be a top-5 unit; if the offense can join it there, it will be a long, happy season in Chapel Hill, culminat-ing with a celebration in New Orleans. Mark us down for: 35–4 overall, 14–2 in the ACC, a loss in the ACC tournament semifinals, and cutting down the nets in the Big Easy. Because, as Charlie Sheen knows better than anyone, there’s only one outcome that will make satisfy the program (and its fans) this season: Winning. MSP

Adrian Atkinson is the editor of Maple Street Press Tar Heel Tip-Off and also contributes at Tobacco Road Blues. he lives in raleigh, NC, with his wife, Katya, and daughter, Allison. You can follow Adrian on twitter @freeportKid.

Table 15: Roy’s Rotations (2006–11)

Year# w/ 30+

MPg# w/ 25+

MPg# w/ 10+

MPg# w/ 5+

MPg# of

Lineups%Min. Top1 %Min. Top 3 %Min. Top 5 %Min. Top 10

%Min Compression

Top 3—Tnmt. Factor2

2006 2 3 9 9 77 20.1 43.0 54.6 65.7 60.3 40.2%

2007 0 3 10 12 239 18.3 27.6 34.7 43.5 46.7 69.2%

2008 2 3 8 9 171 18.1 31.1 39.0 55.1 52.2 67.9%

2009 2 4 8 10 143 23.0 36.5 43.2 55.0 52.4 43.6%

2010 1 4 11 11 264 12.3 24.1 28.2 35.3 49.5 105.4%

2011 0 4 9 10 133 21.6 39.0 47.1 58.0 64.8 66.2%

Average 1.2 3.5 9.2 10.2 171.2 18.9 33.6 41.1 52.1 54.3 62.0%1. This is the percentage of total minutes played by UNC’s most-used line-up in a given season.2. Compression Factor measures how much the rotation is compressed in Tournament play. It represents the percentage increase in minutes that the three most-used line-ups play in ACC/NCAA Tournament games.

Maple street Press | 18

R egardless of one’s opinions on the validity of prep rank-ings and how well the scouts assess talent, most college

hoops fans agree that there is at least some correlation between a player’s high school ranking and his collegiate production. In the eight seasons since Roy Williams has been back in Chapel Hill, this correlation has been especially strong.

Table 1 breaks down Williams’ players (some of whom were recruited by his predecessor, Matt Doherty) as a func-tion of high school (RSCI) recruiting rank. James Michael McAdoo will be the 12th top 10 Tar Heel to take the court for Williams, the most of any recruiting tier. Just by eyeballing this table, a fairly obvious trend emerges: the more-heralded recruits have had significantly more productive collegiate careers than the less-acclaimed ones. Table 2 examines this trend empirically.

Williams has had 23 player-seasons from top 10 recruits during his Carolina tenure—eight from freshmen, eight from sophomores, six from juniors, and one from a senior. The first row of Table 2 shows the average output across those 23 player-seasons. For the sake of comparison, the statistics for an average top 10 recruit from the ACC (over the years 1984-2011) are provided directly under the row for Williams’ top 10 players. To compare apples to apples, the ACC numbers are calculated using a weighted average that mirrors the class distribution of player-seasons for the Williams group (i.e., eight freshmen, eight sophomores, …). As seen in Table 2, recruits ranked in the top 10 and 11-20 tiers are significantly more productive on a per-minute basis than their ACC counterparts in those tiers. Williams’ top 20 recruits also use 5% more possessions than their highly-ranked ACC peers. They make an all-ACC team in 55% of their cumulative player-seasons, and 80% of Roy’s top 20 recruits make at least one all-conference team in

their career. Average top 20 recruits (with a distribution like Williams’) are expected to make an all-ACC team in 42% of their cumulative player-seasons, with 64% earning that honor at some point in their ACC career. Even when compared to other highly-ranked recruits, Roy Williams’ stars truly perform like stars.

It’s a different story, though, for the average Williams recruit ranked outside of the top 20. These players used about 12% fewer possessions than their ACC peer group, and also used them less productively and efficiently. This isn’t neces-sarily surprising: a top 40 prep is generally recruited as a role player at Carolina, whereas he’ll often have a starring role at another ACC school (and the numbers/opportunities that ac-company that role). The data in Table 2 can help fans set more reasonable expectations for incoming recruits. It also helps demonstrate that Roy Williams does a fantastic job of blending 5-star talent and complementary pieces to build teams.

As long as his top-tier talent continues to play like su-perstars, and his other recruits accept their reduced offensive roles, Williams will keep winning big in Chapel Hill. MSP

Know Your roleby Adrian Atkinson

The impact of high school talent in the roy williams era

Table 1: UnC Players by Recruiting Rank in the Roy Williams EraTier # of Players Players (RSCi Rank)

Top 10 12Barnes (1), Felton (3), Wright (3), McCants (4), Hansbrough (4), Lawson (5), Henson (5), McAdoo (6), M. Williams (7), Ellington (8), May (9), Davis (9)

11-20 5J. Williams (11), Hairston (11), Green (15), Bullock (15), Zeller (18)

21-30 4 Strickland (24), Manuel (25), Marshall (25), Ginyard (29)

31-40 5Frasor (31), Scott (37), D. Wear (37), T. Wear (38), Stepheson (39)

41-80 6Thompson (43), Drew II (44), McDonald (44), Thomas (55), Terry (60), Graves (79)

Unranked 9Noel, Sanders, Miller, Copeland, Watts, Knox, Hubert, White, Simmons

Table 2: A Roy Williams-Coached Carolina Player vs. an Average ACC Player as a Function of Recruiting Rank

Tier MPg Pts/40 TS% PERWORP/35

Usage Rate

%All-ACC(Seasons)1

%All-ACC(Players)2

Top 10: Roy 27.7 19.7 58.4 21.9 3.03 21.0 65.2 81.8

Top 10: ACC 28.0 17.1 57.9 18.2 2.52 19.9 48.7 69.0

11-20: Roy 19.7 18.2 55.9 18.5 1.61 19.5 30.0 75.0

11-20: ACC 25.2 15.6 56.9 16.1 1.71 18.5 26.3 50.0

21-30: Roy 22.9 10.6 52.0 12.7 0.62 14.5 11.1 25.0

21-30: ACC 23.7 15.1 55.7 15.4 1.59 18.4 23.0 40.7

31-40: Roy 16.0 10.2 49.7 10.8 0.28 13.9 0.0 0.0

31-40: ACC 22.4 13.5 54.8 12.9 0.97 17.2 10.3 18.4

41-80: Roy 15.4 13.0 51.4 13.5 0.64 17.7 5.0 16.7

41-80: ACC 21.6 13.8 54.9 13.9 1.15 17.6 13.6 25.6

Unranked: Roy 10.2 10.9 50.6 11.2 0.21 14.6 5.9 16.7

Unranked: ACC 21.4 13.1 55.2 13.1 1.04 16.6 8.2 14.01. Represents the percentage of player-seasons for which a player makes an all-ACC team (e.g., a player making one all-ACC team in three collegiate seasons has a 33.3 in this metric).2. Represents the percentage of players who make an all-ACC team at least once in their careers (e.g., a player making one all-ACC team in three collegiate seasons has a 100.0 in this metric).

Maple street Press | 19

In the section that follows, each of Carolina’s eight return-ing rotation players are highlighted with a four-page scouting report and statistical profile. After a one page

scouting report, pages two, three, and four of each profile provide detailed statistical tables on the player. Page two in-cludes projected statistics for 2011–12. These projections are estimated using a two-step process: 1) assume an allocation of minutes for the 2011–12 team and an allocation of possession usage; 2) use average ACC player development curves (by position and class) and comparable/statistically similar player development curves to build a forecasting model that projects per-minute averages for each category.

On page three are statistical splits for each player (by month, location, strength of opponent, etc.), as well as defen-sive box score statistics and shot creation data. The defensive box score stats are described in the statistical glossary on page 18. Page three also includes +/- data for each player. These statistics are analogous to hockey’s +/-, which tracks the score during a player’s minutes on the court. In this case, the raw +/- is converted to +/- efficiencies by using the number of possessions that a player in on the floor. Each player’s on-court numbers for the offensive and defensive Four Factors are also shown in the +/- tables. This allows us to determine if the team was better or worse (offensively, defensively, overall) with a certain player on the court, and why the team was better or worse during those minutes

Page four of each profile includes a table and graphic on shot distribution, and tables on turnover distribution and passing statistics. A description of the passing statistics can be found in the statistical glossary.

Adrian Atkinson is the editor of Maple Street Press Tar Heel Tip-Off and also contributes at Tobacco Road Blues. he lives in raleigh, NC, with his wife, Katya, and daughter, Allison. You can follow Adrian on twitter @freeportKid.

by Adrian Atkinson

2011–12 unC Player Profiles

BY The numBers

20 |

2011–12 Tar Heels

6'8" • 215 • Ames, IA • Sophomore 2010–11 Minutes: SF: 93.1% PF: 6.2% Sg: 0.7%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSAs his shot chart shows, Barnes was a threat to score from all over the court. The trick this season will be learning to score efficiently from all over the court. As a freshman, Barnes made 67 three-pointers (for 34.7% of his total points), 76 lay-ups/dunks (26.2%), 49 midrange jumpers (16.9%), 93 free throws (16.0%), and 18 shots from 5–10 feet, generally floaters (6.2%). He was a much better three-point shooter from the left side of the court (29-70, 41.4%) than the right side (31-105, 29.5%), and a much better three-point shooter off the dribble (14-30, 46.7%) than off of a catch-and-shoot (53-165, 32.1%). Used to having the ball in his hands and creating off the dribble in high school, Barnes became better and better at playing without the ball as the season progressed. As his catch-and-shoot skills, off-ball movement, and spacing continue to improve, he should become a more efficient and dangerous scorer as a sophomore. He tied for the team lead (with Zeller) with 20 “and-one” opportunities, converting 15 of them.

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSBarnes’s scoring average increased each month, including huge spikes in February and March (11.3 PPG in November, 13.0 in December, 13.3 in January, 17.0 in February, 21.6 in March). Some of that was the Kendall Marshall effect, but much was just Barnes learning how to score at the collegiate level and within the Carolina system. A big-game player, Barnes was at his best as a scorer against the top 25 (17.5 PPG, TS% of 56.6% in 11 games). He made just 6-of-32 three-pointers (18.8%) while averaging 11.9 points in the Heels’ eight losses. He can make tough shots, but he probably settled for too many of them as a freshman—43% of his attempts were contested as compared to 36% of UNC’s team total. A primary option will always have to take some difficult shots, but Barnes’s (and the team’s) offensive efficiency would be helped if he turned down some of the contested, off-the-dribble two-point jumpers. Better shot selection and understanding of how to score within the offense should lead to an All-American sophomore campaign for The Black Falcon. His 0.78 ball-handling turnovers per 40 minutes (and raw total of 21) led the team, prompting Barnes to dedicate offseason hours to tightening up his handle. From a +/- perspective, Barnes’s on-court/off-court differential (+7.4) trailed only Zeller’s (+14.6) and Marshall’s (+13.4) in 2010–11; that is, Carolina was 7.4 points better per 100 possessions with Barnes on the court than with him resting on the bench.

DEFENSIVE BOX SCORE OBSERVATIONSBarnes made terrific defensive progress over the course of the season. After a Stop% of 56.6% over the first 19 games, he raised that mark to 62.6% during the final 18 contests. Most notably, Barnes turned in a couple of lockdown performances against Duke’s Kyle Singler. As a sophomore, his Stop% should increase even more. One defensive area of concern for Barnes was defending the three-point arc. Like most freshmen in the Carolina system, he struggled with the timing of his help-and-recover close-outs. He also allowed himself to be screened too easily for much of the year. In several cases, Barnes was in perfect defensive position with the exception of having his hand down—something that quick-triggered college marksmen will take advantage of. The good news is that Barnes’s perimeter defense improved dramatically over the season’s final quarter. After allowing 1.6 three-pointers per 40 minutes, on 41.3% shooting, over the first 28 games, he allowed just 1.1 per 40 minutes, on 29.8% shooting, over the final nine contests.

Harrison Barnes #40

| 21

2011–12 Tar Heels

2010–11 gAME-BY-gAME STATiSTiCS

Harrison Barnes #40

Field goals 3-Point Fg Free Throws ReboundsDATE OPP RESULT Min Fg FgA 3PM 3PA FTM FTA PTS OFF DEF TOT AST STL BLK TO PF11/12 Lipscomb W 27 6 12 0 3 2 2 14 2 2 4 2 0 1 0 411/18 Hofstra (N) W 25 7 11 4 5 1 1 19 3 4 7 2 0 1 2 211/19 Minnesota (N) L 27 0 12 0 3 6 8 6 4 3 7 2 1 0 1 311/21 Vanderbilt (N) L 29 4 12 0 3 3 4 11 2 2 4 2 2 1 1 311/23 North Carolina-Asheville W 33 5 12 3 3 0 0 13 2 5 7 2 0 0 4 211/28 College of Charleston W 29 3 12 0 4 2 3 8 3 6 9 3 1 1 4 411/30 @ Illinois L 27 2 9 1 4 3 3 8 2 3 5 1 0 0 0 212/4 Kentucky W 25 4 10 1 3 3 4 12 1 3 4 1 1 0 3 212/8 @ Evansville W 32 3 11 0 5 3 4 9 1 6 7 2 1 0 2 112/11 Long Beach State W 29 7 16 3 8 2 5 19 3 7 10 2 1 0 0 012/18 Texas L 31 5 10 1 4 5 5 16 1 2 3 2 0 0 3 212/21 William & Mary W 26 5 12 1 4 2 5 13 1 4 5 1 2 1 2 212/28 @ Rutgers W 22 3 9 2 5 1 2 9 0 3 3 1 2 0 2 2

1/2 Saint Francis (PA) W 22 4 8 2 3 0 0 10 0 4 4 2 0 0 2 11/8 @ Virginia W 26 4 9 0 1 1 2 9 0 3 3 0 0 2 1 01/13 Virginia Tech W 29 5 11 2 5 0 1 12 1 4 5 1 0 0 6 11/16 @ Georgia Tech L 23 3 13 0 2 5 5 11 2 1 3 0 0 0 2 21/18 Clemson W 30 4 9 1 3 4 7 13 2 4 6 1 0 0 6 21/26 @ Miami (FL) W 24 4 11 2 5 3 3 13 1 2 3 0 2 0 2 01/29 North Carolina State W 26 10 16 3 7 2 3 25 3 3 6 1 1 0 1 12/1 @ Boston College W 26 9 15 4 7 4 4 26 3 3 6 1 0 0 1 12/6 Florida State W 29 7 15 2 6 1 2 17 3 7 10 1 0 1 0 22/9 @ Duke L 30 3 8 1 3 2 3 9 1 5 6 2 0 2 1 32/12 @ Clemson W 28 7 13 1 5 5 8 20 0 5 5 1 0 0 2 32/15 Wake Forest W 28 7 20 1 8 2 2 17 1 3 4 4 1 1 0 12/19 Boston College W 35 4 14 1 4 1 2 10 4 5 9 0 1 1 2 22/23 @ North Carolina State W 30 6 17 2 7 2 2 16 3 5 8 0 0 0 1 12/27 Maryland W 27 9 23 3 10 0 0 21 5 1 6 2 1 0 2 43/2 @ Florida State W 34 6 10 2 4 4 4 18 1 3 4 1 1 1 3 13/5 Duke W 31 7 17 2 6 2 2 18 2 3 5 2 2 0 1 33/11 Miami (FL) (N) W 34 7 13 4 10 0 0 18 2 3 5 2 0 0 1 13/12 Clemson (N) W 41 12 17 6 8 10 11 40 4 4 8 1 0 0 3 23/13 Duke (N) L 37 6 15 1 4 3 4 16 1 1 2 0 0 0 0 13/18 Long Island University (N) W 35 9 19 2 10 4 6 24 3 13 16 3 2 0 4 23/20 Washington (N) W 36 9 19 4 7 0 0 22 0 2 2 2 3 0 3 23/25 Marquette (N) W 30 7 18 3 7 3 4 20 7 2 9 1 1 2 0 43/27 Kentucky (N) L 34 7 19 2 9 2 3 18 1 5 6 2 1 1 4 3

Totals 37 games 1087 210 497 67 195 93 124 580 75 141 216 53 27 16 72 72Averages 29.4 5.7 13.4 1.8 5.3 2.5 3.4 15.7 2.0 3.8 5.8 1.4 0.7 0.4 1.9 1.9

Year MPg PPg RPg APg SPg BPg TOPg A:TO Fg% FT% 3Pt% PERWORP / 35

FR 29.4 15.7 5.8 1.4 0.7 0.4 1.9 0.74 42.3 75.0 34.4 16.2 1.40

Projected SO 29.0 18.1 6.2 1.9 1.0 0.5 1.8 1.08 46.7 81.5 37.5 22.9 2.66

CAREER STATS BY YEAR

ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40

Off. Fouls / 40 DR% Stop%

Def. On-C/Off-C

FR 40.5 38.2 51.8 2.37 4.27 0.30 12.6 59.5 +1.5

DEFENSIVE BOX SCORE STATS BY YEAR

MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Kyle Singler (2010–11, SR, Duke)

MOST STATISTICALLY SIMILAR ACC SEASON (FRESHMEN)Courtney Alexander (1995–96, Virginia)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Joe Forte (1999–00, FR)

CAREER STATiSTiCS

22 |

2011–12 Tar Heels

g MPg PPg RPg APg SPg BPg TOPg PFPg A:TO Fg% FT% 3Pt% eFg% TS%FTA Rate

Usage Rate1 OR% DR% PER

WORP / 352

All games 37 29.4 15.7 5.8 1.4 0.7 0.4 1.9 1.9 0.74 42.3 75.0 34.4 49.0 52.2 25.0 22.5 7.3 12.8 16.2 1.40/ 40 Min.1 – 40.0 19.9 7.4 1.8 0.9 0.5 2.4 2.4 0.74 42.3 75.0 34.4 49.0 52.2 25.0 22.5 7.3 12.8 16.2 1.78nov. 7 28.1 11.3 6.1 2.0 0.6 0.6 1.7 2.9 1.17 33.8 81.0 32.0 38.8 43.9 26.3 20.6 9.6 12.5 13.0 0.67Dec. 6 27.5 13.0 5.3 1.5 1.2 0.2 2.0 1.5 0.75 39.7 64.0 27.6 45.6 48.8 36.8 21.8 4.5 14.9 14.3 0.93Jan. 7 25.7 13.3 4.3 0.7 0.4 0.3 2.9 1.0 0.25 44.2 71.4 38.5 50.7 53.5 27.3 22.7 5.3 11.5 12.0 0.43Feb. 8 29.1 17.0 6.8 1.4 0.4 0.6 1.1 2.1 1.22 41.6 73.9 30.0 47.6 50.0 18.4 24.1 9.0 14.4 17.9 1.78Mar./Apr. 9 34.7 21.6 6.3 1.6 1.1 0.4 2.1 2.1 0.74 47.6 82.4 40.0 56.5 59.5 23.1 22.6 7.1 11.4 20.2 2.72ACC 19 29.9 17.3 5.5 1.1 0.5 0.4 1.8 1.6 0.57 45.1 78.5 36.2 52.3 55.4 24.4 22.5 7.2 11.3 17.0 1.64non-Conf 18 28.8 13.9 6.2 1.8 1.0 0.4 2.1 2.3 0.89 39.0 71.2 32.2 45.2 48.5 25.5 22.5 7.3 14.4 15.2 1.16Regular 30 28.0 14.1 5.6 1.4 0.7 0.4 1.9 1.9 0.74 40.6 74.0 32.1 46.6 49.9 25.5 22.2 7.1 13.0 14.8 1.06Post 7 35.3 22.6 6.9 1.6 1.0 0.4 2.1 2.1 0.73 47.5 78.6 40.0 56.7 59.3 23.3 23.2 7.7 12.0 20.6 2.88vs. Top 25 11 31.8 17.5 4.7 1.4 0.6 0.3 2.4 2.3 0.58 45.2 78.0 37.5 52.4 56.6 34.3 21.7 4.5 10.4 15.7 1.41vs. 26–50 6 29.7 16.5 6.3 1.3 0.8 0.8 2.0 2.5 0.67 42.7 73.3 34.3 49.4 51.5 16.9 23.5 11.2 10.5 17.2 1.65vs. 51–100 12 27.6 14.2 6.0 1.0 0.8 0.3 1.5 1.4 0.67 38.2 74.4 33.3 44.9 48.4 24.8 22.5 8.9 13.1 15.3 1.13vs. 100+ 8 28.5 14.9 6.8 2.3 0.8 0.7 2.0 1.9 1.13 43.8 70.0 31.7 50.0 52.0 19.1 22.8 6.0 17.7 17.3 1.62Home 16 28.6 14.9 6.1 1.7 0.7 0.4 2.3 2.1 0.75 42.4 65.1 32.1 48.4 50.1 19.8 23.4 7.8 13.6 15.0 1.12Road 11 27.5 13.5 4.8 0.8 0.5 0.5 1.5 1.5 0.53 40.0 82.5 31.3 46.0 51.4 32.0 20.5 4.9 12.7 14.2 0.91neutral 10 32.8 19.4 6.6 1.7 1.0 0.5 1.9 2.3 0.89 43.9 78.1 39.4 52.3 55.6 26.5 23.0 8.7 11.7 19.5 2.40Wins 29 29.3 16.7 6.2 1.4 0.8 0.4 2.1 1.8 0.70 45.1 71.9 37.4 52.8 55.0 22.3 23.0 7.6 13.8 17.8 1.76Losses 8 29.8 11.9 4.5 1.4 0.5 0.5 1.5 2.4 0.92 30.6 82.9 18.8 33.7 41.4 35.7 20.7 6.2 9.2 10.4 0.12

BE YOnD THE BOX SCORE STATiSTiCS

2010–11 BOX SCORE STATiSTiCS

DEFENSIVE BOX SCORE STATISTICS

Min. Fg-A 3Pt-A FT-A Fg % eFg % TS % Pts. All. TOFOff.

Fouls Defl. DR % St. % Bl. % Stop %Def.Rat.

Def. Rat.+1

On-Court Def. Eff.

All: Total 1078 99-244.5 39.5-103.5 54-78 40.5 48.6 51.8 291.5 64 8 115 12.8 1.4 1.4 59.5 94.4 100.6 94.6

Per 40 40.0 3.7-9.1 1.5-3.8 2.0-2.9 40.5 48.6 51.8 10.8 2.4 0.30 4.3 12.8 1.4 1.4 59.5 94.4 100.6 94.6

ACC: Total 568 46.5-126 17-48.5 17-29 36.9 43.7 45.4 127 29.5 5 52 11.3 0.9 1.4 62.3 95.2 101.7 97.2

Per 40 40.0 3.3-8.9 1.2-3.4 1.2-2.0 36.9 43.7 45.4 8.9 2.1 0.35 3.7 11.3 0.9 1.4 62.3 95.2 101.7 97.2

SHOT CREATION

Assisted by: Unasst. Marshall Strickland Drew ii Zeller Henson McDonald Bullock Knox Watts Others Total

# of Fg 111 46 25 12 6 5 3 2 0 0 0 210

% of Total Fg 52.9 21.9 11.9 5.7 2.9 2.4 1.4 1.0 0.0 0.0 0.0 100.0

+/– STATISTICS

Min. Pace net Eff. Off. Eff.Offensive 4 Factors

Def. Eff.Defensive 4 Factors

All Minutes eFg % FTA Rate OR % TO % eFg % FTA Rate DR % TOF %

On-Court 1078.0 72.4 +13.5 108.1 49.9 38.8 38.4 18.6 94.6 45.3 24.7 70.0 18.7

Off-Court 407.0 72.4 +6.1 102.2 47.1 35.4 33.9 17.6 96.1 48.6 25.1 69.6 22.4

Difference1 – 0.0 +7.4 +5.9 +2.8 +3.4 +4.5 -1.0 +1.5 +3.3 +0.4 +0.4 -3.7

As 3 (SF) 1003.5 72.3 +13.2 107.0 49.8 38.0 38.1 18.7 93.8 44.8 23.0 69.8 18.6

As 4 (PF) 67.0 73.8 +14.8 122.9 51.8 50.9 41.1 15.3 108.1 55.4 47.8 72.4 20.3

As 2 (Sg) 19.0 61.6 -15.8 84.2 33.3 54.2 50.0 24.6 100.0 38.7 25.8 54.5 13.3

1. A positive (negative) difference means that the team is better (worse) in an area during the minutes that the player is on the court. In some cases (e.g., offensive efficiency, OR%), this is reflected in a higher on-court number. In other cases (e.g., defensive efficiency, TO%), this is reflected in a lower on-court number.

1. Per-game stats in the “/ 40 minutes” row are pace-adjusted to reflect an average-paced ACC game for 2010–11 (67.9 possessions / 40 minutes). Per-game stats in all other rows are pace-dependent (based on UNC’s 2010–11 pace of 72.8 possessions / 40).2. WORP / 35 (wins over replacement player per 35 games) measures the number of marginal wins that a player contributes as compared to a “replacement level” ACC player at his position.

1. Defensive Rating+ is an index of a player’s Defensive Rating compared to UNC’s average team defensive efficiency where 102 is 2% better than average and 98 is 2% worse than average.

Harrison Barnes #40

| 23

2011–12 Tar Heels

TURNOVER STATISTICS

Type # of TOs TOs / 40 TO Rate (%)

Bad pass 30 1.11 6.0

Ball-handling 21 0.78 4.2

Bad catch 8 0.30 1.6

Offensive foul 7 0.26 1.4

Traveling 6 0.22 1.2

Live-ball TO 44 1.63 8.8

Dead-ball TO 28 1.04 5.6

Total 72 2.67 14.4

SHOOTING BY LEVEL OF CONTESTEDNESS

Type 2-Pt Fg2-Pt Fg% 3-Pt Fg

3-Pt Fg% FgA / 40 eFg%

Open 26-34 76.5 5-20 25.0 2.0 62.0

Lightly Contested 69-99 69.7 56-130 43.1 8.4 66.8

Contested 48-145 33.1 6-43 14.0 6.9 30.3

Heavily Contested 0-24 0.0 0-2 0.0 1.0 0.0

Total 143-302 47.4 67-195 34.4 18.3 49.0

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40

“Hockey” Asst. / 40

Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

1.22 0.45 0.18 0.41 0.30 2.26 1.41 1.11 9.6 18.3 19.8 0.93

Pot. Close / 40 (PCA)

Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40

Pot. Asst. / 40 Asst. % PCA:PTO

Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

1.74 1.30 0.78 1.15 6.09 37.2 1.57 5.45 42.2 40.1 17.7

TOTAL SHOOTING BY AREA

Area Fg-FgA FgA / 40 %Shots eFg%

Total Close 76-121 4.5 7.1 62.8

Total non-Close Paint 26-75 2.8 4.4 34.7

Total Mid-Range 41-106 3.9 6.2 38.7

Total 3-Pt. 67-195 7.2 11.5 51.5

Total 0'-10' 94-173 6.4 10.2 54.3

Total 10'-20' 49-129 4.7 7.6 38.0

Total Paint 102-196 7.2 11.6 52.0

Total non-Paint 108-301 11.1 17.7 47.0

Total non-Close 134-376 13.8 22.2 44.6

ALL FgA 210-497 18.3 29.3 49.0

PERCENTAGES AND SHOTS BY AREA

28.4%19-67

35.0%7-20

35.3%6-17

66.7%6-9

50.0%4-8

42.9%3-7

42.9%3-7

31.3%5-16

36.0%9-25

26.7%4-15

30.8%4-13

41.7%5-12

31.6%12-38

50.0%12-24

41.4%12-29

26.1%6-23

66.7%30-45

73.1%19-26

54.0%27-50

37.0%17-46

Harrison Barnes #40

24 |

2011–12 Tar Heels

7'0" • 250 • Washington, IN • Senior 2010–11 Minutes: C: 100.0%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSZeller’s go-to move in the post is undeniably the jump hook. He used the shot 141 times last season (37% of his total field-goal attempts), connecting on 58, or 41.1%. Over his first two campaigns, Zeller converted 38.8% of his hooks and attempted them on 35% of his shots. If he can inch that hook percentage into the mid-40s as a senior, he’ll become an even more efficient and reliable primary post option. Zeller also shot less frequently and more accurately from midrange. In his first two seasons, he attempted 22% of his shots from 10–19 feet, connecting on 32.7% of them. As a junior, Zeller attempted just 14% of his shots from this distance while making 39.6%. Much of this improvement was simply due to establishing consistently deeper post position, and therefore having to settle for fewer hook shots of the 12-foot variety. He was also a more consistent midrange jump shooter, particularly when trailing in the secondary break (and also from the short corner against opposing zones, albeit in limited opportunities). Most importantly, however, Zeller continued to be an efficient (and underrated) finisher around the basket. Although he doesn’t rattle the rim as much as many Heels fans would like, his quick release and ability to finish with either hand (51-71, or 71.8%, with the left hand in 2010–11) pay big dividends around the hoop. After making 68.6% of close field goals in his first two seasons, Zeller improved to 71.8% as a junior. His rate of close attempts also increased: from 45% of all shots as a freshman and sophomore to 49% as a junior. Kendall Marshall can be partially credited for both of these increases—his ability to complete hit-ahead passes and create in the halfcourt shouldn’t be overlooked. But Zeller also deserves some credit for adding strength and finishing through contact better (although he’ll never be confused with that other Tyler who recently donned Carolina blue).

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSIn seven postseason contests, Zeller averaged 20.6 points with a TS% of 63.0%. If that continues through 2012, you’re looking at a first-team All-American. Both his assist rate and assist-to-turnover ratio skyrocketed in the postseason, too. Passing will never be his forte, but the more he can make opponents pay for doubling the post, the more dangerous Carolina’s offense will be. From a +/- perspective, Zeller was the Heels’ most irreplaceable offensive player (+12.4), and only Henson (defensive on-court/off-court of +2.9) was a more valuable defender than Zeller (+2.3). At his best against the best opponents, Zeller’s WORP/35 was higher against top 50 teams (3.03) than it was against those ranked 51 or worse (2.53).

DEFENSIVE BOX SCORE OBSERVATIONSJust a mediocre defensive rebounder, Zeller’s DR% was especially poor in ACC contests. While he often does the dirty work (consistently boxing out the opponent’s top offensive rebounder) that allows Henson to clean the defensive glass, Zeller’s progression in this area could help Carolina’s defense become truly elite. For the second consecutive year, he led the Heels in charges drawn (29) and charges drawn per 40 minutes (1.11). His Stop% of 65.7% trailed only Henson’s 66.4%—this interior duo clearly spearheaded UNC’s stellar defense last season (ranked sixth in the nation in adjusted defensive efficiency). While opponents managed to make just 28.7% of their attempts against Henson (many of which were blocked or altered), Zeller limited them to a still-excellent 31.9% mark with his more blue-collar brand of positional post defense.

Tyler Zeller #44

| 25

2011–12 Tar Heels

2010–11 gAME-BY-gAME STATiSTiCS

Tyler Zeller #44

Field goals 3-Point Fg Free Throws ReboundsDATE OPP RESULT Min Fg FgA 3PM 3PA FTM FTA PTS OFF DEF TOT AST STL BLK TO PF11/12 Lipscomb W 25 4 10 0 0 7 10 15 4 3 7 0 2 1 2 311/18 Hofstra (N) W 25 4 7 0 0 3 5 11 1 7 8 1 1 1 0 211/19 Minnesota (N) L 27 7 14 0 0 2 3 16 2 3 5 0 0 1 0 411/21 Vanderbilt (N) L 33 7 13 0 0 6 6 20 3 7 10 1 0 2 1 411/23 North Carolina-Asheville W 32 8 11 0 0 7 9 23 4 3 7 2 1 2 3 211/28 College of Charleston W 30 4 12 0 0 0 0 8 2 8 10 0 0 1 2 111/30 @ Illinois L 20 5 9 0 0 0 3 10 1 3 4 1 2 0 1 312/4 Kentucky W 30 8 13 0 0 11 12 27 3 8 11 0 0 5 0 412/8 @ Evansville W 26 5 9 0 0 8 10 18 2 6 8 2 1 2 1 312/11 Long Beach State W 30 3 10 0 0 4 5 10 0 7 7 2 1 0 1 212/18 Texas L 24 6 12 0 0 2 4 14 2 5 7 1 1 1 2 412/21 William & Mary W 24 4 9 0 0 6 7 14 5 4 9 0 3 0 1 112/28 @ Rutgers W 24 3 8 0 0 2 2 8 2 8 10 0 0 1 3 4




FR 7.8 3.1 2.0 0.2 0.2 0.2 0.5 0.38 47.2 76.5 – 14.8 0.41

SO 17.4 9.3 4.6 0.3 0.5 0.9 1.3 0.21 52.1 72.2 0.0 19.2 1.52

JR 28.1 15.7 7.2 0.6 0.7 1.2 1.4 0.46 54.7 76.3 – 21.7 2.76

Projected SR 27.0 15.8 7.1 0.7 0.7 1.4 1.3 0.54 56.0 77.8 – 22.8 2.80


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 44.0 57.1 54.4 3.39 3.05 1.02 17.8 55.4 +1.0

SO 36.1 29.8 43.1 3.54 3.80 1.43 15.1 62.0 +4.5

JR 31.9 32.7 38.1 3.46 3.29 1.11 15.2 65.7 +2.3


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Alaa Abdelnaby (1989–90, SR, Duke)

MOST STATISTICALLY SIMILAR ACC SEASON (jUNIORS)Ben Coleman (1982–83, Maryland)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Brandan Wright (2006–07, FR)

CAREER STATiSTiCS

26 |

2011–12 Tar Heels



WORP / 352

All games 37 28.1 15.7 7.2 0.6 0.7 1.2 1.4 2.7 0.46 54.7 76.3 – 54.7 60.0 55.0 19.6 10.8 15.2 21.7 2.76/ 40 Min.1 – 40.0 20.8 9.6 0.8 0.9 1.6 1.9 3.6 0.46 54.7 76.3 – 54.7 60.0 55.0 19.6 10.8 15.2 21.7 3.66nov. 7 27.4 14.7 7.3 0.7 0.9 1.1 1.3 2.7 0.56 51.3 69.4 – 51.3 55.3 47.4 20.3 9.3 17.5 20.1 2.35Dec. 6 26.3 15.2 8.7 0.8 1.0 1.5 1.3 3.0 0.63 47.5 82.5 – 47.5 56.9 65.6 21.4 9.3 23.7 24.0 3.06Jan. 7 26.1 11.7 5.6 0.1 0.3 1.3 1.4 2.4 0.10 50.9 76.5 – 50.9 57.6 61.8 16.7 10.9 10.8 16.3 1.49Feb. 8 28.3 17.3 7.9 0.3 1.0 0.8 1.0 2.9 0.25 61.9 77.3 – 61.9 65.8 52.4 18.8 15.3 13.1 24.8 3.45Mar. 9 31.3 18.6 7.0 1.1 0.6 1.4 1.7 2.6 0.67 57.4 75.4 – 57.4 61.8 52.8 20.5 8.9 13.6 22.4 3.24ACC 19 28.5 14.4 6.5 0.4 0.5 0.9 1.3 2.7 0.28 56.9 74.4 – 56.9 61.0 49.7 17.4 11.1 12.2 18.6 2.14non-Conf 18 27.8 17.1 8.0 0.9 1.0 1.5 1.4 2.7 0.64 52.7 77.7 – 52.7 59.1 59.6 21.9 10.5 18.5 24.9 3.41Regular 30 27.2 14.6 7.1 0.4 0.7 1.1 1.3 2.7 0.33 54.1 74.4 – 54.1 59.1 54.4 19.0 10.8 15.7 20.5 2.42Post 7 32.0 20.6 7.7 1.4 0.7 1.6 1.4 2.6 1.00 56.7 82.4 – 56.7 63.0 56.7 21.5 10.8 13.6 26.0 4.19vs. Top 25 11 30.2 16.5 7.1 0.5 0.5 1.7 1.5 2.6 0.31 57.9 72.4 – 57.9 61.3 47.9 18.8 8.9 14.8 20.7 2.74vs. 26–50 6 28.8 18.8 7.5 1.0 0.7 1.0 1.2 3.0 0.86 57.3 75.0 – 57.3 61.4 48.0 22.0 12.1 14.2 25.0 3.55vs. 51–100 12 26.9 12.0 6.8 0.5 0.6 0.8 1.2 3.0 0.43 47.3 84.4 – 47.3 54.0 40.2 17.4 10.1 15.6 16.1 1.51vs. 100+ 8 26.6 17.8 7.9 0.8 1.3 1.4 1.6 2.1 0.46 57.9 75.0 – 57.9 64.4 94.7 22.1 13.8 16.2 28.8 4.06Home 16 27.6 15.8 7.4 0.4 0.8 1.2 1.4 2.3 0.26 55.4 73.9 – 55.4 60.1 55.4 19.9 10.9 16.1 21.7 2.72Road 11 26.4 12.5 6.6 0.5 0.8 1.0 1.5 3.2 0.31 52.1 74.1 – 52.1 57.7 57.5 17.8 11.6 13.9 18.3 1.91neutral 10 30.9 19.1 7.7 1.2 0.6 1.5 1.1 2.8 1.09 55.7 81.5 – 55.7 61.7 52.4 20.8 9.9 15.3 24.7 3.75Wins 29 28.2 15.6 7.3 0.7 0.8 1.1 1.2 2.7 0.53 54.3 77.6 – 54.3 60.3 59.4 19.2 10.9 15.4 22.1 2.86Losses 8 28.0 16.0 6.9 0.5 0.4 1.5 1.8 2.9 0.29 56.0 70.3 – 56.0 59.0 40.7 20.8 10.3 14.5 19.9 2.38






Def. Rat.+1

On-Court Def. Eff.

All: Total 1046 103-322.5 17-52 59-101 31.9 34.6 38.1 282 90.5 29 86 15.2 1.4 4.2 65.7 91.4 103.9 94.3

Per 40 40.0 3.9-12.3 0.7-2.0 2.3-3.9 31.9 34.6 38.1 10.8 3.5 1.11 3.3 15.2 1.4 4.2 65.7 91.4 103.9 94.3

ACC: Total 538 50.5-163.5 9.5-29.5 25-49 30.9 33.8 36.3 135.5 35.5 12 37 12.2 1.0 3.4 64.4 93.8 103.2 97.0

Per 40 40.0 3.8-12.2 0.7-2.2 1.9-3.6 30.9 33.8 36.3 10.1 2.6 0.89 2.8 12.2 1.0 3.4 64.4 93.8 103.2 97.0

SHOT CREATION

Assisted by: Marshall Unasst. Drew ii Strickland Henson Barnes McDonald Knox Watts Bullock Others Total

# of Fg 65 65 26 16 16 13 6 2 1 0 0 210

% of Total Fg 31.0 31.0 12.4 7.6 7.6 6.2 2.9 1.0 0.5 0.0 0.0 100.0

+/– STATISTICS




On-Court 1046.2 72.3 +15.8 110.1 50.7 40.1 39.3 18.5 94.3 46.3 24.1 69.7 20.2

Off-Court 438.8 72.6 +1.1 97.7 45.4 32.8 32.7 17.8 96.6 46.1 26.2 70.2 18.6

Difference1 – -0.3 +14.7 +12.4 +5.3 +7.3 +6.6 -0.7 +2.3 -0.2 +2.1 -0.5 +1.6

As 5 (C) 1046.2 72.3 +3.2 110.1 50.7 40.1 39.3 18.5 94.3 46.3 24.1 69.7 20.2




Tyler Zeller #44

| 27

2011–12 Tar Heels

TURNOVER STATISTICS


Bad Pass 20 0.76 4.6

Bad Catch 15 0.57 3.4

Ball Handling 6 0.23 1.0

Offensive Foul 5 0.19 1.1




Total 50 1.91 11.4




Open 57-71 80.3 0-0 – 2.7 80.3

Lightly Contested 118-192 61.5 0-0 – 7.4 61.5

Contested 32-95 33.7 0-0 – 3.7 33.7

Heavily Contested 3-26 11.5 0-0 – 1.0 11.5

Total 210-384 54.7 0-0 – 14.8 54.7

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

0.38 0.08 0.08 0.50 0.15 1.03 0.76 0.76 4.4 25.0 12.5 0.3


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

0.54 0.27 0.23 1.26 3.06 33.8 0.70 0.50 38.5 53.9 7.7


N/A0-0

N/A0-0

0.0%0-3

37.5%3-8

42.9%3-7

33.3%2-6

40.0%4-10

40.0%2-5

0.0%0-2

25.0%1-4

75.0%3-4

75.0%3-4

N/A0-0

38.9%35-90

35.8%19-53

72.3%60-83

71.4%35-49

71.4%40-56

N/A0-0

Tyler Zeller #44



Total Close 135-188 7.2 11.6 71.8


Total Mid-Range 15-38 1.5 2.3 39.5

Total 3-Pt. 0-0 0.0 0.0 –

Total 0'-10' 189-331 12.7 20.3 57.1

Total 10'-20' 21-53 2.0 3.3 39.6

Total Paint 195-346 13.3 21.3 56.4

Total non-Paint 15-38 1.5 2.3 39.5

Total non-Close 75-196 7.5 12.0 38.3

ALL FgA 210-384 14.8 23.6 54.7

N/A0-0

28 |

2011–12 Tar Heels

6'3" • 180 • Rahway, NJ • Junior 2010–11 Minutes: Sg: 91.7% Pg: 8.2%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSStrickland was a pretty one-dimensional offensive threat last season: 71 of his 94 made field goals were either layups or dunks. Moreover, 66 of those 71 were made with his strong hand. Since 2005–06 (the first season we charted shot location), Byron Sanders (96.7% in 2005–06) and Marcus Ginyard (84.9% in 2006–07) are the only Heels to have a higher percentage of their total made field goals from close range than Strickland’s 75.5% last season. It’s a testament to Strickland’s athleticism, penetration, and finishing ability that he was able to get to the rim with his right hand so frequently, even when defenses knew that was his primary mission. But until he can diversify his offensive repertoire, he’ll remain somewhat of a liability on that end. Strickland’s floater is still basically nonexistent; he only attempted four shots in the 5–10-foot range last season, and almost always tries to get the whole way to the rim rather than pulling up in the paint. He made just 12-of-48 (25.0%) shots from 10–20 feet, consistent with his 25.0% (8-32) from behind the arc. Most of his midrange attempts were off the dribble, and his poor percentage (9-37, 24.3%) on those shots reflects his poor form (usually fading away or otherwise off-balance). When he rises straight up, the midrange jumper can be an effective weapon. But he needs to retool his mechanics to ensure that this is happening consistently. The bottom line is that Strickland made just 23-of-83 (27.7%) non-close attempts. Until that improves, he’ll continue to be almost exclusively a transition threat and a virtual non-factor against zone defenses.

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSStrickland had a lights-out December in which he scored 11.5 points per game on 57.1% from the field and 78.3% from the line. He even made three of his four three-pointers. But over the final three months, those numbers regressed to 6.5 points, 41.4% from the field, 65.8% from the line, and 3-of-22 (13.6%) behind the arc. After launching 15 three-pointers in February (out of 44 total field-goal attempts), Strickland attempted just two (in 46 total attempts) in March. While Carolina doesn’t need the December version of Strickland to win a title, a little more scoring output and efficiency from the off-guard position would make the task much easier. After a shaky 0.82 assist-to-turnover ratio in November, Strickland improved to a sterling 1.84 (68 assists, 37 TO) over the season’s final four months. Strickland converted 36.8% of his contested two-pointers, easily the best mark on the team (Zeller was next at 33.7%). His ability to finish tough shots around the rim remains a strength; the next frontier will be learning to make easier attempts away from the hoop.

DEFENSIVE BOX SCORE OBSERVATIONSNot surprisingly, the super-active and disruptive Strickland led the Tar Heels in deflections (6.16) and forced turnovers (3.54) per 40 minutes. He also led Carolina in denies per 40 minutes (2.05)—a category that charts how often a UNC defender forces an offensive reset by stonewalling an attacking opponent (or by blowing up a set play by fighting hard through a screen, etc.). Despite consistently matching up with the opponent’s best offensive guard, Strickland allowed the second-fewest field-goal attempts per 40 minutes of any UNC defender (his 9.1 was bested only by Reggie Bullock’s 7.1). This is further evidence of his ability to play strong denial defense and limit the touches of high-usage scorers. That skill—sometimes an underrated one—will continue to earn Strickland minutes this season.

Dexter strickland #1

| 29

2011–12 Tar Heels



FR 17.4 5.4 1.5 2.0 0.9 0.1 1.7 1.16 43.2 69.2 24.2 11.6 0.50

SO 27.0 7.5 3.1 2.2 1.2 0.0 1.5 1.52 45.6 68.6 25.0 12.0 0.34

Projected JR 27.0 8.0 3.4 2.9 1.6 0.1 1.8 1.65 46.7 71.4 27.8 13.4 0.45


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 41.4 24.7 53.1 3.29 5.02 0.00 7.7 58.4 +2.1

SO 46.2 32.8 55.3 3.54 6.16 0.16 8.2 58.5 -2.5


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Jackie Manuel (2004–05, SR, UNC)

MOST STATISTICALLY SIMILAR ACC SEASON (SOPHOMORES)John Johnson (1986–87, Maryland)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Jackie Manuel (2004–05, SR)

CAREER STATiSTiCS

2010–11 gAME-BY-gAME STATiSTiCSField goals 3-Point Fg Free Throws Rebounds

DATE OPP RESULT Min Fg FgA 3PM 3PA FTM FTA PTS OFF DEF TOT AST STL BLK TO PF11/12 Lipscomb W 23 0 2 0 0 2 4 2 0 1 1 1 1 0 0 111/18 Hofstra (N) W 23 4 5 1 2 2 2 11 0 2 2 4 3 0 2 111/19 Minnesota (N) L 19 3 3 1 1 0 0 7 0 0 0 2 2 0 1 311/21 Vanderbilt (N) L 26 3 6 0 0 0 0 6 2 1 3 1 1 0 4 311/23 North Carolina-Asheville W 32 2 6 0 2 7 10 11 2 4 6 2 3 0 5 111/28 College of Charleston W 24 3 5 0 0 3 4 9 3 1 4 3 1 0 2 211/30 @ Illinois L 25 2 9 0 1 3 5 7 1 2 3 1 1 0 3 212/4 Kentucky W 29 2 6 0 0 2 4 6 0 4 4 1 0 0 0 312/8 @ Evansville W 21 1 1 0 0 2 2 4 0 1 1 1 3 0 1 212/11 Long Beach State W 25 4 7 0 1 5 6 13 1 0 1 3 1 0 1 212/18 Texas L 30 6 10 1 1 5 6 18 0 1 1 3 1 0 0 012/21 William & Mary W 23 8 12 2 2 1 1 19 0 1 1 1 3 0 2 112/28 @ Rutgers W 23 3 6 0 0 3 4 9 1 2 3 1 1 0 1 1



30 |

2011–12 Tar Heels




WORP / 352

All games 37 27.0 7.5 3.1 2.2 1.2 0.0 1.5 1.9 1.52 45.6 68.6 25.0 47.6 53.0 58.7 13.4 3.6 8.1 12.0 0.34/ 40 Min.1 – 40.0 10.0 4.3 3.0 1.7 0.0 2.1 2.6 1.52 45.6 68.6 25.0 47.6 53.0 58.7 13.4 3.6 8.1 12.0 0.47nov. 7 24.6 7.6 2.7 2.0 1.7 0.0 2.4 1.9 0.82 47.2 68.0 33.3 50.0 55.4 69.4 15.6 4.9 6.3 12.2 0.35Dec. 6 25.2 11.5 1.8 1.7 1.5 0.0 0.8 1.5 2.00 57.1 78.3 75.0 60.7 65.2 54.8 15.6 1.4 5.9 18.5 1.56Jan. 7 25.6 7.0 4.7 1.9 1.1 0.0 1.0 1.6 1.86 44.7 51.7 0.0 44.7 47.3 76.3 13.6 5.3 13.2 12.6 0.44Feb. 8 27.6 6.0 3.1 3.0 0.8 0.0 1.1 2.4 2.67 34.1 75.0 20.0 37.5 44.9 45.5 12.6 3.3 8.0 10.1 -0.04Mar. 9 30.8 6.7 3.1 2.3 1.2 0.0 1.8 2.1 1.31 45.7 75.0 0.0 45.7 52.3 52.2 11.3 3.0 7.1 9.3 -0.24ACC 19 27.6 5.4 3.6 2.4 0.8 0.0 1.5 2.2 1.61 35.8 62.8 13.6 37.4 43.2 53.7 12.1 3.8 9.4 8.4 -0.40non-Conf 18 26.4 9.8 2.6 2.1 1.7 0.0 1.4 1.6 1.42 54.1 72.9 50.0 56.3 61.0 63.1 14.8 3.3 6.6 15.9 1.12Regular 30 26.1 7.8 3.2 2.2 1.2 0.0 1.4 1.9 1.59 45.1 67.3 25.8 47.4 52.5 57.7 14.1 3.8 8.4 12.5 0.44Post 7 31.0 6.4 3.0 2.4 1.4 0.0 1.9 1.9 1.31 48.4 75.0 0.0 48.4 55.6 64.5 10.7 2.9 6.8 9.8 -0.12vs. Top 25 11 28.5 7.1 2.8 1.7 1.1 0.0 1.1 2.2 1.58 41.5 67.7 16.7 42.3 48.1 52.3 12.2 2.3 7.5 9.4 -0.20vs. 26–50 6 30.0 7.0 3.3 2.7 1.3 0.0 1.8 2.0 1.45 37.8 80.0 28.6 40.5 47.6 40.5 13.1 5.3 6.0 10.1 -0.04vs. 51–100 12 25.1 7.3 3.8 2.3 0.9 0.0 1.4 2.1 1.65 51.7 63.2 25.0 53.3 56.4 63.3 13.5 5.2 9.8 13.3 0.57vs. 100+ 8 25.6 8.9 2.5 2.4 1.9 0.0 1.8 1.3 1.36 50.0 70.6 27.3 53.4 59.0 77.3 15.2 1.5 8.2 15.5 1.01Home 16 27.6 8.4 3.3 2.6 1.2 0.0 1.3 1.4 1.95 42.7 64.6 23.8 45.2 50.4 63.1 14.8 3.8 8.0 13.1 0.59Road 11 24.8 6.8 3.5 1.5 1.0 0.0 1.2 2.5 1.31 43.1 70.6 14.3 44.0 50.6 58.6 13.1 3.9 10.1 10.8 0.09neutral 10 28.5 6.9 2.6 2.4 1.6 0.0 2.0 2.0 1.20 55.6 77.3 50.0 57.8 62.2 48.9 11.5 3.0 6.2 11.2 0.20Wins 29 27.5 7.6 3.3 2.4 1.3 0.0 1.4 1.7 1.67 45.3 67.7 20.7 47.2 52.6 61.5 13.3 3.4 8.5 12.3 0.41Losses 8 25.4 7.5 2.6 1.5 1.1 0.0 1.5 2.6 1.00 46.7 72.7 66.7 48.9 54.1 48.9 13.5 4.1 6.3 10.6 0.06






Def. Rat.+1

On-Court Def. Eff.

All: Total 994 104-225 30-91.5 39-54 46.2 52.9 55.3 277 88 4 153 8.1 2.6 0.0 58.5 94.7 100.3 95.8

Per 40 40.0 4.2-9.1 1.2-3.7 1.6-2.2 46.2 52.9 55.3 11.1 3.5 0.16 6.2 8.1 2.6 0.0 58.5 94.7 100.3 95.8

ACC: Total 527 61.5-135.5 18.5-57.5 18-23 45.4 52.2 54.5 159.5 33 1 60 9.4 1.7 0.0 54.8 97.8 99.0 98.7

Per 40 40.0 4.7-10.3 1.4-4.4 1.4-1.7 45.4 52.2 54.5 12.1 2.5 0.08 4.6 9.4 1.7 0.0 54.8 97.8 99.0 98.7

SHOT CREATION

Assisted by: Unasst. Drew ii Marshall Barnes Zeller Henson Bullock Watts Knox McDonald Others Total

# of Fg 54 14 8 8 4 3 2 1 0 0 0 94

% of Total Fg 57.4 14.9 8.5 8.5 4.3 3.2 2.1 1.1 0.0 0.0 0.0 100.0

+/– STATISTICS




On-Court 994.2 72.1 +9.8 105.6 49.0 39.4 38.3 18.9 95.8 46.8 23.6 69.9 19.3

Off-Court 490.8 73.0 +14.8 108.1 49.4 34.9 34.8 17.0 93.3 44.9 27.2 69.8 20.5

Difference1 – -0.9 -5.0 -2.5 -0.4 +4.5 +3.5 -1.9 -2.5 -1.9 +3.6 +0.1 -1.2

As 2 (Sg) 912.1 72.3 +10.3 105.7 49.3 39.6 38.2 19.1 95.4 47.0 23.5 70.5 19.3

As 1 (Pg) 81.6 69.0 +2.5 103.2 45.4 33.1 40.5 17.8 100.7 45.0 25.2 63.5 19.1


1. Per-game stats in the “/ 40 minutes” row are pace-adjusted to reflect an average-paced ACC game for 2010-11 (67.9 possessions / 40 minutes). Per-game stats in all other rows are pace-dependent (based on UNC’s 2010–11 pace of 72.8 possessions / 40).2. WORP / 35 (wins over replacement player per 35 games) measures the number of marginal wins that a player contributes as compared to a “replacement level” ACC player at his position.


| 31

2011–12 Tar Heels



28.6%2-7

0.0%0-7

20.0%1-5

22.2%2-9

14.3%1-7

0.0%0-7

50.0%1-2

0.0%0-2

50.0%2-4

33.3%2-6

N/A0-0

50.0%3-6

100.0%3-3

25.0%1-4

100.0%1-1

66.7%2-3

65.2%43-66

59.4%19-32

37.5%9-24

18.2%2-11

TURNOVER STATISTICS


Bad pass 24 0.97 8.6







Total 54 2.17 19.4




Open 24-31 77.4 1-6 16.7 1.5 68.9

Lightly contested 37-63 58.7 6-15 40.0 3.1 59.0

Contested 25-68 36.8 1-11 9.1 3.2 33.5

Heavily contested 0-12 0.0 0-0 – 0.5 0.0

Total 86-174 49.4 8-32 25.0 8.2 47.6

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

1.73 0.28 0.64 1.33 0.68 3.98 2.29 0.97 13.5 10.7 12.6 0.9


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

2.21 1.45 1.37 3.06 9.05 44.0 2.29 5.43 27.4 54.8 17.8



Total Close 71-122 4.9 7.8 58.2


Total Mid-Range 11-43 1.7 2.8 25.6

Total 3-Pt. 8-32 1.3 2.1 37.5

Total 0'-10' 74-126 5.0 8.1 58.7

Total 10'-20' 12-47 1.9 3.0 25.5

Total Paint 75-130 5.2 8.3 57.7

Total non-Paint 19-75 3.0 4.8 30.7

Total non-Close 23-83 3.3 5.3 32.5

ALL FgA 94-206 8.2 13.2 47.6

32 |

2011–12 Tar Heels

John Henson #31 6'11" • 220 • Tampa, FL • Junior 2010–11 Minutes: PF: 95.7% C: 4.3%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSThe post equivalent of Dexter Strickland, 72.0% of Henson’s made field goals were dunks and layups—down from 75.0% as a freshman. As his offensive game continues to progress, expect that number to drop again this season. Even without much range or offensive versatility, Henson proved he’s long and athletic enough to score in double-digits. His 55 dunks easily led the Heels, and the ACC for that matter—only Mason Plumlee (46) and C.J. Leslie (44) had as many as 40—and his 131 close makes trailed only Zeller’s 135. While many of his close attempts were set up by terrific Marshall passes, Henson also did a much better job of creating his own close offense off the dribble (both from the perimeter and via steadily improving post footwork after receiving an entry pass). He displayed some skillful up-and-under, step-through, and spin moves in the post as a sophomore, but still has plenty of room for improvement in terms of attacking the basket from the low block. A menace on the offensive glass, he also led the Heels in second-chance, put-back hoops with 44 (26 of which were tip-ins or tip-dunks). As far as non-close attempts go, Henson favored the jump hook (with either hand, although preferring his “weak” left hand). He made 23-of-62 hooks (37.1%) as a sophomore, a nice improvement from his jump-hook percentage of 28.6% as a freshman. Truly ambidextrous, Henson attempted over a quarter of his field goals with his left hand, connecting on 56.5% of them (52-92). Henson made just 20-of-74 shots (27.0%) from 10–20 feet; shot selection can be an issue for Henson, and it’s probably not necessary for him to launch two shots per game from this distance (as he did last season). The combination of fewer and better attempts from midrange and an improved touch from this part of the court would go a long way towards raising Henson’s pedestrian offensive efficiency.

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSHenson’s touch from the free-throw line got better as the season progressed: 33% in November and December, followed by 46%, 56%, and 61% over the next three months. Henson can make big gains in offensive efficiency by simply maintaining that March performance at the charity stripe. He blocked 109 shots in Carolina’s 29 wins (3.8 per game), but only nine in the eight losses (1.1). His scoring efficiency was also significantly worse in losses. When Henson has a big game (on both ends), the Heels are very tough to beat. Perhaps not surprisingly (but still impressively), Henson blocked 8.7 shots per 40 minutes against opponents ranked outside the Pomeroy top 100. Sending a low-major foe into the paint against him was almost unfair. Error-prone, Henson was a true five-tool turnover machine as a sophomore, reaching double digits in each of the five categories charted (passing, ball handling, catching, traveling, offensive fouls)—a first in the five seasons we’ve been recording turnovers by type.

DEFENSIVE BOX SCORE OBSERVATIONSCarolina’s most important defender from a +/- perspective, opponents made just 27.0% of their two-pointers against Henson. They had better luck from behind the arc, connecting on 33.3% of their 120 attempts. Despite his freshman cameo on the wing, Henson can still struggle to close out on jump shooters. Extremely active, Henson was credited (via defensive charting) with 12.1 defensive stops per 40 minutes—Zeller was a distant second with 9.6. Between blocking shots, altering shots, and corralling defensive boards, Henson’s impact on the defensive end is almost always felt.

| 33

2011–12 Tar Heels

John Henson #31


FR 15.8 5.7 4.4 0.9 0.7 1.6 1.2 0.76 48.6 43.8 22.2 18.4 1.05

SO 26.7 11.7 10.1 0.8 0.6 3.2 2.1 0.39 50.0 47.9 20.0 19.9 1.88

Projected JR 27.0 12.0 10.4 1.1 0.8 3.4 2.0 0.57 51.5 55.6 25.0 22.4 2.34


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 40.1 46.9 47.2 2.83 4.23 0.27 17.6 56.2 -4.4

SO 28.7 33.3 35.5 2.43 3.82 0.12 24.8 66.4 +2.9


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Sharone Wright (1992–93, SO, Clemson)

MOST STATISTICALLY SIMILAR ACC SEASON (SOPHOMORES)Sharone Wright (1992–93)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Ed Davis (2008–09, FR)

CAREER STATiSTiCS





34 |

2011–12 Tar Heels

John Henson #31



WORP / 352

All games 37 26.7 11.7 10.1 0.8 0.6 3.2 2.1 1.8 0.39 50.0 47.9 16.7 50.1 50.2 39.0 19.7 12.7 25.3 19.9 1.88/ 40 Min.1 – 40.0 16.3 14.1 1.1 0.8 4.5 2.9 2.5 0.39 50.0 47.9 16.7 50.1 50.2 39.0 19.7 12.7 25.3 19.9 2.63nov. 7 23.7 11.1 10.3 0.6 0.4 2.9 2.3 1.4 0.25 54.0 33.3 – 54.0 50.5 47.6 21.4 17.7 26.1 20.9 1.84Dec. 6 21.2 8.3 7.2 0.5 0.7 2.3 2.0 1.2 0.25 46.8 33.3 – 46.8 45.0 38.3 20.3 11.6 22.5 15.8 0.83Jan. 7 25.3 12.4 7.9 1.3 0.9 4.0 1.9 2.1 0.69 58.7 46.4 – 58.7 57.0 44.4 19.8 10.1 21.2 24.5 2.66Feb. 8 29.3 11.9 12.0 1.1 0.3 3.5 1.9 1.8 0.60 46.5 56.0 25.0 47.1 48.5 29.1 18.7 12.1 29.1 19.4 1.95Mar. 9 31.7 13.7 12.0 0.6 0.8 3.1 2.2 2.1 0.25 46.7 61.0 0.0 46.7 49.4 39.1 19.2 12.5 25.6 18.7 1.93ACC 19 29.2 12.4 11.1 1.1 0.5 3.3 2.1 1.9 0.53 49.0 55.7 20.0 49.3 50.6 35.0 19.1 12.3 26.0 19.8 2.02non-Conf 18 24.2 10.9 9.1 0.5 0.7 3.1 2.0 1.6 0.25 51.2 40.3 0.0 51.2 49.7 43.9 20.5 13.3 24.5 20.1 1.73Regular 30 25.5 11.3 9.7 0.9 0.5 3.1 2.0 1.7 0.45 51.4 45.1 25.0 51.6 50.9 39.6 19.8 12.5 25.6 20.4 1.89Post 7 31.9 13.4 12.0 0.4 0.9 3.4 2.3 2.1 0.19 45.2 58.1 0.0 45.2 47.6 36.9 19.5 13.7 24.3 18.3 1.85vs. Top 25 11 29.5 12.1 10.7 0.9 0.8 2.1 1.7 2.1 0.53 47.6 40.0 33.3 48.0 47.4 23.8 18.9 13.6 23.0 17.2 1.47vs. 26–50 6 28.0 13.0 10.8 1.0 0.3 3.3 2.7 1.7 0.38 54.2 51.9 0.0 54.2 54.3 45.8 20.2 11.9 27.0 20.6 2.11vs. 51–100 12 26.6 10.2 9.3 0.8 0.6 3.1 2.2 1.7 0.35 49.0 48.9 0.0 49.0 49.4 44.1 18.0 10.9 24.1 17.5 1.38vs. 100+ 8 22.1 12.5 10.0 0.6 0.5 4.8 1.9 1.5 0.33 52.0 50.0 – 52.0 52.1 52.0 23.9 15.4 30.1 28.5 2.99Home 16 25.5 11.9 10.6 1.1 0.6 3.6 1.7 1.8 0.67 52.9 47.5 0.0 52.9 52.5 39.9 19.9 12.6 29.0 23.7 2.51Road 11 26.9 11.4 8.2 0.7 0.5 2.8 2.2 1.5 0.33 51.4 48.5 33.3 51.9 51.8 31.4 18.7 9.2 21.3 17.3 1.35neutral 10 28.5 11.7 11.5 0.4 0.7 2.9 2.5 2.0 0.16 44.3 47.9 0.0 44.3 45.4 45.3 20.4 16.6 24.2 17.3 1.44Wins 29 27.0 12.3 10.2 0.9 0.7 3.8 2.0 1.6 0.46 51.7 50.9 20.0 51.9 52.2 39.6 19.6 11.7 26.3 21.9 2.31Losses 8 25.6 9.5 9.8 0.5 0.4 1.1 2.4 2.4 0.21 43.4 35.7 0.0 43.4 42.6 36.8 20.1 16.9 21.6 12.2 0.30






Def. Rat.+1

On-Court Def. Eff.

All: Total 995 131.5-458.5 40-120 44-65 28.7 33.0 35.5 347 60.5 3 95 25.3 1.2 11.1 66.4 90.1 105.4 94.0

Per 40 40.0 5.3-18.4 1.6-4.8 1.8-2.6 28.7 33.0 35.5 13.9 2.4 0.12 3.8 25.3 1.2 11.1 66.4 90.1 105.4 94.0

ACC: Total 560 72-241 23.5-66.5 25-42 29.9 34.8 36.9 192.5 31 1 54 26.0 0.9 11.4 66.4 91.5 105.7 97.4

Per 40 40.0 5.1-17.2 1.7-4.8 1.8-3.0 29.9 34.8 36.9 13.8 2.2 0.07 3.9 26.0 0.9 11.4 66.4 91.5 105.7 97.4

SHOT CREATION

Assisted by: Unasst. Marshall Strickland Barnes Drew ii Zeller Watts Knox McDonald Bullock Others Total

# of Fg 95 45 12 11 9 4 3 2 1 0 0 182

% of Total Fg 52.2 24.7 6.6 6.0 5.0 2.2 1.7 1.1 0.6 0.0 0.0 100.0

+/– STATISTICS




On-Court 995.1 71.6 +8.7 102.7 47.6 35.5 38.3 19.0 94.0 45.1 21.6 68.6 19.9

Off-Court 489.9 73.9 +16.7 113.6 52.4 42.8 34.6 16.9 96.9 48.5 31.6 72.6 19.3

Difference1 – -2.3 -8.0 -10.9 -4.8 -7.3 +3.7 -2.1 +2.9 +3.4 +10.0 -4.0 +0.6

As 4 (PF) 952.3 71.6 +8.7 102.6 47.5 36.0 38.5 19.2 93.9 45.2 20.9 68.6 19.9

As 5 (C) 42.8 71.3 +8.8 106.3 49.3 23.9 34.7 14.0 97.5 43.9 37.9 68.2 19.8




| 35

2011–12 Tar Heels

John Henson #31


N/A0-0

0.0%0-1

25.0%1-4

100.0%1-1

22.2%2-9

33.3%1-3

36.4%4-11

30.0%3-10

0.0%0-5

27.3%3-11

15.4%2-13

42.9%3-7

0.0%0-1

0.0%0-1

34.2%13-38

37.0%17-46

70.2%40-57

70.0%35-50

60.2%56-93

33.3%1-3

TURNOVER STATISTICS


Bad pass 27 1.09 6.3


Bad catch 13 0.52 3.0





Total 76 3.06 17.7




Open 79-93 85.0 1-2 50.0 3.8 84.7


Contested 35-105 33.3 0-1 0.0 4.3 33.0

Heavily contested 0-32 0.0 0-0 – 1.3 0.0

Total 181-358 50.6 1-6 16.7 14.6 50.1

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

1.33 0.04 0.04 0.28 0.48 1.69 1.17 1.09 5.8 24.1 13.7 0.4


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

1.65 0.28 0.24 1.25 4.50 37.5 1.52 2.29 38.6 42.1 19.3



Total Close 131-200 8.0 13.0 65.5


Total Mid-Range 13-53 2.1 3.4 24.5

Total 3-Pt. 1-6 0.2 0.4 25.0

Total 0'-10' 161-284 11.4 18.4 56.7

Total 10'-20' 20-74 3.0 4.8 27.0

Total Paint 168-305 12.3 19.8 55.1

Total non-Paint 14-59 2.4 3.8 24.6

Total non-Close 51-164 6.6 10.6 31.4

ALL FgA 182-364 14.6 23.6 50.1

36 |

2011–12 Tar Heels

6'4" • 195 • Dumfries, VA • Sophomore 2010–11 Minutes: Pg: 100.0%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSSimply put, Marshall needs to finish more consistently at the rim. He made just 37-of-82 (45.1%) layups as a freshman. From his strong (left) side, that figure was 49.1% (on 55 attempts); from the middle/right side, it was just 37.0% (on 27 attempts). As teams began to play him more for the drive-and-dish, a much larger emphasis was placed on his ability to score in the paint. The ultimate cerebral player, Marshall undoubtedly will have a few tricks up his sleeve as a sophomore intended to improve his finishing. Adding a more consistent floater is also a point of emphasis: Marshall made only 6-of-20 as a freshman. Despite lacking blazing speed, he’s clever, athletic, and physical enough to get into the paint almost at will. So, by improving at the rim and with the floater—both of which will set up the pass, his most dangerous offensive weapon—Marshall can become a pick-your-poison nightmare for opposing coaches. Outside the paint, he’s already an underrated scoring threat. Marshall led the Heels by shooting 46.4% on 28 attempts from 10–20 feet. Of these 28 attempts, 26 of them (and all 13 makes) were created off the dribble. Marshall’s ability to manufacture and consistently make midrange jumpers is a valuable skill, especially late in the shot clock and on halfcourt possessions that break down. While almost all of his midrange offense comes via the dribble, Marshall prefers the catch-and-shoot jumper from behind the arc (48 of his 53 attempts were of this variety). Not a volume shooter from deep, the majority of his three-point attempts occurred after the defense was broken down. Specifically, Marshall made 15-of-33 three-pointers (a sparkling 45.5%) following a drive-and-kick or inside-out pass. He also knocked down 44.4% of his 18 trifectas against opposing zones. As long as he can continue to keep opposing defenses honest for doubling down and over-helping, teams won’t be able to play Marshall strictly for the pass.

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSDue to the timing of Drew II’s departure, Marshall’s minutes were skewed towards the meaty part of the Carolina schedule: 55% were against top-50 foes as compared to 46% of UNC’s total minutes. Against teams outside the top 100, Marshall averaged a staggering 13.3 assists per 40 minutes (vs. “just” 9.4 per 40 vs. the top 100). His gaudy assist and assist-to-turnover numbers as a freshman were actually skewed downwards due to how his minutes were distributed across strength of opponent. As a scorer, Marshall seemed to hit a wall in March. In 35 minutes per game in the final month, he shot just 33.8% from the field, including only 31.3% on two-pointers. Tired legs almost certainly played a role in Marshall’s inability to consistently finish at the rim late in the season. More rest (depending on Strickland’s development as a point guard) and improved stamina and conditioning should lead to a fresher Marshall in March 2012 than the version we saw in March 2011.

DEFENSIVE BOX SCORE OBSERVATIONSMarshall is a different type of defender than the typical Roy Williams point guard. Relying less on ball pressure and more on angles and length, Marshall is still generally effective, if slightly ill-suited for Carolina’s preferred scheme. Last season, he forced fewer turnovers (2.6) and had fewer deflections (4.2) than Drew (3.1 and 5.4) per 40 minutes, but also forced a significantly lower eFG% (44.3% vs. 57.2%). Opponents shot just 26.5% behind the arc on the 121 attempts that Marshall was responsible for—in large part due to his fantastic positioning and length on close-outs.

Kendall Marshall #5

| 37

2011–12 Tar Heels

Kendall Marshall #5


FR 24.6 6.2 2.1 6.2 1.1 0.1 2.5 2.50 41.8 69.0 37.7 16.0 1.41

Projected SO 29.0 7.6 2.5 8.4 1.5 0.1 2.7 3.13 44.4 72.5 38.5 18.9 2.14


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 37.6 26.5 47.0 2.56 4.17 0.22 7.6 58.9 +2.1


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Karl Brown (1988–89, JR, GA Tech)

MOST STATISTICALLY SIMILAR ACC SEASON (FRESHMEN)Keith Gatlin (1983–84, Maryland)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)King Rice (1989–90, JR)

CAREER STATiSTiCS





38 |

2011–12 Tar Heels

Kendall Marshall #5



WORP / 352

All games 37 24.6 6.2 2.1 6.2 1.1 0.1 2.5 1.4 2.50 41.8 69.0 37.7 47.3 51.8 46.2 17.6 0.7 7.7 16.0 1.41/ 40 Min.1 – 40.0 9.4 3.2 9.4 1.7 0.1 3.8 2.1 2.50 41.8 69.0 37.7 47.3 51.8 46.2 17.6 0.7 7.7 16.0 2.14nov. 7 15.0 4.3 1.4 4.0 0.9 0.0 2.0 1.3 2.00 64.7 50.0 60.0 73.5 69.0 58.8 17.7 0.0 9.4 18.0 1.08Dec. 6 13.8 2.5 1.7 4.0 0.7 0.0 1.2 0.8 3.43 31.6 33.3 28.6 36.8 36.7 15.8 17.7 1.3 10.7 14.9 0.68Jan. 7 20.9 5.3 1.0 5.1 1.1 0.1 2.3 0.7 2.25 50.0 87.5 20.0 52.3 62.5 72.7 16.3 0.7 4.1 17.3 1.39Feb. 8 32.8 9.3 2.6 7.6 1.6 0.0 3.1 1.3 2.44 45.3 70.0 38.5 50.0 55.0 56.6 17.5 0.0 7.9 16.8 2.06Mar. 9 35.1 8.2 3.2 9.0 1.0 0.2 3.3 2.3 2.70 33.8 68.0 39.1 40.1 44.7 35.2 18.1 1.3 7.8 14.4 1.58ACC 19 29.6 7.9 2.1 6.9 1.2 0.1 3.0 1.4 2.30 40.5 70.0 35.5 45.0 50.5 49.6 18.0 0.8 6.7 15.0 1.45non-Conf 18 19.4 4.4 2.1 5.5 1.0 0.1 1.9 1.3 2.83 44.3 66.7 40.9 51.6 54.6 39.3 16.8 0.6 9.9 17.7 1.35Regular 30 22.2 5.9 1.8 5.6 1.0 0.03 2.2 1.2 2.51 46.5 70.3 38.2 51.6 55.8 49.6 17.4 0.5 7.6 16.9 1.42Post 7 35.1 7.4 3.3 8.9 1.3 0.3 3.6 2.1 2.48 30.2 65.0 36.8 36.8 41.6 37.7 18.0 1.3 8.0 13.5 1.35vs. Top 25 11 28.7 8.5 2.1 6.2 1.0 0.1 3.1 1.5 2.00 34.6 72.3 25.0 37.8 46.4 60.3 19.9 1.0 6.2 13.9 1.17vs. 26–50 6 30.3 6.2 2.8 8.7 2.0 0.2 2.1 1.7 4.00 50.0 60.0 50.0 59.6 60.2 38.5 14.3 0.6 8.7 19.6 2.55vs. 51–100 12 21.8 6.2 1.6 4.9 0.7 0.0 2.8 0.8 1.79 47.5 63.2 37.5 52.5 54.4 32.2 18.7 0.8 6.4 13.6 0.85vs. 100+ 8 19.1 3.3 2.3 6.4 1.1 0.1 1.5 1.6 4.25 42.1 75.0 57.1 52.6 57.0 42.1 14.7 0.0 11.6 20.2 1.70Home 16 22.0 5.7 2.0 6.6 1.1 0.1 2.3 1.2 2.84 54.1 69.2 38.9 59.8 62.0 42.6 17.3 0.6 8.4 19.5 1.84Road 11 24.0 6.9 1.8 4.4 0.9 0.0 2.3 0.9 1.92 38.1 71.9 35.7 42.1 48.6 50.8 18.0 0.4 7.1 13.1 0.83neutral 10 29.6 6.3 2.5 7.7 1.2 0.2 3.0 2.1 2.57 32.8 65.4 38.1 39.7 44.8 44.8 17.5 1.1 7.3 14.4 1.34Wins 29 24.9 6.3 2.1 6.7 1.1 0.1 2.4 1.3 2.75 44.4 71.0 40.5 50.8 55.5 51.9 17.3 0.7 7.8 17.6 1.71Losses 8 23.6 5.8 1.9 4.4 1.1 0.0 2.6 1.5 1.67 34.7 60.0 27.3 37.8 41.0 30.6 18.7 0.6 7.3 10.1 0.29






Def. Rat.+1

On-Court Def. Eff.

All: Total 921 90-239.5 32-121 33-45 37.6 44.3 47.0 245 59 5 96 7.7 2.4 0.3 58.9 94.6 100.4 94.2

Per 40 40.0 3.9-10.4 1.4-5.3 1.4-2.0 37.6 44.3 47.0 10.6 2.6 0.22 4.2 7.7 2.4 0.3 58.9 94.6 100.4 94.2

ACC: Total 567 61-139 22-72.5 15-19 43.9 51.8 53.7 159 34 2 56 6.7 2.2 0.2 54.7 97.7 99.0 93.0

Per 40 40.0 4.3-9.8 1.6-5.1 1.1-1.3 43.9 51.8 53.7 11.2 2.4 0.14 4.0 6.7 2.2 0.2 54.7 97.7 99.0 93.0

SHOT CREATION

Assisted by: Unasst. Strickland Barnes Zeller McDonald Knox Drew ii Bullock Watts Henson Others Total

# of Fg 56 5 4 4 2 2 1 1 1 0 0 76

% of Total Fg 73.7 6.6 5.3 5.3 2.6 2.6 1.3 1.3 1.3 0.0 0.0 100.0

+/– STATISTICS




On-Court 920.6 72.0 +16.5 110.7 50.9 36.4 37.5 17.7 94.2 46.2 22.5 69.8 20.1

Off-Court 564.4 73.1 +3.1 99.4 46.2 40.3 36.6 19.3 96.3 46.2 28.5 70.1 19.1

Difference1 – -1.1 +13.4 +11.3 +4.7 -3.9 +0.9 +1.6 +2.1 0.0 +6.0 -0.3 +1.0

As 1 (Pg) 920.6 72.0 +16.5 110.7 50.9 36.4 37.5 17.7 94.2 46.2 22.5 69.8 20.1




| 39

2011–12 Tar Heels

Kendall Marshall #5


40.0%6-15

35.7%5-14

0.0%0-1

60.0%3-5

80.0%4-5

N/A0-0

33.3%2-6

50.0%2-4

66.7%2-3

0.0%0-2

0.0%0-2

N/A0-0

40.0%2-5

0.0%0-2

22.2%2-9

40.0%4-10

36.8%7-19

37.5%3-8

49.1%27-55

41.2%7-17

TURNOVER STATISTICS


Bad pass 67 2.91 21.5







Total 92 4.00 29.5




Open 14-19 73.7 5-9 55.6 1.2 76.8


Contested 11-45 24.4 1-5 20.0 2.2 25.0

Heavily contested 0-7 0.0 0-1 0.0 0.3 0.0

Total 56-129 43.4 20-53 37.7 7.9 47.3

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

7.08 1.69 0.83 2.48 2.09 12.08 2.22 2.91 40.7 11.1 21.1 4.5


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

8.65 3.91 2.39 8.34 26.20 46.1 2.97 14.16 45.4 41.7 12.9



Total Close 37-82 3.6 5.8 45.1


Total Mid-Range 9-18 0.8 1.3 50.0

Total 3-Pt. 20-53 2.3 3.7 56.6

Total 0'-10' 43-101 4.4 7.1 42.6

Total 10'-20' 13-28 1.2 2.0 46.4

Total Paint 47-111 4.8 7.8 42.3

Total non-Paint 29-71 3.1 5.0 54.9

Total non-Close 39-100 4.3 7.0 49.0

ALL FgA 76-182 7.9 12.8 47.3

40 |

2011–12 Tar Heels

leslie McDonald #2 6'5" • 210 • Memphis, TN • Junior 2010–11 Minutes: Sg: 89.2% SF: 10.8%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSAs a scorer, McDonald was almost the mirror image of Strickland, the player with whom he split minutes at shooting guard. While 76% of Strickland’s made field goals were layups or dunks, only 13% of McDonald’s were. Only Wes Miller (9% in 2006, 4% in 2007) has had a number that low since we started tracking shot location in 2005–06—no other Heel in that six-year period is below 22% (Graves in 2010). Moreover, McDonald made just 11-of-24 close attempts (45.8%) as a sophomore. Clearly, increasing both the rate and efficiency of his close shots is an area for improvement. An improved handle would help McDonald attack the rim and slash more frequently in the halfcourt. He also needs to fill the lanes harder in transition, an area in which Wayne Ellington made huge strides as his Carolina career progressed. The other side of the coin, of course, is that only 9% of Strickland’s made field goals were three-pointers (on 25% shooting) as compared to 59% of McDonald’s (on 38.1% shooting). As one might expect based on their distribution of field-goal attempts, Strickland also gets to the line far more often than McDonald (respective free-throw attempt rates of 58.7 and 17.5). McDonald’s intermediate game is also a strength. From 10–20 feet, McDonald knocked down 19-of-43 attempts (44.2%). He trailed just Barnes in midrange makes per 40, and only Marshall in midrange FG%. McDonald was also a versatile midrange scorer—hitting 9-of-23 off the dribble (generally using a single bounce to create space) and 10-of-20 catch-and-shoot attempts. McDonald made just 4-of-20 floaters as a sophomore—while his one-bounce pull-up jumper was an effective weapon, he tended to get into trouble whenever he took more than a single dribble (either to get to the rim or attempt a floater).

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSMcDonald’s splits by level of competition were quite dramatic last season. In 16 games against the top 50, he averaged 5.3 points while shooting 34.1% from the field and 28.9% behind the arc. In 20 games against opponents outside of the top 50, those numbers improved to 8.4, 43.5%, and 43.9%. Against the top 50, his assist-to-turnover ratio was 0.20; it improved to 1.13 in all other games. If McDonald is able to return to the rotation this season following his knee surgery, he’ll still need to prove that he can perform consistently against top-flight opponents in order to help the team during the stretch run.

DEFENSIVE BOX SCORE OBSERVATIONSProbably the scrappiest and toughest Tar Heel defender last season, McDonald was never afraid to dive for a loose ball or battle for a long rebound. He trailed only Zeller in offensive fouls drawn (1.00) and floorburns (2.14) per 40 minutes. He drew 11 of his 14 offensive fouls in ACC contests—a rate of 1.52 per 40 minutes, easily good for the team lead in league play (followed by Watts at 0.93 and Zeller at 0.89). His ability to mix it up and play physically also led to some fouling issues. While McDonald was rarely in foul trouble due to his amount of playing time, he did allow a team-leading 5.3 free throws per 40 minutes. By comparison, Strickland allowed just 2.2 trips to the line per 40. McDonald and Strickland allowed almost identical eFG% on shots they were responsible for (52.9% for Strickland, 53.0% for McDonald). But due to Strickland’s ability to force turnovers and keep opponents off the foul line, he had a much higher Stop% than his fellow off-guard (58.5% vs. 52.6%).

| 41

2011–12 Tar Heels

leslie McDonald #2


FR 10.3 3.4 1.5 0.6 0.2 0.1 0.5 1.22 30.9 65.5 20.8 8.4 -0.11

SO 15.7 7.0 2.1 0.6 0.5 0.1 0.8 0.67 38.6 74.4 38.1 12.3 0.23

Projected JR inJURED


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 35.2 44.1 48.2 3.32 5.30 0.68 8.8 62.8 +11.7

SO 45.6 35.1 57.8 3.06 4.99 1.00 8.6 52.6 -0.8


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Steven Goolsby (1997–98, SR, Wake Forest)

MOST STATISTICALLY SIMILAR ACC SEASON (SOPHOMORES)Curtis Staples (1995–96, Virginia)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Will Graves (2009–10, JR)

CAREER STATiSTiCS



1/2 Saint Francis (PA) W 17 4 7 4 6 0 0 12 0 3 3 0 0 0 0 11/8 @ Virginia W 17 3 7 1 3 0 1 7 0 3 3 1 0 0 1 11/13 Virginia Tech W 14 1 6 1 6 0 0 3 1 1 2 0 0 0 0 21/16 @ Georgia Tech L 18 2 10 2 5 4 4 10 1 2 3 0 0 0 0 21/18 Clemson W DID NOT PLAY1/26 @ Miami (FL) W 12 2 8 2 6 0 0 6 2 1 3 1 0 0 1 11/29 North Carolina State W 14 1 5 1 3 0 0 3 1 0 1 2 0 0 1 02/1 @ Boston College W 15 4 9 1 4 0 0 9 0 0 0 1 0 0 0 12/6 Florida State W 7 1 5 1 4 0 0 3 1 0 1 0 0 0 2 32/9 @ Duke L 16 3 7 1 5 1 1 8 0 2 2 0 0 0 2 22/12 @ Clemson W 22 0 3 0 2 1 2 1 1 2 3 0 2 0 0 22/15 Wake Forest W 16 3 9 2 6 5 6 13 5 2 7 2 1 0 2 12/19 Boston College W 14 1 5 1 3 0 0 3 0 0 0 0 2 0 0 12/23 @ North Carolina State W 12 2 4 1 2 0 0 5 0 1 1 0 1 0 2 12/27 Maryland W 20 6 10 3 5 0 0 15 2 2 4 0 1 0 2 23/2 @ Florida State W 17 3 7 3 5 1 2 10 1 1 2 0 1 0 0 03/5 Duke W 15 3 3 1 1 2 2 9 2 3 5 1 0 0 0 33/11 Miami (FL) (N) W 22 4 7 3 4 0 0 11 0 2 2 1 0 0 2 23/12 Clemson (N) W 16 2 6 1 3 0 0 5 0 3 3 0 1 0 0 43/13 Duke (N) L 24 1 6 1 4 3 4 6 1 3 4 1 3 0 3 33/18 Long Island University (N) W 21 0 7 0 5 2 2 2 0 4 4 2 0 1 1 33/20 Washington (N) W 16 2 5 1 3 0 0 5 2 1 3 1 0 0 0 13/25 Marquette (N) W 21 2 8 1 3 0 0 5 2 2 4 0 0 0 1 13/27 Kentucky (N) L 17 1 4 0 2 0 0 2 1 0 1 0 0 0 1 3


42 |

2011–12 Tar Heels

leslie McDonald #2



WORP / 352

All games 36 15.7 7.0 2.1 0.6 0.5 0.1 0.8 1.8 0.67 38.6 74.4 38.1 50.0 52.2 17.5 18.6 5.2 8.6 12.3 0.23/ 40 Min.1 – 40.0 16.6 5.0 1.4 1.2 0.1 1.9 4.3 0.67 38.6 74.4 38.1 50.0 52.2 17.5 18.6 5.2 8.6 12.3 0.55nov. 7 14.4 6.6 1.0 0.1 0.6 0.0 1.1 2.0 0.13 47.2 57.1 42.1 58.3 58.5 19.4 17.7 2.1 4.9 9.9 -0.05Dec. 6 13.5 8.8 1.5 1.0 0.5 0.2 0.2 1.5 6.00 46.2 75.0 44.0 60.3 61.9 20.5 21.6 3.9 7.3 23.3 1.33Jan. 6 15.3 6.8 2.5 0.7 0.0 0.0 0.5 1.2 1.33 30.2 80.0 37.9 43.0 45.2 11.6 20.4 5.7 10.7 10.5 0.02Feb. 8 15.3 7.1 2.3 0.4 0.9 0.0 1.3 1.6 0.30 38.5 77.8 32.3 48.1 50.6 17.3 20.7 7.8 7.3 12.1 0.20Mar. 9 18.8 6.1 3.1 0.7 0.6 0.1 0.9 2.2 0.75 34.0 80.0 36.7 44.3 47.6 18.9 15.2 5.6 11.1 9.5 -0.12ACC 18 16.2 7.1 2.6 0.6 0.7 0.0 1.0 1.7 0.56 35.9 77.3 36.6 47.0 49.8 18.8 19.3 6.5 9.5 11.9 0.19non-Conf 18 15.2 6.9 1.7 0.6 0.4 0.1 0.7 1.8 0.83 41.5 70.6 39.7 53.3 54.8 16.0 17.9 3.8 7.6 12.7 0.27Regular 29 14.8 7.4 1.9 0.5 0.5 0.03 0.8 1.6 0.68 41.1 72.7 40.0 53.3 55.2 18.3 19.6 5.4 7.8 14.3 0.45Post 7 19.6 5.1 3.0 0.7 0.6 0.1 1.1 2.4 0.63 27.9 83.3 29.2 36.1 39.3 14.0 15.4 4.6 10.8 5.7 -0.68vs. Top 25 10 16.3 4.4 2.3 0.3 0.7 0.0 0.8 2.3 0.38 33.3 72.7 23.1 40.0 43.8 24.4 13.7 4.5 9.7 6.7 -0.45vs. 26–50 6 15.8 6.8 2.3 0.0 0.5 0.0 1.2 1.8 0.00 34.9 50.0 34.6 45.4 45.7 9.3 20.4 8.8 6.2 7.7 -0.32vs. 51–100 12 15.3 7.8 1.7 0.8 0.3 0.0 0.7 1.0 1.25 41.8 71.4 47.9 56.3 57.1 8.9 19.3 4.0 7.0 14.9 0.53vs. 100+ 8 15.4 9.1 2.5 0.9 0.6 0.3 0.9 2.1 1.00 41.1 82.4 38.2 52.7 57.0 30.4 22.6 5.1 11.2 19.2 1.04Home 15 14.1 7.7 1.9 0.6 0.5 0.1 0.6 1.7 1.00 44.9 73.3 42.9 58.4 59.8 16.9 19.3 6.4 7.4 17.1 0.33Road 11 15.6 7.3 2.2 0.5 0.5 0.0 0.6 1.3 0.71 38.0 71.4 38.1 49.3 51.5 19.7 18.9 4.3 9.7 12.9 0.31neutral 10 18.1 5.7 2.4 0.6 0.6 0.1 1.4 2.3 0.43 30.2 80.0 30.6 38.9 42.1 15.9 17.5 4.6 8.7 6.0 -0.60Wins 28 15.6 7.7 2.3 0.6 0.5 0.1 0.7 1.7 0.95 42.1 71.4 42.2 55.1 56.5 15.7 18.7 5.5 9.0 15.1 0.57Losses 8 16.1 4.5 1.8 0.3 0.6 0.0 1.4 2.0 0.18 24.4 81.8 20.0 30.0 35.8 24.4 18.0 4.1 6.9 2.6 -0.95






Def. Rat.+1

On-Court Def. Eff.

All: Total 561 60-131.5 19.5-55.5 53-74 45.6 53.0 57.8 192.5 43 14 70 8.6 1.9 0.4 52.6 97.1 97.9 95.5

Per 40 40.0 4.3-9.4 1.4-4.0 3.8-5.3 45.6 53.0 57.8 13.7 3.1 1.00 5.0 8.6 1.9 0.4 52.6 97.1 97.9 95.5

ACC: Total 290 28.5-60.5 11-26 33-42 47.1 56.2 62.8 101 27 11 37 9.5 2.4 0.0 54.3 98.1 98.6 94.5

Per 40 40.0 3.9-8.3 1.5-3.6 4.6-5.8 47.1 56.2 62.8 13.9 3.7 1.52 5.1 9.5 2.4 0.0 54.3 98.1 98.6 94.5

SHOT CREATION

Assisted by: Marshall Unasst. Barnes Strickland Watts Bullock Drew ii Henson Knox Zeller Others Total

# of Fg 27 19 9 7 6 5 5 4 3 1 0 86

% of Total Fg 31.4 22.1 10.5 8.1 7.0 5.8 5.8 4.7 3.5 1.2 0.0 100.0

+/– STATISTICS




On-Court 561.4 72.5 +14.0 109.5 49.8 34.6 37.0 17.3 95.5 46.4 28.0 69.1 21.0

Off-Court 923.6 72.3 +9.8 104.5 48.7 40.0 37.2 18.9 94.7 46.1 22.9 70.3 18.9

Difference1 – +0.2 +4.2 +5.0 +1.1 -5.4 -0.2 +1.6 -0.8 -0.3 -5.1 -1.2 +2.1

As 2 (Sg) 500.8 72.4 +13.9 109.3 49.7 34.5 36.4 17.1 95.4 46.2 25.8 68.4 21.0

As 3 (SF) 60.5 73.9 +14.9 111.4 50.5 35.4 42.1 19.2 96.5 48.3 47.7 75.0 21.1




| 43

2011–12 Tar Heels

leslie McDonald #2


42.9%9-21

60.0%12-20

100.0%1-1

0.0%0-3

100.0%2-2

33.3%2-6

25.0%1-4

33.3%1-3

28.6%2-7

50.0%4-8

100.0%5-5

25.0%1-4

20.8%5-24

36.8%14-38

0.0%0-8

35.7%5-14

54.5%6-11

0.0%0-2

45.5%5-11

35.5%11-31

TURNOVER STATISTICS


Bad pass 15 1.07 7.1







Total 30 2.14 14.3




Open 8-10 80.0 4-8 50.0 1.3 77.8


Contested 11-41 26.8 7-35 20.0 5.4 28.3


Total 35-89 39.3 51-134 38.1 15.9 50.0

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

1.14 0.57 0.00 0.50 0.78 2.21 1.92 1.07 6.4 16.7 15.4 0.7


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

1.57 1.50 0.36 1.92 6.41 34.4 1.47 6.41 40.0 38.9 21.1



Total Close 11-24 1.7 2.7 45.8


Total Mid-Range 17-36 2.6 4.1 47.2

Total 3-Pt. 51-134 9.6 15.2 57.1

Total 0'-10' 16-46 3.3 5.2 34.8

Total 10'-20' 19-43 3.1 4.9 44.2

Total Paint 18-53 3.8 6.0 34.0

Total non-Paint 68-170 12.1 19.3 55.0

Total non-Close 75-199 14.2 22.6 50.5

ALL FgA 86-223 15.9 25.3 50.0

44 |

2011–12 Tar Heels

reggie Bullock #35 6'7" • 205 • Kinston, NC • Sophomore 2010–11 Minutes: SF: 90.2% Sg: 8.5% PF: 1.3%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSAs a freshman, Bullock showed flashes of being a versatile offensive threat. He scored 34% of his hoops on layups and dunks—generally in transition—a percentage that compares favorably to Wayne Ellington’s sophomore (32%) and junior years (38%) (and is clearly higher than UNC’s pure jump-shooting wings like Graves, McDonald, and Miller). He also converted his close attempts at an excellent rate of 67.7%. Only 5 of his 31 close attempts were created off the dribble (including two for breakaway dunks vs. Clemson caused by strong overplays of the passing lanes). Like McDonald, an area where Bullock could improve is creating his own offense at the rim via the dribble. While largely inefficient, Bullock showed glimpses of a floater (6-22) and a midrange game (6-21 from 10–20 feet). Early in the season (pre-knee flare-ups), his floater looked particularly promising. Still, Bullock was too dependent on the three-pointer as a freshman: Of his 169 field-goal attempts, 98 (or 58%) were from behind the arc. That’s too many—Ellington never exceeded 47%—especially for someone who shot below 30% from that range. Bullock had a tendency, both in transition and in the halfcourt, to slide into the corners for spot-up threes. From the left corner, he made a solid 35.7% (10-28). But from the right corner, he connected on just 14.3% (3-21). Interestingly, McDonald—who also showed a proclivity for corner threes—had similar splits: 36.8% (14-38) from the left corner, 20.8% (5-24) from the right corner. As a team, the Heels shot 40.6% from the left corner and 27.4% from the right, on a perfectly symmetrical 106 attempts from each.

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSAnother similarity between Bullock and McDonald last season was that both struggled against top-50 opposition. Bullock averaged 7.2 points, shooting 40.7% from the field and 33.3% from behind the arc in 17 games versus teams ranked outside the Pomeroy top 50. In 10 top-50 games, those numbers plummeted to 4.3, 28.6%, and 21.9%. His assist-to-turnover ratio was 0.33 against the top 50, and 2.00 outside of it. From a WORP/35 standpoint, Bullock became less and less effective as the season progressed (0.83 in November, 0.78 in December, 0.47 in January, -0.33 in February). Some of that was due to the uptick in competition level, but much was likely a result of the deteriorating condition of Bullock’s knee. Provided he can remain healthy, Bullock will have every opportunity to prove that he can be a major contributor against opponents of any caliber especially with the injury to McDonald.

DEFENSIVE BOX SCORE OBSERVATIONSAfter a slow defensive start to his career (Stop% of 48.1% over the first quarter of the season), Bullock really turned things on (Stop% of 66.1% and 66.3% in quarters 2 and 3) before missing the final quarter of the season with his knee injury. Only Henson and Zeller had better cumulative Stop% in quarters 2 and 3 than Bullock. Many of his early season errors were typical freshman mistakes: losing his man in transition, mistiming a help rotation, or poor defensive spacing in general. The physical gifts were evident from the first game—good length, lateral quickness, and the willingness to get in a stance, move his feet, and guard somebody. With a healthy knee, Bullock can be an elite wing defender in Carolina’s system. The big question is, with McDonald’s injury, how will Bullock fare if asked to guard smaller, quicker opposing twos (he guarded threes almost exclusively as a freshman)?

| 45

2011–12 Tar Heels

reggie Bullock #35


FR 14.5 6.1 2.8 0.6 0.7 0.1 0.5 1.23 36.7 56.5 29.6 13.3 0.38

Projected SO 21.0 9.3 4.3 1.1 1.1 0.2 1.0 1.17 42.5 66.7 35.7 14.8 0.62


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 49.6 29.2 56.3 2.66 5.52 0.10 14.9 60.8 -3.4


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Will Graves (2009–10, JR, UNC)

MOST STATISTICALLY SIMILAR ACC SEASON (FRESHMEN)Anthony Morrow (2004–05, GA Tech)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Will Graves (2009–10, JR)

CAREER STATiSTiCS


DATE OPP RESULT Min Fg FgA 3PM 3PA FTM FTA PTS OFF DEF TOT AST STL BLK TO PF11/12 Lipscomb W 15 5 11 2 4 0 0 12 2 2 4 1 0 0 0 011/18 Hofstra (N) W 13 2 4 2 3 0 0 6 0 1 1 2 1 0 0 111/19 Minnesota (N) L 19 4 9 2 6 1 2 11 0 1 1 0 1 0 1 111/21 Vanderbilt (N) L 15 4 6 2 2 0 0 10 1 1 2 0 1 0 1 111/23 North Carolina-Asheville W DID NOT PLAY11/28 College of Charleston W 12 3 6 0 0 1 2 7 1 0 1 0 0 0 0 011/30 @ Illinois L 13 2 4 1 3 0 1 5 0 1 1 0 1 0 3 112/4 Kentucky W 16 0 5 0 3 1 2 1 0 3 3 0 1 0 0 212/8 @ Evansville W 10 3 9 2 5 1 2 9 2 2 4 0 0 1 0 212/11 Long Beach State W 10 3 5 2 4 0 0 8 0 1 1 0 0 0 0 012/18 Texas L 9 1 2 0 0 0 0 2 0 2 2 0 0 0 0 112/21 William & Mary W 20 4 8 1 5 2 4 11 2 3 5 3 1 0 1 112/28 @ Rutgers W 16 2 7 2 7 0 0 6 1 2 3 3 1 1 0 0

1/2 Saint Francis (PA) W 17 5 8 1 4 1 1 12 1 4 5 2 0 0 0 01/8 @ Virginia W 14 1 3 1 2 1 2 4 0 5 5 0 0 0 0 21/13 Virginia Tech W 10 1 8 0 5 0 0 2 0 1 1 0 0 0 1 01/16 @ Georgia Tech L 15 1 5 0 3 0 0 2 1 4 5 0 0 0 2 11/18 Clemson W 18 6 10 3 7 3 4 18 2 3 5 2 2 0 1 11/26 @ Miami (FL) W 23 3 8 2 5 0 0 8 3 2 5 0 2 0 1 01/29 North Carolina State W 16 0 5 0 3 0 0 0 1 3 4 1 1 0 0 12/1 @ Boston College W 17 6 9 4 7 0 0 16 1 3 4 1 1 1 1 02/6 Florida State W 13 1 5 1 4 0 0 3 0 1 1 0 0 0 0 12/9 @ Duke L 17 0 5 0 4 0 0 0 1 4 5 0 2 0 0 42/12 @ Clemson W 14 0 3 0 2 0 0 0 0 1 1 0 1 0 0 22/15 Wake Forest W 14 2 7 1 6 0 0 5 1 3 4 0 0 0 0 12/19 Boston College W 17 1 4 0 1 0 0 2 1 1 2 0 0 0 1 12/23 @ North Carolina State W 12 1 5 0 1 2 3 4 1 0 1 1 0 0 0 02/27 Maryland W 7 1 8 0 2 0 0 2 0 0 0 0 2 0 0 13/2 @ Florida State W DID NOT PLAY3/5 Duke W DID NOT PLAY3/11 Miami (FL) (N) W DID NOT PLAY3/12 Clemson (N) W DID NOT PLAY3/13 Duke (N) L DID NOT PLAY3/18 Long Island University (N) W DID NOT PLAY3/20 Washington (N) W DID NOT PLAY3/25 Marquette (N) W DID NOT PLAY3/27 Kentucky (N) L DID NOT PLAY


46 |

2011–12 Tar Heels

reggie Bullock #35



WORP / 352

All games 27 14.5 6.1 2.8 0.6 0.7 0.1 0.5 0.9 1.23 36.7 56.5 29.6 45.3 46.1 13.6 19.1 5.9 13.6 13.3 0.38/ 40 Min.1 – 40.0 15.7 7.2 1.5 1.8 0.3 1.3 2.3 1.23 36.7 56.5 29.6 45.3 46.1 13.6 19.1 5.9 13.6 13.3 0.98nov. 6 14.5 8.5 1.7 0.5 0.7 0.0 0.8 0.7 0.60 50.0 40.0 50.0 61.3 60.2 12.5 21.0 4.8 6.8 17.4 0.83Dec. 6 13.5 6.2 3.0 1.0 0.5 0.3 0.2 1.0 6.00 36.1 50.0 29.2 45.8 46.5 22.2 20.2 6.5 15.8 17.4 0.78Jan. 7 16.1 6.6 4.3 0.7 0.7 0.0 0.7 0.7 1.00 36.2 71.4 24.1 43.6 45.7 14.9 19.1 7.4 19.2 13.7 0.47Feb. 8 13.9 4.0 2.3 0.3 0.8 0.1 0.3 1.3 1.00 26.1 66.7 22.2 32.6 33.7 6.5 17.0 4.7 11.5 6.7 -0.33Mar. – – – – – – – – – – – – – – – – – – – – –ACC 14 14.8 4.7 3.1 0.4 0.8 0.1 0.5 1.1 0.71 28.2 66.7 23.1 35.3 37.0 10.6 17.8 6.1 14.8 8.5 -0.15non-Conf 13 14.2 7.7 2.5 0.8 0.5 0.1 0.5 0.8 1.83 45.2 50.0 37.0 55.4 55.2 16.7 20.6 5.7 12.3 18.6 0.95Regular 27 14.5 6.1 2.8 0.6 0.7 0.1 0.5 0.9 1.23 36.7 56.5 29.6 45.3 46.1 13.6 19.1 5.9 13.6 13.3 0.38Post – – – – – – – – – – – – – – – – – – – – –vs. Top 25 6 14.5 4.3 2.8 0.3 1.2 0.0 0.7 1.8 0.50 31.0 57.1 21.1 37.9 40.2 24.1 16.0 3.6 15.9 9.1 -0.08vs. 26–50 4 11.3 4.3 1.0 0.0 0.8 0.0 0.5 0.8 0.00 25.9 – 23.1 31.5 31.5 0.0 24.1 2.3 6.6 2.7 -0.61vs. 51–100 11 15.5 6.2 2.9 0.5 0.5 0.2 0.5 0.5 1.00 37.9 55.6 33.3 47.7 48.4 13.6 17.3 6.1 12.7 12.9 0.36vs. 100+ 6 14.8 9.2 3.8 1.3 0.3 0.2 0.2 0.8 8.00 44.7 57.1 33.3 54.3 54.6 14.9 23.2 9.4 16.6 23.6 1.55Home 14 13.9 6.1 2.7 0.6 0.5 0.0 0.3 0.7 2.25 35.9 61.5 22.9 41.9 43.3 14.1 20.5 6.0 13.7 13.0 0.33Road 10 15.1 5.4 3.4 0.5 0.8 0.3 0.7 1.2 0.71 32.8 50.0 30.8 43.1 43.7 13.8 17.6 7.0 15.3 11.8 0.22neutral 3 15.7 9.0 1.3 0.7 1.0 0.0 0.7 1.0 1.00 52.6 50.0 54.5 68.4 67.7 10.5 18.2 2.2 6.3 19.5 1.15Wins 21 14.5 6.5 2.9 0.8 0.6 0.1 0.3 0.8 2.67 36.2 60.0 30.0 44.9 46.1 14.5 19.8 6.6 13.3 15.1 0.58Losses 6 14.7 5.0 2.7 0.0 0.8 0.0 1.2 1.5 0.00 38.7 33.3 27.8 46.8 46.3 9.7 16.7 3.6 14.6 7.0 -0.32






Def. Rat.+1

On-Court Def. Eff.

All: Total 399 35-70.5 7-24 12-18 49.6 54.6 56.3 89 26.5 1 55 13.6 2.5 0.8 60.8 94.0 101.0 97.6

Per 40 40.0 3.5-7.1 0.7-2.4 1.2-1.8 49.6 54.6 56.3 8.9 2.7 0.10 5.5 13.6 2.5 0.8 60.8 94.0 101.0 97.6

ACC: Total 209 13-31.5 2.5-14.5 9-13 41.3 45.2 49.8 37.5 15 0 30 14.8 3.0 0.5 67.1 93.6 103.4 99.7

Per 40 40.0 2.5-6.0 0.5-2.8 1.7-2.5 41.3 45.2 49.8 7.2 2.9 0.00 5.7 14.8 3.0 0.5 67.1 93.6 103.4 99.7

SHOT CREATION

Assisted by: Marshall Unasst. Drew ii Strickland Henson Barnes McDonald Knox Watts Bullock Others Total

# of Fg 20 19 8 4 3 3 2 2 0 0 1 62

% of Total Fg 32.3 30.7 12.9 6.5 4.8 4.8 3.2 3.2 0.0 0.0 1.6 100.0

+/– STATISTICS




On-Court 398.9 72.5 +10.7 108.2 49.2 37.1 34.8 16.3 97.5 49.8 29.7 69.7 23.1

Off-Court 1086.1 72.3 +11.7 105.8 49.1 38.2 38.1 19.1 94.1 45.0 23.2 69.9 18.5

Difference1 – +0.2 -1.0 +2.4 +0.1 -1.1 -3.3 +2.8 -3.4 -4.8 -6.5 -0.2 +4.6

As 3 (SF) 359.7 72.2 +9.8 107.9 49.2 37.4 35.2 16.9 98.1 51.2 27.1 69.6 23.6

As 2 (Sg) 34.0 72.4 +24.2 115.9 50.9 37.5 36.4 11.1 91.7 36.1 35.2 70.0 16.7




| 47

2011–12 Tar Heels

reggie Bullock #35


37.0%10-27

33.3%1-3

N/A0-0

100.0%1-1

0.0%0-1

N/A0-0

33.3%2-6

N/A0-0

0.0%0-3

25.0%1-4

33.3%2-6

N/A0-0

14.3%3-21

35.7%10-28

33.3%1-3

31.3%5-16

63.2%12-19

100.0%2-2

70.0%7-10

26.3%5-19

TURNOVER STATISTICS


Bad pass 9 0.90 6.1







Total 13 1.30 8.8




Open 14-17 82.4 1-11 9.1 2.8 55.4


Contested 7-27 25.9 2-9 22.2 3.6 27.8


Total 33-71 46.5 29-98 29.6 16.9 45.3

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

0.70 0.40 0.10 0.80 0.40 2.01 1.70 0.90 7.5 15.5 4.4 0.20


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

1.10 1.00 0.40 2.41 5.82 34.5 1.22 4.31 34.9 44.2 20.9



Total Close 21-31 3.1 5.1 67.7


Total Mid-Range 4-15 1.5 2.4 26.7

Total 3-Pt. 29-98 9.8 16.0 44.4

Total 0'-10' 27-50 5.0 8.2 54.0

Total 10'-20' 6-21 2.1 3.4 28.6

Total Paint 9-56 5.6 9.1 51.8

Total non-Paint 33-113 11.3 18.5 42.0

Total non-Close 41-138 13.8 22.5 40.2

ALL FgA 62-169 16.9 27.6 45.3

48 |

2011–12 Tar Heels

Justin Watts #24 6'5" • 210 • Durham, NC • Senior 2010–11 Minutes: PF: 85.6% SF: 12.6% C: 1.8%

OFFENSIVE HOT SPOTS AND GO-TO SHOTSWatts’ primary offensive contribution last season didn’t involve shooting or scoring, but rather spreading the court and moving the ball as a face-up four. A very solid screener as well, Watts provided myriad intangible offensive benefits, especially when paired in the frontcourt with Zeller who best utilized the floor spacing that Watts helped to provide. As a scorer, however, Watts didn’t bring a whole lot to the table. He made just 47.4% of his close attempts (9-19), generally giving up several inches in the paint as an undersized four. Of his 19 close shots, 14 came via offensive rebounds and second-chance attempts, including 10 tips (of which he made just four). He worked hard on the offensive glass and kept plenty of balls alive; just don’t expect him to convert those chances into hoops at an overwhelming rate. The highest percentage of Watts’ field-goal attempts actually came from behind the arc. He shot an acceptable 33.3% on 21 deep tries; a sizzling 7-of-12 (58.3%) from the deep corners and 0-of-9 from the top of key and wings. While an admittedly small sample size, last year’s data suggest that Watts would be best served to spot up in the corners. Certainly not a true post player, Watts made just 3-of-12 shots from 5–10 feet via a combination of post moves (2-5 on jump hooks, 0-1 on turnaround jumpers) and floaters (1-6). He knocked down his only two catch-and-shoot midrange attempts, his only makes in four chances from 10–20 feet. Watts knows his offensive role is to space the floor, move the ball, set solid screens, and make life easier for the big scorers. He performs that role very well, and can also throw in an occasional hoop in a variety of ways: be it a corner three, a transition dunk, or a tip-in.

STATISTICAL TRENDS AND BOX SCORE OBSERVATIONSWatts’ role was reduced dramatically over the season’s final two months. After averaging 12.1 minutes from November through January, he played just 6.1 per game in February and March, and just 5.0 in seven postseason contests. Even when he played in February and March, he rarely shot—after attempting 8.5 field goals per 40 minutes through January, he tried just 4.1 per 40 in the final 16 games. Watts definitely understood his role down the stretch: play hard on both ends, don’t make any mistakes, and give Henson or Barnes a brief rest without hurting the team. Based on the +/- data, Watts did an admirable job in this capacity: Carolina was +25 in his 124 minutes against top 50 teams, and +14 in his 129 ACC minutes. Even against Kentucky in the NCAA Tournament, when Henson’s foul trouble dictated a longer-than-usual first-half stint for Watts, Carolina won 18–12 in his 5.8 minutes on the floor. These small sample size plus-minuses don’t necessarily prove that Watts was valuable; they do, however, help to demonstrate that he wasn’t a liability during his minutes. The 2011–12 version of Watts, a hard-working, versatile senior who takes very few bad shots and makes even fewer mistakes, should be a valuable bench piece for Roy Williams to have at his disposal.

DEFENSIVE BOX SCORE OBSERVATIONSTrying to box out bigger players, Watts got off to a rough start as a defensive rebounder. Through 10 games, he had allowed 13 offensive rebounds while grabbing only 12 defensive rebounds himself. Over the final 27 games, though, that ratio improved to 30 defensive rebounds vs. 15 offensive boards allowed. If that can continue, Watts will be adequate as an undersized defensive four, especially against perimeter-oriented match-ups.

| 49

2011–12 Tar Heels

Justin Watts #24


FR 3.1 0.7 0.7 0.2 0.1 0.1 0.3 0.56 24.2 42.9 0.0 3.3 -0.15

SO 6.2 1.7 0.8 0.8 0.2 0.2 0.7 1.20 40.5 42.9 44.4 11.3 0.08

JR 9.2 1.9 1.9 0.5 0.1 0.1 0.4 1.20 37.5 53.3 33.3 8.6 -0.14

Projected SR 6.0 1.5 1.3 0.3 0.1 0.1 0.2 1.67 40.0 55.6 33.3 9.5 -0.09


ClassFg% All.

3Pt% All.

TS% All.

TOF / 40

Defl. / 40


Def. On-C/Off-C

FR 44.6 51.5 62.1 1.84 2.30 0.00 12.0 50.6 -1.1

SO 48.9 41.2 59.2 2.26 4.51 0.00 8.8 46.0 +7.3

JR 43.5 32.3 51.7 1.88 3.26 0.38 13.9 52.3 +2.7


MOST STATISTICALLY SIMILAR ACC SEASON (ALL CLASSES)Jordan Collins (2003–04, JR, NCSU)

MOST STATISTICALLY SIMILAR ACC SEASON (jUNIORS)Jordan Collins (2003–04, NCSU)

MOST STATISTICALLY SIMILAR UNC SEASON (ALL CLASSES)Will Johnson (2002–03, SR)

CAREER STATiSTiCS



1/2 Saint Francis (PA) W 13 2 5 1 2 1 2 6 3 2 5 2 1 0 0 31/8 @ Virginia W 16 0 3 0 1 1 2 1 1 3 4 0 0 0 0 11/13 Virginia Tech W 13 0 3 0 1 1 2 1 3 3 6 2 0 0 1 11/16 @ Georgia Tech L 16 0 1 0 0 2 2 2 0 2 2 0 0 1 1 21/18 Clemson W 8 0 1 0 1 1 2 1 0 3 3 1 0 0 0 11/26 @ Miami (FL) W DID NOT PLAY1/29 North Carolina State W DID NOT PLAY2/1 @ Boston College W DID NOT PLAY2/6 Florida State W 7 0 0 0 0 0 0 0 0 2 2 1 0 0 0 12/9 @ Duke L 7 0 2 0 1 0 0 0 0 1 1 0 0 0 0 12/12 @ Clemson W 7 0 0 0 0 0 0 0 0 1 1 0 1 0 1 02/15 Wake Forest W 11 0 0 0 0 0 0 0 0 1 1 1 0 0 0 02/19 Boston College W 4 0 1 0 1 0 0 0 0 0 0 0 0 0 0 12/23 @ North Carolina State W 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 02/27 Maryland W 8 0 1 0 0 0 0 0 1 2 3 1 0 0 0 13/2 @ Florida State W 8 0 1 0 0 0 0 0 0 0 0 2 0 0 2 13/5 Duke W 8 1 2 0 0 0 0 2 1 1 2 0 0 0 0 03/11 Miami (FL) (N) W 5 1 1 1 1 0 0 3 0 0 0 0 0 0 1 13/12 Clemson (N) W 5 0 0 0 0 1 2 1 0 0 0 0 0 0 0 03/13 Duke (N) L 7 0 0 0 0 0 0 0 1 1 2 0 0 0 1 23/18 Long Island University (N) W 7 1 1 0 0 0 0 2 1 2 3 0 0 0 1 03/20 Washington (N) W 4 0 1 0 0 0 0 0 1 0 1 0 0 0 0 03/25 Marquette (N) W 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 03/27 Kentucky (N) L 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0


50 |

2011–12 Tar Heels

Justin Watts #24



WORP / 352

All games 34 9.2 1.9 1.9 0.5 0.1 0.1 0.4 0.9 1.20 37.5 53.3 33.3 43.8 46.3 53.6 11.2 7.4 13.2 8.6 -0.14/ 40 Min.1 – 40.0 7.7 7.6 1.8 0.2 0.5 1.8 3.5 1.20 37.5 53.3 33.3 43.8 46.3 53.6 11.2 7.4 13.2 8.6 -0.57nov. 7 12.3 3.3 2.1 0.7 0.0 0.3 0.6 1.0 1.25 47.4 44.4 16.7 50.0 49.4 47.4 12.9 4.9 12.6 9.8 -0.08Dec. 6 10.8 3.8 2.2 0.5 0.0 0.2 0.5 1.0 1.00 50.0 55.6 57.1 64.3 62.9 64.3 13.1 9.7 10.6 14.0 0.28Jan. 5 13.2 2.2 4.0 1.0 0.2 0.2 0.4 1.6 2.50 15.4 60.0 20.0 19.2 31.0 76.9 12.6 11.1 19.4 9.8 -0.09Feb. 7 6.6 0.0 1.1 0.4 0.1 0.0 0.1 0.6 3.00 0.0 – 0.0 0.0 0.0 0.0 5.3 2.3 15.0 2.6 -0.40Mar. 9 5.7 0.9 0.9 0.2 0.0 0.0 0.6 0.4 0.40 50.0 50.0 100.0 58.3 57.6 33.3 9.5 8.2 7.7 3.9 -0.29ACC 16 8.3 0.7 1.7 0.5 0.1 0.1 0.4 0.8 1.14 12.5 60.0 16.7 15.6 26.5 62.5 9.0 5.6 14.9 4.0 -0.42non-Conf 18 10.1 3.0 2.1 0.6 0.1 0.2 0.4 0.9 1.25 47.5 50.0 40.0 55.0 54.5 50.0 12.8 8.7 11.9 12.0 0.11Regular 27 10.3 2.2 2.1 0.7 0.1 0.1 0.4 1.0 1.50 35.9 53.6 30.0 41.5 44.5 52.8 11.7 7.2 13.8 9.2 -0.12Post 7 5.0 0.9 0.9 0.0 0.0 0.0 0.4 0.4 0.00 66.7 50.0 100.0 83.3 76.0 66.7 7.4 9.0 8.5 4.4 -0.24vs. Top 25 11 7.5 1.5 1.5 0.5 0.1 0.1 0.2 0.5 2.50 35.7 57.1 33.3 42.9 46.2 50.0 9.8 7.6 11.9 9.9 -0.05vs. 26–50 6 7.3 0.2 2.2 1.0 0.0 0.0 0.7 0.8 1.50 0.0 50.0 0.0 0.0 7.2 33.3 11.8 9.6 20.2 3.5 -0.40vs. 51–100 9 10.0 2.3 1.3 0.1 0.0 0.2 0.4 1.3 0.25 33.3 57.1 37.5 43.3 48.5 93.3 10.8 4.7 8.7 6.3 -0.33vs. 100+ 8 12.1 3.4 2.9 0.8 0.1 0.1 0.6 0.8 1.20 52.4 42.9 33.3 57.1 55.5 33.3 12.4 8.7 15.2 12.1 0.13Home 15 10.2 1.7 2.5 0.7 0.1 0.1 0.3 0.9 2.20 32.1 45.5 27.3 37.5 39.1 39.3 10.7 9.6 15.5 8.9 -0.14Road 9 10.2 1.9 1.3 0.6 0.1 0.1 0.6 0.9 1.00 26.7 60.0 42.9 36.7 43.0 66.7 11.1 2.3 10.7 5.9 -0.37neutral 10 6.9 2.2 1.4 0.2 0.0 0.2 0.5 0.7 0.40 61.5 55.6 33.3 65.4 63.7 69.2 12.6 9.1 11.4 11.7 0.05Wins 26 9.1 2.0 1.9 0.6 0.1 0.1 0.4 0.7 1.36 42.9 45.8 35.7 48.8 48.7 57.1 11.4 7.6 13.8 9.7 -0.07Losses 8 9.8 1.6 1.8 0.4 0.0 0.3 0.5 1.3 0.75 21.4 83.3 28.6 28.6 38.6 42.9 10.7 6.7 11.4 5.4 -0.39






Def. Rat.+1

On-Court Def. Eff.

All: Total 319 42-96.5 10.5-32.5 18-26 43.5 49.0 51.7 112.5 15 3 26 13.2 0.3 1.3 52.3 97.3 97.6 92.9

Per 40 40.0 5.3-12.1 1.3-4.1 2.3-3.3 43.5 49.0 51.7 14.1 1.9 0.38 3.3 13.2 0.3 1.3 52.3 97.3 97.6 92.9

ACC: Total 129 14-36 2-10 4-6 38.9 41.7 43.8 34 8.5 3 10 14.9 0.5 0.8 62.0 94.8 102.0 88.0

Per 40 40.0 4.3-11.2 0.6-3.1 1.2-1.9 38.9 41.7 43.8 10.5 2.6 0.93 3.1 14.9 0.5 0.8 62.0 94.8 102.0 88.0

SHOT CREATION

Assisted by: Unassisted Strickland Bullock Marshall Drew ii McDonald Zeller Knox Henson Barnes Others Total

# of Fg 9 5 3 2 1 1 0 0 0 0 0 21

% of Total Fg 42.9 23.8 14.3 9.5 4.8 4.8 0.0 0.0 0.0 0.0 0.0 100.0

+/– STATISTICS




On-Court 319.2 73.8 +19.8 112.7 51.3 40.7 34.2 15.3 92.9 48.6 23.4 73.2 21.8

Off-Court 1165.8 72.0 +9.1 104.7 48.5 37.1 37.9 19.1 95.6 45.0 23.2 69.9 18.5

Difference1 – +1.8 +10.7 +8.0 +2.8 +3.6 -3.7 +3.8 +2.7 -3.6 -0.2 +3.3 +3.3

As 4 (PF) 273.3 74.2 +22.5 113.5 52.1 41.1 33.2 15.2 91.0 48.9 24.0 75.4 22.2

As 3 (SF) 40.2 69.1 +1.5 97.9 41.3 41.3 38.1 17.0 96.4 43.9 18.2 65.1 20.4




| 51

2011–12 Tar Heels

Justin Watts #24


0.0%0-2

0.0%0-3

N/A0-0

N/A0-0

N/A0-0

N/A0-0

N/A0-0

50.0%1-2

N/A0-0

N/A0-0

50.0%1-2

N/A0-0

44.4%4-9

100.0%3-3

25.0%2-8

25.0%1-4

56.3%9-16

0.0%0-1

0.0%0-2

0.0%0-4

TURNOVER STATISTICS


Bad pass 7 0.88 9.1







Total 15 1.88 19.6




Open 6-6 100.0 1-6 16.7 1.5 62.5


Contested 3-14 21.4 0-1 0.0 1.9 20.0


Total 14-35 40.0 7-21 33.3 7.0 43.8

PASSING STATISTICS

Close Asst / 40

Paint Asst / 40

Midrange Asst / 40

3-Pt. Asst / 40

FT Asst / 40

Asst. / 40


Pass TO / 40 (PTO)

Asst. Rate (%)

Pass TO (%)

% Open Created

Open FgA / 40

0.88 0.38 0.00 1.13 0.13 2.38 2.13 0.88 9.0 15.6 27.0 1.3


Pot. Paint / 40

Pot. Midrange / 40

Pot. 3-Pt. / 40


Entry Passes / 40

Entry Success %

Entry Fail %

Entry Reset %

1.00 1.00 0.25 2.51 5.64 42.2 1.14 2.63 42.9 42.9 14.3



Total Close 9-19 2.4 3.9 47.4


Total Mid-Range 1-2 0.3 0.4 50.0

Total 3-Pt. 7-21 2.6 4.3 50.0

Total 0'-10' 12-31 3.9 6.3 38.7

Total 10'-20' 2-4 0.5 0.8 50.0

Total Paint 13-33 4.1 6.7 39.4

Total non-Paint 8-23 2.9 4.7 50.0

Total non-Close 12-37 4.6 7.5 41.9

ALL FgA 21-56 7.0 11.4 43.8

52 | www.maplestreetpress.com

TiP-off TriviaWant to impress your Tar Heel friends and co-workers?

Want to win free beers at the bar based on your expan-sive knowledge of Carolina hoops? The Tip-Off trivia page will help fill your brain with even more esoteric nuggets about your favorite college hoops program.

SECTION IKeeping with the theme of an article in last year’s MSP Tar Heel Tip-Off, the first two questions deal with career UNC scoring leaders by uniform number and first letter of their last name. This section contains Sporcle.com-type questions—so put yourself on the clock to answer as many as possible in a given amount of time.1. Name UNC’s scoring leader by uniform number for

ACC-era players (1954–11). One eligible number (i.e., not containing the digits 6, 7, 8, or 9) has never been worn by a Tar Heel. All others have (including both #0 and #00).

2. Name UNC’s scoring leaders from A–Z for ACC-era players. Three letters are blank since Carolina has never had a player whose last name starts with that letter.

SECTION IIThis section contains more traditional trivia questions—that is, there aren’t 20-plus answers to a single question. 3. Only one Carolina team has featured six double-digit

scorers in the same season. Name the season and the six Tar Heels who scored 10-plus points per game that year.

4. Three jersey numbers have been worn by five different Tar Heels who scored at least 1,000 career points. Provide the numbers and the quintet of 1,000-point scorers that donned each.

5. Five Carolina uniform numbers have been honored in the rafters for three different players. List the thrice-honored numbers, as well as the Tar Heels who wore them.

6. In 2009, Ty Lawson set a UNC (and ACC) record with his 3.48 assist-to-turnover ratio. Which Tar Heel holds

the dubious distinction of having the lowest single-season A:TO in Carolina history (for seasons with at least 10 minutes per game)?

7. Six different times (by five different Heels), a UNC player has made at least 85% of his free throws and 40% of his three-pointers in the same season (with at least 50 attempts from each location). List the members of this prestigious group of sharpshooters.

8. In the ACC era, which Tar Heel has scored the most career points without ever being selected to any of the All-ACC teams? Excluding active players, which member of an All-ACC team has scored the fewest career points at Carolina?

ANSWERS:Section I:1. #0: Holley ( 24 points), #00: Montross (1,636), #1: Ginyard (874—M. Scott

had 873), #2: Felton (1,260), #3: Sh. Williams (1,397), #4: Frasor (402), #5: Lawson (1,375), #10: Rosenbluth (2,045), #11: Larry Brown (661), #12: Ford (2,290), #13: Okulaja (1,254), #14: Lebo (1,567), #15: Carter (1,267), #20: Bucknall (974), #21: J. Williams (1,626), #22: Lewis (1,836), #23: M. Jordan (1,788), #24: W. Davis (1,863), #25: Capel (1,447), #30: Wood (2,015), #31: O’Koren (1,765), #32: McCants (1,721), #33: C. Scott (2,007), #34: Lynch (1,747), #35: Brennan (1,332), #40: H. Davis (1,615), #41: Perkins (2,145), #42: Daugherty (1,912), #43: R. Clark (1,339), #44: L. Miller (1,982), #45: LaGarde (1,007), #50: Hansbrough (2,872), #51: Makkonen (20), #52: Worthy (1,219), #53: never worn, #54: Martin (670), #55: Wenstrom (194)

2. A: Bill Akins (6 points), B: Brennan (1,332), C: Billy Cunningham (1,709), D: Daugherty (1,912), E: Ellington (1,694), F: Ford (2,290), G: D. Green (1,368), H: Hansbrough (2,872), I: no players, J: A. Jamison (1,974), K: Kupchak (1,611), L: Lewis (1,836), M: L. Miller (1,982), N: Noel (880), O: O’Koren (1,765), P: Perkins (2,145), Q: Quigg (594), R: Rosenbluth (2,045), S: C. Scott (2,007), T: Thompson (1,414), U: no players, V: Vayda (1,187), W: Wood (2,015), X: no players, Y: Yonakor (597), Z: Zeller (880)

Section II:3. 1988–89: Reid (15.9), Madden (14.7), Bucknall (13.1), Lebo (12.2), Fox

(11.5), Sc. Williams (11.4)4. #21: Lifson, Kupchak, D. Williams, J. Williams, Thompson; #22: Larese, Lewis,

Karl, Madden, Ellington; #42: Daugherty, Sc. Williams, Stackhouse, Lang, May5. #22: Larese, Lewis, Ellington; #30: Wood, K. Smith, Wallace; #34: B. Jones, Reid,

Lynch; #35: Brennan, Doug Moe, McAdoo; #42: Daugherty, Stackhouse, May6. Kris Lang (0.19 in 2000)—closely followed by Stepheson (0.20 in 2008)

and Zeller (0.21 in 2010)7. Jeff Lebo (1987, 1988), Ranzino Smith (1988), Shammond Williams (1998),

Jason Capel (1999), Danny Green (2009)8. Scott Williams with 1,508 (followed by Kris Lang with 1,339); Brandan

Wright (2nd team in ’07) with 545, followed by Jim Hudock (2nd team in 1962) with 558 and Bob McAdoo (1st team in 1972) with 604

Test your heels knowledgeby Adrian Atkinson

2011-12 north carolina basketball preview

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