Comparing 2017-18 Preseason Rankings

Five teams received first place votes in either the preseason AP or coach’s poll last year; Villanova was not one of those teams. But Ken Pomeroy's computer pegged Villanova as the best team in the nation in the preseason. Perhaps this is a reminder to poll voters to avoid group-think and not be afraid to stray from the consensus. If Ken was best at the very top last year, John Gasaway had the most accurate Top 50 last year. And for the third time in four year's Sports Illustrated's projection of all 351 teams proved to be the most accurate for the full rankings.

Relative to the baseline (simply running the final Pomeroy rankings from the prior year), David Hess of Team Rankings, Ken Pomeroy, and John Gasaway all improved the average team's ranking by 9.5 to 9.9 slots. Clearly, their model's moved the needle quite far in the correct direction. The SI model, a combination of effort from me (Dan Hanner), Chris Johnson, and Jeremy Fuchs ended up being the most accurate, improving the average team's ranking by 11.65 spots relative to simply running the prior year's final standings.

Rank, Publication (Author), Improvement over Baseline

1^st, SI (Hanner, Johnson, Fuchs), +11.65

2^nd, Team Rankings (Hess), +9.90
3^rd, Pomeroy Preseason, + 9.55
4^th, ESPN (Gasaway), +9.53
5^th, ESPN BPI, +6.70
6^th, Torvik Rank, +6.68
7^th, CBS Sports, +5.49

Full details about these numbers are found at the end of this post.

For the last seven years, I have had the honor of ranking 351 teams for either ESPN the Magazine or Sports Illustrated. I am thankful to everyone who gave me this opportunity and worked with me along the way. I still remember when my late grandfather gave me my first subscription to SI. I fell in love with the SI preview editions and it was a dream come true to contribute to these for so many years.

But it shouldn't be a huge surprise when I announce I am stepping away from this process. After I gave up my column on RealGM.com a few years ago, I have been cutting back on how much college basketball I watch. And I don't feel it is appropriate to rank all these players and teams as I continue to cut-back on how much I watch.

Our SI player level projections have always been partly based on crunching the numbers, and partly based on scouting. We would take input from coaches and beat reporters to tweak the rotations for teams (usually the minutes for players, but also sometimes ORtg and usage rates), based on what people were seeing in practice. We got to the point of even including summer tour data in our analysis. It was awesome to see the results every year, but it became almost too time consuming to include all these inputs. Once you allow the ability to make these manual scouting adjustments, you essentially add a potentially unlimited amount of work to the project.

No one has quite matched what we have done, but I also go back to the above numbers and conclude that the effort is not quite worth it. At SI we were able to improve on what Pomeroy, Gasaway, and Hess have done, but not to a huge degree. And there remains substantial noise, substantial uncertainty each year, that will probably never be overcome, due to the fact that college basketball players are at a very developmental point of their lives.

You probably assume my departure from SI is related to all the media shake-ups that have happened. I would say only barely so. Sure, if there were huge amounts of money being thrown around for basketball columns, I might stick around. But this is more about personal time than money. I was fortunate to do this as a part-time job for as long as I did.

I also don't assume this will be the end of my sports writing career. I hope that some day I have the energy to blog every day of the NCAA tournament again. I hope that I can do more to publicize sporting events the public is missing out on. (For example, I think it is a crime that more people did not hear about this year’s NCAA women’s gymnastics final. Oklahoma posted a dominant score only to see UCLA’s red-shirt senior Peng Peng Lee close the meet with back to back perfect 10’s to give UCLA the National Title by the slimmest of margins. It was easily one of the most compelling sports moments of this entire year.) There are still stories to tell, and I am not done telling them. But I am done ranking college basketball teams for now.

...If you are sad to see the player projections go away…

Please continue to follow the work of Bart Torvik. While his team model did a little worse last year, his website started to show some player projections last year, and I feel he is on the brink of greatness.

...If you want some input on doing this yourself…

I continue to make two points. First, scouting matters. Follow the twitter feeds of beat reporters. College players develop rapidly and what beat reporters see happening in practice is real.

Second, I continue to believe that the AAU data is getting more and more accurate at predicting college. Trae Young wasn’t a Top 10 recruit, but his AAU data was off the charts. He had a 32% usage rate and 130 ORtg on the AAU circuit. His success in college should not have been a surprise. Whether it translates to the NBA is another question, but when projecting college basketball, don’t overlook the statistically dominant AAU players who don’t have NBA size or quickness. If someone is efficient and high volume on the AAU circuit, they can play college basketball.

Final Details
 

And for you raw number nerds, here is how I evaluated the preseason rankings from last year.  For each set of preseason predictions, I take the difference between each team’s preseason ranking and its final Sagarin ranking, take the absolute value of each difference, and add up the total over 351 teams. (I am using the final Sagarin rating rather than the final Pomeroy ranking, since one of the things we are evaluating is Pomeroy’s system. Nonetheless, if we used the Final Pomeroy instead, the results are very similar.)

I start with a baseline which is simply the final Pomeroy ranking of teams 1-351 from 2016-2017, and I take the difference between each ranking system and this baseline in the table above.

Here was the raw data before the calculations:
 

2017-18 Preseason Predictions:

Comparing 2016-17 Preseason Rankings

Quick FYI: Our preseason SI college basketball material begins to roll out next week.

One piece of business I wanted to take care of before the rollout of this year's material, is a comparison of last year's preseason rankings.

2017 was a weird year. Every ranking system under the sun had Duke #1 and they did not live up to the hype despite immense talent. Meanwhile many of the top freshman (I’m thinking of Dennis Smith Jr. and Markelle Fultz) were great statistically, but failed to elevate their teams. Meanwhile, Ken Pomeroy added transfers to his model, but it turned out to be a year where transfers were not as impactful as usual, and Pomeroy was actually hurt by this addition in a lot of places. (See Syracuse). Finally, ESPN launched a second preseason rankings, the BPI preseason rankings, but the new system actually performed worse than the system their own ESPN Insider John Gasaway put online at the same time. Gasaway's preseason 351 crushed the BPI preseason 351.

Now, some people will look at the variance in college basketball and say that predicting the season is a fool's errand. And while there is always a lot of uncertainty, that doesn't mean that things like star ratings and AAU stats don't have some predictive power. I happen to believe that all of these rankings are useful, and together they paint a fair picture of preseason expectations. In fact, I personally consider the CBS rankings, that have fallen at the back of the pack in recent years, to be among the most important because they are based on coaching interviews and opinions, and that's an important additional data-point that many of the similar statistical systems don't catch.

As you will see below, last year our SI rankings beat CBS and ESPN again, so of the major websites, we won for a third year in a row. But the folks behind Torvik Rank actually took the top spot this year. After finishing 5th in 2016, I'm not quite convinced Torvik Rank has found the special sauce yet. I'd like to see a little more consistency first. But after last year, I highly recommend you follow them and read their work. Some of their ideas for evolving coach effects, i.e. allowing for the possibility that Thad Matta and John Thompson III got worse over time, turned out to be an important part of Torvik Rank winning last year. http://adamcwisports.blogspot.com/2015/09/t-rank-2016-preview-nuts-and-bolts.html

OK, so now onto the numbers. In the table below, I compared Sports Illustrated preseason rankings, the ESPN preseason rankings by John Gasaway, the ESPN BPI preseason rankings, the CBS Sports preseason rankings, Ken Pomeroy’s preseason rankings, David Hess’s preseason rankings, and the Torvik Rank preseason rankings.

Then I calculated the total absolute error in each ranking system. The total absolute error is found by taking the absolute value of the difference between each team’s preseason ranking and the end of season Sagarin ranking and adding up the total.

For the end of season rankings, David Hess asked me to use Sagarin instead of Pomeroy so we were not using Pomeroy to score Pomeroy, but I actually ran the numbers both ways and it didn’t make a major difference this year. The astute reader will notice that switching from a Pomeroy system to a Sagarin system did raise David Hess’s ranking in 2016, however. (I kid, I'm sure that was unintentional.)

This is certainly not the only way to compare the rankings. You may prefer to look at NCAA bids or conference titles or something else. But if you care about where every team is ranked, last year Torvik Rank finished first and Sports Illustrated finished second:

I have intentionally left John Gasaway's rankings out of the second table, since they were only available behind a paywall, but I can assure you, he did in fact finish 3rd.

Onto the new season!

Returning Minutes and Number of Players Who Were Former Top 100 Recruits

In our SI projections, we project every player and lineup to get our team projections.

But I still get lots of requests for a list of returning minutes. That isn't a direct input into our model, though it is something I can easily calculate with the roster data I have.

I cannot say that these numbers will be 100% accurate. We typically don't pull walk-on data unless those walk-ons are expected to play a lot. And we have to make some decisions about certain players. For example, this assumes Coastal Carolina's Shivaughn Wiggins will be able to return in the second semester. But it should be mostly accurate.

I also list the number of RSCI Top 100 recruits on each roster. This includes current RSCI Top 100 freshmen, former RSCI Top 100 recruits (who are now sophomores, juniors, and seniors), and players that we think were incorrectly ranked by RSCI because they changed classes.

 

Comparison of 2016 Preseason Rankings

(Quick note: This column is talking about last year's preseason rankings. The 2016-17 preseason rankings will be released soon.)

Ever since I partnered with Luke Winn at Sports Illustrated, we’ve been doing something rather unique when it comes to projecting the college basketball season. We project every D1 player, project every D1 lineup, and use those lineups to project every D1 team. I tend to think this is a unique and worthwhile exercise regardless of the accuracy, but every year we get questions about how our model has done in the past.

This year, we wrote a column that shows that we think we have had the most accurate projections for two years in a row. That said, as anyone who knows about statistics will tell you, there are often different ways to spin results. Our approach is to judge the preseason rankings based on the final ranking of teams 1-351 based on margin-of-victory (MOV). If you focus on NCAA tournament bids, NCAA wins, or conference wins, one of the other models may beat our model. But our feeling is that since the season-long MOV does a good job predicting those other outcomes, it is the best way to evaluate the rankings.

To judge the models I simply took the absolute value of the difference between each team’s preseason ranking minus the team's final MOV ranking and added up the absolute error for each model. (Taking the sum of the squared errors produced the same ordering of the various ranking systems.)

The column linked to above also highlighted some of the teams where the SI.com model did better than the other models and the teams where the SI.com model fell short. But I was asked on Twitter for a full comparison of all five preseason rankings from last year. In the interest of transparency, I list all five preseason rankings from last year below.

The first thing you will notice when you look at the full list of teams is that there were plenty of teams that surprised everyone. College basketball players are at a developmental stage of their career, and we only have a small sample of useful statistics, so not surprisingly there are positive and negative surprises every season. Still, all of the models meaningfully improved on simply running the final rankings from the previous year.

One final comment, the Final 2016 MOV 1-351 ranking is based on Ken Pomeroy’s final 2016 ranking as was on his website from April to August. I did not update this analysis after he recently made the decision to tweak his formula heading into this year.

Big Ten Player Development

I started this series to try to show the uniqueness of players like Colorado's George King and TCU's Vladamir Brodziansky. I look at the box scores every week and continue to be surprised to see a three-star bench-warmer (King) become a breakout star and to see a JUCO transfer who was not highly publicized (Brodziansky) lead his team. 

I also started this series to check in on our impact freshmen and breakout scorers lists from SI.com. For that reason, I wish I had time to show all the high major leagues we previewed at SI. But due to time constraints, I am going to wrap this up with the Big Ten. Part 6 of the series looks at every player in the Big Ten playing roughly 20% of is team's minutes when active.

Big Ten Freshmen

PPG, Min%, Poss%, ORtg, Player, Team

15.9, 82%, 27%, 98.8, *Corey Sanders, Rutgers

12.9, 54%, 29%, 115.9, *+Diamond Stone, Maryland

12.3, 70%, 24%, 108.1, +Ethan Happ, Wisconsin

12.1, 56%, 22%, 125.1, *+Thomas Bryant, Indiana

10.7, 59%, 24%, 105.5, Jordan Murphy, Minnesota

9.9, 70%, 25%, 94.6, *+JaQuan Lyle, Ohio St.

9.8, 66%, 24%, 94.1, *+Caleb Swanigan, Purdue

9.8, 59%, 19%, 103.7, *+Jalen Coleman, Illinois

9.1, 50%, 19%, 127.4, Dererk Pardon, Northwestern

9.0, 61%, 17%, 116.7, Aaron Falzon, Northwestern

8.8, 55%, 20%, 113.7, Michael Finke, Illinois

8.6, 56%, 22%, 104.5, *+Glynn Watson, Nebraska

7.8, 45%, 19%, 117.6, *+Deyonta Davis, Michigan St.

Players marked with a * were consensus Top 100 recruits. Players marked with a + were players we picked as instant impact freshmen at SI.com.

I am still kicking myself about our SI Corey Sanders projection. The stats model loved Sanders to be a major scorer in the preseason. He was Rutgers best player by far. But our SI scouting said that Sanders was attempting to be a pass-first PG. And that might have been true at first. But there is only so many times you can pass someone the ball and watch them miss a wide open shot. At some point in the season, the team just decided to give Sanders the ball and get out of the way, as seen by his team freshman record 39 points in a recent game.

And even if the scouting led us astray on Sanders, scouting has substantially improved the projections. Despite the fact that he was just a 3-star prospect, Luke Winn's personal scouting said that Ethan Happ was going to be a star. And my limited scouting moved Minnesota's Jordan Murphy up in the preseason. Murphy's recruiting rank suggested he would barely play, but I at least moved him up into Minnesota's Top 7. So even though the scouting caused us to miss on Sanders, if you look across the board at all the teams, 95% of the time scouting made our projection better. A few other notes:

-The big question for Indiana's Thomas Bryant wasn't whether or not he would score. The question was whether or not he could improve Indiana's defense. And he has delivered as Indiana's two point defense has improved from 283rd nationally to 137th. Overall, Indiana's defense has improved from 214th to 49th.

-A lot of people thought this might be the year that Northwestern finally made the NCAA tournament, but in a down year in the Big Ten, their performance isn't quite good enough. And distressingly, a lot of points will likely graduate along with Tre Demps and Alex Olah. But that's why Dererk Pardon's story is so awesome. His 28 point, 12 rebound performance soon after debuting mid-season bring a lot of hope for next year.

-Illinois' Michael Finke was a 3-star red-shirt player, the kind you might not expect that much from. In fact, among Illinois forwards he had the 6th best statistical expectation when I first ran the team's numbers this summer. But as three other big men left the team or were injured, he moved up. Finke's development is one of the only things that has gone right for Illinois this year.

 

PPG, Min%, Poss%, ORtg, Player, Team

6.7, 54%, 17%, 96.3, Jonathan Jean Laurent, Rutgers

6.7, 45%, 25%, 85.9, Kevin Dorsey, Minnesota

5.7, 56%, 20%, 84.6, Josh Reaves, Penn St.

5.1, 37%, 15%, 124.9, Nicholas Baer, Iowa

4.9, 53%, 19%, 83.8, Dupree McBrayer, Minnesota

4.9, 41%, 17%, 106.7, Jack McVeigh, Nebraska

4.5, 41%, 14%, 121.2, Michael Jacobson, Nebraska

4.2, 29%, 17%, 118.1, Ogugua Anunoby, Indiana

4.1, 46%, 16%, 86.4, *Daniel Giddens, Ohio St.

4.0, 31%, 16%, 106.5, Aaron Jordan, Illinois

3.9, 41%, 14%, 113.2, *Matt McQuaid, Michigan St.

3.8, 34%, 15%, 113.4, Ryan Cline, Purdue

3.8, 34%, 17%, 98.9, *Ed Morrow, Nebraska

3.5, 35%, 15%, 104.6, Deividas Zemgulis, Penn St.

3.1, 28%, 18%, 93.4, Charlie Thomas, Wisconsin

3.0, 35%, 15%, 90.9, Khalil Iverson, Wisconsin

2.9, 33%, 17%, 88.5, *A.J. Harris, Ohio St.

2.9, 22%, 19%, 100.4, *Victor Wagner, Michigan

2.8, 24%, 13%, 128.2, Ahmad Wagner, Iowa

2.8, 27%, 14%, 118.1, Alex Illikainen, Wisconsin

2.0, 37%, 9%, 96.3, Justin Goode, Rutgers

1.9, 25%, 12%, 111.3, Kenny Goins, Michigan St.

1.8, 22%, 18%, 82.5, Mickey Mitchell, Ohio St.

1.7, 22%, 17%, 70.5, *D.J. Williams, Illinois

1.5, 20%, 11%, 102.5, Juwan Morgan, Indiana

Four names I am not listing above: Wisconsin's Brevin Pritzl, a Top 100 recruit forced to redshirt due to injury; Ohio St.'s Austin Grandstaff, a Top 100 recruit who is transferring; Penn St.'s Mike Watkins, a 4-star prospect who was not eligible, and Rutger's Ibrahima Diallo, who played quite a bit early, but was injured.

Big Ten D3 Transfer

PPG, Min%, Poss%, ORtg, Player, Team

12.1, 70%, 18%, 132.0, Duncan Robinson, Michigan

There are not many players that transition from D3 to D1, so I can't really show you comps to explain how special Duncan Robinson's season has been. But there is no question he is very unique. The experts were right that he is a lights out three point shooter. But I'm not quite sure they were right about his ability to play in the paint. Michigan's interior defense has been pretty poor this year and teams expose Robinson inside when they can. I think Michigan views him as a stretch-four, but I think he would be better off as a true-wing. Or perhaps he will be a better interior defender and rebounder with another year of bulking up in the weight room.

Big Ten JUCO

PPG, Min%, Poss%, ORtg, Player, Team

2.1, 19%, 15%, 114.4, Jaylen Brantley, Maryland

No debuting JUCOs have played a big role in the Big Ten this year. Rutger's DeShawn Freeman and Iowa's Dale Jones might have made a bigger impact but they both got hurt.

Big Ten D1 Transfers

PPG, Min%, Poss%, ORtg, Player, Team, LastPPG, LastTeam

17.2, 72%, 24%, 123.3, Andrew White, Nebraska, 2.6, Kansas

13.1, 65%, 24%, 116.7, Robert Carter, Jr., Maryland, 11.4, Georgia Tech

10.9, 80%, 18%, 114.1, Rasheed Sulaimon, Maryland, 7.5, Duke

9.7, 51%, 25%, 110.6, Eron Harris, Michigan St., 17.2, West Virginia

7.9, 43%, 20%, 123.7, Max Bielfeldt, Indiana, 5.1, Michigan

7.9, 52%, 18%, 107.4, Omari Grier, Rutgers, 7.9, Bradley

6.5, 42%, 19%, 113.0, Trevor Thompson, Ohio St., 5.0, Virginia Tech

5.3, 45%, 18%, 114.9, Johnny Hill, Purdue, 9.6, UT Arlington

4.1, 33%, 20%, 96.3, Joey van Zegeren, Northwestern, 9.8, Virginia Tech

3.5, 56%, 14%, 88.9, Khalid Lewis, Illinois, 5.8, La Salle

1.8, 29%, 10%, 100.4, Alex Austin, Illinois, 7.0, Eastern Illinois

Andrew White was expected to be a major scorer for Nebraska, but he has done more than that. He has become the efficient superstar Nebraska needed to have a top flight offense again. (According to Kenpom.com, this is the best Nebraska offense since 2004.) Unfortunately for Cornhusker fans the defense has fallen off. The best news I can give is that Nebraska's two point defense has been better than its three point defense and free throw defense. And two point defense tends to have more predictive power going forward. (FYI: the same 2Pt/3Pt/FT defense split holds true for Wisconsin, Ohio St., and Penn St.)

I saw people in the preseason saying that Rasheed Sulaimon could average 15 to 20 PPG. And of course he could if he was the only good player on his team. The problem is that on a good team, shots are at a premium. That is why my model tries to account for the number of possessions available to each player. Sulaimon has not been a statistical disappointment; he is just one part of an offense with a lot of good players.

I am not listing Mike Thorne from Illinois due to his injury, but the play of Illinois' two guard transfers makes me think the team really does miss Tracy Abrams. Khalid Lewis and Alex Austin are just not as versatile. The losses at forward and point-guard have clearly caused Illinois to drop from a bubble team to a team that is just hanging on.

Finally Playing

This group of players were technically on the roster last year, but they didn't play meaningful minutes.

PPG, Min%, Poss%, ORtg, Player, Team

10.2, 71%, 22%, 99.2, Payton Banks, Penn St.

8.6, 57%, 22%, 102.1, Vitto Brown, Wisconsin

7.5, 79%, 13%, 115.8, Zak Showalter, Wisconsin

5.0, 50%, 14%, 102.9, Bakary Konate, Minnesota

4.8, 44%, 16%, 104.6, Julian Moore, Penn St.

4.3, 51%, 13%, 103.2, Devin Foster, Penn St.

3.7, 34%, 17%, 106.1, Javon Bess, Michigan St.

3.5, 19%, 24%, 105.2, D.J. Wilson, Michigan

3.3, 26%, 14%, 112.4, Brady Ellingson, Iowa

3.0, 27%, 17%, 107.1, Gavin Skelly, Northwestern

3.0, 36%, 13%, 101.3, Jordan Hill, Wisconsin

2.6, 18%, 20%, 111.1, Alvin Ellis III, Michigan St.

2.4, 20%, 18%, 102.2, Nick Fuller, Nebraska

2.3, 27%, 16%, 94.7, Jake Hammond, Nebraska

1.9, 23%, 19%, 69.9, Isaiah Washington, Penn St.

Banks and Brown are the leading scorers in this group, but I'm not convinced either is playing well. Banks misses way too many threes and Brown is neither the outside shooter nor defensive rebounder that Wisconsin could really use.

Returning Players

Once again, when interpreting changes in PPG, you should keep in mind the changes in pace and opponent defense. Indiana's schedule has been easier defensively this year than it was on the whole season last year. Meanwhile, Rutgers games have had over 6 more possessions than their games had on the full year last year. Obviously that is going to inflate scoring totals.
 

ChOppDef, Team, ChRawPace

3.4, Indiana, 3.2

2.6, Rutgers, 6.4

2.5, Michigan, 5.7

2.5, Minnesota, 0.2

2.4, Northwestern, 4.8

2.2, Wisconsin, 5.1

1.8, Michigan St., 4.5

1.8, Nebraska, 4.3

1.5, Purdue, 4.4

1.4, Iowa, 5.4

1.3, Illinois, 4.8

0.9, Penn St., 0.6

0.7, Ohio St., 2.2

0.6, Maryland, 2.5

Here are the biggest changes in PPG:

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

8.4, 15%, 4%, 19.8, Peter Jok, Iowa, Jr, 15.5

7.9, 52%, 1%, -6.4, +Keita Bates-Diop, Ohio St., So, 11.7

7.5, 17%, 8%, 10.7, +Brandon Taylor, Penn St., Sr, 16.6

6.0, 23%, 3%, 19.3, Tai Webster, Nebraska, Jr, 10.0

6.0, -1%, 5%, 6.6, Jarrod Uthoff, Iowa, Sr, 18.4

5.7, 17%, 5%, 7.0, Mike Williams, Rutgers, So, 12.1

5.7, 3%, 4%, 12.2, Bryn Forbes, Michigan St., Sr, 14.3

5.6, 11%, 3%, -0.1, Kendrick Nunn, Illinois, Jr, 16.7

5.2, 22%, 3%, 31.2, Dominique Uhl, Iowa, So, 7.3

4.7, 8%, 7%, -13.6, Nigel Hayes, Wisconsin, Jr, 17.1

4.7, 14%, 3%, -11.4, +Bronson Koenig, Wisconsin, Jr, 13.4

4.5, 11%, 3%, -3.1, Malcolm Hill, Illinois, Jr, 18.9

4.4, 15%, 4%, -1.1, +Shep Garner, Penn St., So, 13.6

4.4, 22%, 1%, 1.3, Maverick Morgan, Illinois, Jr, 7.0

4.1, 22%, 2%, 6.9, Anthony Clemmons, Iowa, Sr, 8.9

4.1, -2%, 4%, 9.6, Denzel Valentine, Michigan St., Sr, 18.6

Players marked with a + are players we projected as breakout scorers at SI.com. With DJ Newbill graduating, Brandon Taylor seemed like a good bet to increase his workload and he has. Taylor has increased his usage rate more than any other player in the Big Ten. Nigel Hayes has the next biggest increase in usage, but unlike Taylor, Hayes has seen his efficiency plummet now that he has a larger role in the offense.

There are not a ton of players in the Big Ten who have seen big improvements in efficiency (at least relative to the other top 5 conferences). But most of the big improvements are on Iowa. Dominique Uhl has had the biggest jump in efficiency in the Big Ten, Adam Woodbury (next table) has had the third biggest jump in efficiency in the Big Ten, Peter Jok has had the fifth biggest jump in efficiency in the Big Ten along with a big jump in usage, and Jarrod Uthoff has seen his efficiency improve slightly despite the third biggest jump in usage in the Big Ten. Even Anthony Clemmons is passing better and finishing better around the rim.

Don't let anyone tell you we should have seen this coming with the Hawkeyes because they have a veteran team. Iowa had a veteran team last year and they didn't become elite. The difference this year is that Iowa's players have put in the work and improved across the board.

I am a little nervous about Iowa's defense going forward. Their three point and free throw defense looks a little unsustainable given that they are not a dominant team at defending two point shots. But that is just my way of saying I am not sure Iowa is the #1 team in the country (the current Kenpom.com rank). Because of massive offensive improvements by multiple players, Iowa is miles better than their preseason bubble status.

 

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

 

3.7, 26%, 0%, 4.5, D.J. Foreman, Rutgers, So, 7.5

3.6, 16%, 4%, -4.8, +Nate Mason, Minnesota, So, 13.4

3.5, 20%, 3%, -1.1, Mark Donnal, Michigan, So, 7.0

3.5, 28%, 4%, -19.8, Marc Loving, Ohio St., Jr, 13.0

3.4, 5%, 2%, 8.9, Bryant McIntosh, Northwestern, So, 14.8

3.4, 26%, 0%, 40.9, P.J. Thompson, Purdue, So, 5.8

2.8, 5%, 4%, 2.8, Matt Costello, Michigan St., Sr, 9.8

2.6, -1%, 0%, 9.9, A.J. Hammons, Purdue, Sr, 14.5

2.6, 1%, -1%, 19.9, Isaac Haas, Purdue, So, 10.2

2.5, 26%, -1%, -8.8, Charles Buggs, Minnesota, Jr, 6.1

2.4, 14%, 1%, -2.2, +Kam Williams, Ohio St., So, 7.8

2.4, 16%, 1%, -6.3, +Jae'sean Tate, Ohio St., So, 11.2

2.2, 10%, 0%, 0.6, Tre Demps, Northwestern, Sr, 14.8

2.0, 11%, 0%, 12.3, Scottie Lindsey, Northwestern, So, 6.4

2.0, 17%, -2%, 19.0, Muhammad-Ali Abdur-Rahkman, Michigan, So, 6.5

1.9, 8%, -3%, 21.2, Adam Woodbury, Iowa, Sr, 8.5

1.9, 13%, 2%, 16.7, Tum Tum Nairn, Jr., Michigan St., So, 4.1

Other than Iowa, the other big jumps in efficiency are concentrated on the Purdue Boilermakers. PJ Thompson has seen the biggest jump in efficiency in the Big Ten. Thompson still isn't consistent and he and Johnny Hill have split starts this year, but Thompson's huge drop in turnover rate and improved shooting have been a great asset for the team. And Isaac Haas has improved his free throw percentage from 55% to 69% allowing him to become an efficient player.

Meanwhile Ohio St.'s Marc Loving has had the biggest drop in efficiency in the Big Ten. Loving has had to take on a larger role in his team's offense and he has struggled.

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG 

1.7, 2%, 1%, 10.6, Joey King, Minnesota, Sr, 11.4

1.6, 0%, 3%, -0.1, Vince Edwards, Purdue, So, 10.4

1.2, -4%, 2%, 10.4, Aubrey Dawkins, Michigan, So, 8.1

1.0, 10%, -1%, 9.5, Mike Gesell, Iowa, Sr, 8.4

0.9, 3%, 0%, 10.2, Derrick Walton, Jr., Michigan, Jr, 11.7

0.9, -2%, 2%, 0.6, Yogi Ferrell, Indiana, Sr, 17.3

0.5, -7%, 1%, 12.1, Benny Parker, Nebraska, Sr, 4.7

0.5, 0%, 2%, -8.9, Donovon Jack, Penn St., Sr, 4.0

0.4, 8%, 2%, -8.4, Nathan Taphorn, Northwestern, Jr, 4.5

0.4, 1%, 0%, 8.3, Jordan Dickerson, Penn St., Sr, 3.0

0.3, -2%, 0%, 16.5, Dakota Mathias, Purdue, So, 5.1

0.3, 10%, -1%, 1.1, Bishop Daniels, Rutgers, Sr, 8.7

0.2, -12%, 1%, 7.5, Shavon Shields, Nebraska, Sr, 15.7

0.0, 4%, 0%, -0.2, Sanjay Lumpkin, Northwestern, Jr, 4.4

0.0, -1%, 1%, -9.7, Nick Zeisloft, Indiana, Sr, 6.6

These tables do not include Michigan's Caris LeVert, Indiana's James Blackmon, Illinois' Leron Black, and Michigan's Spike Albrecht. Injuries have kept all of these players out of a significant number of games. LeVert and Blackmon were projected to be stars and Black was one of our projected breakout players at SI.com, meaning all three injuries were critical. The injury to Albrecht has been tempered by Derrick Walton's big improvement in efficiency this year. Walton was really hampered by injuries last year but he is back to being an efficient and effective PG this season.

I really thought heading into the season that Penn St.'s front-court would be an asset, but it hasn't been. First super-frosh Mike Watkins was declared ineligible. Meawnhile Donovan Jack stopped making his free throws and started turning the ball over more leading to the 9 point drop in efficiency you see here. But my biggest disappointment is Penn St. senior Jordan Dickerson. A lot of big men are late bloomers and the 7 footer seemed like he was making strides last year. It seemed quite possible he would anchor the defense and provide some surprising offense in his final season. The best I can say is that he has remained a solid rim-protector and shot-blocker. But he has been too foul prone and he hasn't been able to stay on the floor and take that next step.

 

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

-0.1, 6%, 1%, -12.3, Collin Hartman, Indiana, Jr, 4.8

-0.3, -3%, 2%, -5.4, Michal Cekovsky, Maryland, So, 2.3

-0.3, -2%, 1%, -5.9, Troy Williams, Indiana, Jr, 12.8

-0.6, -2%, -2%, -10.0, Damonte Dodd, Maryland, Jr, 3.4

-0.7, 4%, -2%, -6.9, Jared Nickens, Maryland, So, 5.4

-0.8, 1%, 0%, -11.6, Carlos Morris, Minnesota, Sr, 10.3

-0.9, -11%, 2%, -4.8, Gavin Schilling, Michigan St., Jr, 4.2

-1.0, -7%, 0%, 3.9, Marvin Clark Jr., Michigan St., So, 3.5

-1.1, -7%, 1%, -14.9, Greg Lewis, Rutgers, Sr, 4.2

-1.1, -17%, -2%, 8.2, Alexandru Olah, Northwestern, Sr, 10.6

-1.1, -6%, -1%, 9.0, Robert Johnson, Indiana, So, 7.8

-1.3, 0%, -4%, -3.0, Jaylon Tate, Illinois, Jr, 2.3

-1.5, -4%, 0%, 2.0, Melo Trimble, Maryland, So, 14.8

-1.6, -16%, 0%, 3.6, Kendall Stephens, Purdue, Jr, 7.2

-1.6, -9%, -3%, 1.0, Rapheal Davis, Purdue, Sr, 9.1

-2.0, 2%, -6%, 2.3, Jake Layman, Maryland, Sr, 10.5

-2.2, -12%, -1%, -11.3, Ricky Doyle, Michigan, So, 4.0

-3.1, -10%, -2%, 3.5, Zak Irvin, Michigan, Jr, 11.2

Maryland's Jake Layman has had to sacrifice a lot of shots with the additions of Robert Carter and Rasheed Sulaimon. Layman has seen the biggest drop in usage rate in the Big Ten.

ACC Player Development

Part 5 of the series looks at every player in the ACC playing roughly 20% of his team's minutes when active.

ACC Freshmen

PPG, Min%, Poss%, ORtg, Player, Team

17.4, 73%, 24%, 121.6, *Malik Beasley, Florida St.

17.0, 81%, 24%, 119.1, *+Brandon Ingram, Duke

16.4, 72%, 28%, 102.8, *+Dwayne Bacon, Florida St.

13.5, 76%, 26%, 97.1, *Bryant Crawford, Wake Forest

13.4, 83%, 22%, 102.6, *+Malachi Richardson, Syracuse

12.6, 83%, 19%, 105.7, *Maverick Rowan, North Carolina St.

11.9, 62%, 21%, 125.9, *Luke Kennard, Duke

11.6, 82%, 23%, 90.2, Jerome Robinson, Boston College

8.9, 74%, 15%, 121.3, *Tyler Lydon, Syracuse

8.5, 63%, 20%, 104.3, *+Derryck Thornton, Duke

7.6, 50%, 19%, 119.3, *+Donovan Mitchell, Louisville

7.2, 35%, 23%, 117.1, John Collins, Wake Forest

6.8, 48%, 18%, 106.4, Kerry Blackshear, Jr., Virginia Tech

5.9, 69%, 14%, 90.9, +A.J. Turner, Boston College

Players marked with a * were consensus Top 100 recruits. Players marked with a + were players we picked as instant impact freshmen at SI.com.

A few notable players are missing from this list. Virginia Tech's Chris Clarke was off to a nice start before he fractured his foot, but since he played so few games, I am not listing his stats. Two consensus Top 100 recruits are barely playing and didn't meet my minutes cut-off, Wake Forest's Doral Moore and North Carolina's Kenny Williams.

Let's start off by noting that Malik Beasley is putting up numbers very similar to Duke's Brandon Ingram. This is extremely impressive because unlike Ingram, Beasley didn't enroll at Florida St. with the expectation that he would be the go-to-player. The team brought in Dwayne Bacon, who was more highly rated, and the team brought back nearly all its starters from last year. Beasley had to practice hard to earn his large role, and he has not only delivered in practice, he has delivered on the court.

The second thing I want to discuss is how critical the injury was to transfer Terry Henderson for NC State. With Henderson out, Anthony Barber and Maverick Rowan have had to log huge minutes. Cat Barber has been phenomenal, but Maverick Rowan has been the typical quality freshman. Rowan has a great game and then he has a bad game. In a normal season if Rowan wasn't playing well, Mark Gottfried could put him on the bench. But this season he doesn't really have a choice; he has to keep Rowan on the floor.

Syracuse's Franklin Howard and Kaleb Johnson have scored 26 points and 16 points respectively on the season. I find this pretty shocking, but even with Howard playing a little bit more in a few games, Michael Gbinije has pretty much become the full-time PG. I thought he might be the part-time PG, but as the full-time PG that has opened the door for Malachi Richardson to play a ton at the wing and he has made the most of his opportunity.

Duke has been on an incredible roll with freshmen point-guards that are highly ranked out of high school. Tyus Jones, Austin Rivers, and Kyrie Irving were all highly ranked recruits that received major playing time when healthy and were eventually selected in the first round of the NBA draft after their freshman season. But this time Derryck Thornton has to count as a mild disappointment. Thornton was the RSCI #13 recruit, and despite the team having an open slot at point-guard, he is only starting sporadically. He is also Duke's least efficient regular rotation player. He isn't bad by any normal standard, but by elite prospect Duke standards, he isn't great. And Chase Jeter has been even worse. In the preseason at SI we projected Duke's Chase Jeter to be the 40th most impactful freshman, despite the fact that he was the RSCI #14 recruit, but even that seemingly pessimistic projection was way too optimistic:

 

PPG, Min%, Poss%, ORtg, Player, Team

5.8, 53%, 18%, 98.1, *Justin Robinson, Virginia Tech

5.7, 42%, 15%, 124.4, Matt Ryan, Notre Dame

5.6, 43%, 18%, 109.4, *Raymond Spalding, Louisville

4.6, 28%, 18%, 133.7, Anthony Lawrence Jr., Miami FL

4.5, 40%, 16%, 104.4, Terance Mann, Florida St.

4.5, 36%, 14%, 116.7, Matt Milon, Boston College

4.3, 28%, 21%, 88.9, Sammy Barnes-Thompkins, Boston College

4.0, 28%, 20%, 108.1, Damon Wilson, Pittsburgh

3.5, 48%, 13%, 88.0, Ervins Meznieks, Boston College

3.0, 22%, 24%, 86.4, *+Deng Adel, Louisville

2.5, 30%, 10%, 142.5, Rex Pflueger, Notre Dame

2.3, 26%, 15%, 82.1, Idy Diallo, Boston College

1.9, 19%, 19%, 91.9, Jack Salt, Virginia

1.7, 19%, 17%, 85.6, *+Chase Jeter, Duke

1.4, 23%, 18%, 82.9, *Franklin Howard, Syracuse

Boston College has played a lot of freshman, but only Matt Milon (over 50% of his threes) has been efficient and Milon is a role player who rarely plays or shoots. Don't knock Deng Adel for his low production; he is recovering from an injury. Notre Dame plays its starters a lot of minutes, but Matt Ryan has somehow earned his way into the rotation with some great shooting.

 

ACC Guys Who Sat Out 2 Years Due to Injury

PPG, Min%, Poss%, ORtg, Player, Team

4.0, 34%, 18%, 90.8, Darryl Hicks, Boston College

It is brutal to be injured for two years and then get healthy in time to play for such a depleted team.

ACC JUCOs

PPG, Min%, Poss%, ORtg, Player, Team

3.5, 25%, 18%, 102.1, Benji Bell, Florida St.

2.2, 20%, 17%, 105.7, Johnny Hamilton, Virginia Tech

Benji Bell picked the wrong year to join Florida St. The guard and wing positions are just too loaded for him to earn playing time.

ACC D1 Transfers

PPG, Min%, Poss%, ORtg, Player, Team, LastPPG, LastTeam

17.0, 81%, 21%, 128.4, Damion Lee, Louisville, 21.4, Drexel

16.8, 82%, 33%, 92.0, Eli Carter, Boston College, 8.8, Florida

15.8, 76%, 25%, 117.1, Zach LeDay, Virginia Tech, 3.5, South Florida

14.6, 70%, 29%, 96.0, Seth Allen, Virginia Tech, 13.4, Maryland

14.5, 72%, 21%, 120.8, Adam Smith, Georgia Tech, 13.4, Virginia Tech

12.1, 70%, 21%, 116.5, Trey Lewis, Louisville, 16.3, Cleveland St.

11.5, 56%, 25%, 108.1, Nick Jacobs, Georgia Tech, 8.4, Alabama

9.8, 76%, 19%, 107.9, Avry Holmes, Clemson, 12.5, San Francisco

6.6, 55%, 13%, 124.2, Sterling Smith, Pittsburgh, 14.1, Coppin St.

5.9, 57%, 15%, 102.7, Kamari Murphy, Miami FL, 6.1, Oklahoma

5.7, 54%, 15%, 114.7, Darius Thompson, Virginia, 2.5, Tennessee

3.9, 36%, 17%, 105.3, James White, Georgia Tech, 11.9, Arkansas Little Rock

2.5, 34%, 13%, 111.8, Rafael Maia, Pittsburgh, 9.9, Brown

1.9, 24%, 13%, 100.9, Alonzo Nelson-Ododa, Pittsburgh, 6.6, Richmond

Damion Lee was pushed pretty hard by Deng Adel in the preseason and when Adel went down, Lee was more than ready to be one of the nation's best wing-players. Eli Carter has had to score by default for Boston College, as expected. Thus the transfer that has probably surprised the most is Virginia Tech's Zach LeDay. My model thought he might get the most playing time in Virginia Tech's front-court, but he wasn't a very physical player at South Florida, and it wasn't clear he could be this good. Instead he's raised his rebounding rates substantially, he's increased his block rate, and he is shooting better across the board to boot.

The Pittsburgh frontcourt transfers have been a bit of a bust. After the team struggled to defend the paint last year they were supposed to fill the gap, but instead the team has looked in-house at players like Sheldon Jeter and Ryan Luther.

Finally Playing

The following players were not rotation players last year and have finally cracked the lineup:

PPG, Min%, Poss%, ORtg, Player, Team

6.3, 60%, 16%, 108.9, Cody Martin, North Carolina St.

5.4, 49%, 19%, 89.5, Gabe DeVoe, Clemson

5.2, 42%, 18%, 108.4, Jaylen Johnson, Louisville

5.0, 41%, 18%, 106.3, DaJuan Coleman, Syracuse

4.8, 24%, 21%, 122.6, Cameron Johnson, Pittsburgh

3.8, 37%, 12%, 130.2, Ben Lammers, Georgia Tech

3.7, 27%, 17%, 111.6, Ryan Luther, Pittsburgh

3.5, 33%, 18%, 96.9, Anas Mahmoud, Louisville

3.1, 37%, 13%, 95.5, Rondale Watson, Wake Forest

2.2, 29%, 13%, 108.7, Matt Farrell, Notre Dame

1.8, 38%, 9%, 80.1, Trent VanHorn, Wake Forest

Players who have barely played don’t typically become high scorers. Jumping back to the Pac-12 column, that is why what George King is doing at Colorado is so impressive.

Syracuse's DaJuan Coleman isn’t a major scorer, but his defense seems pretty critical to me at this point. There are a lot of times when he is on the bench that Syracuse looks over-matched in the paint.

Returning Players

Once again, when interpreting changes in PPG, you should keep in mind the changes in pace and opponent defense. Louisville's schedule has been significantly easier defensively this year than it was on the whole season last year. Meanwhile, Florida St.’s games have had almost 8 more possessions per game than their games had on the full year last year. Obviously that is going to inflate scoring totals.
 

ChOppDef, Team, ChRawPace

5.1, Louisville, 2.3

4.3, Boston College, 4.1

4.3, North Carolina, 3.5

3.7, North Carolina St., 3.9

3.7, Pittsburgh, 6.9

2.9, Virginia Tech, 7.1

2.8, Duke, 3.3

2.4, Miami FL, 5.5

2.3, Notre Dame, 2.0

2.2, Clemson, 1.2

2.0, Syracuse, -1.3

1.7, Georgia Tech, 4.7

1.2, Wake Forest, 3.5

0.6, Virginia, 3.4

0.3, Florida St., 7.7

 

Here are the biggest changes in PPG:

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

16.1, 66%, 3%, 11.6, +Grayson Allen, Duke, So, 20.6

11.3, 19%, 6%, 10.6, Anthony Barber, North Carolina St., Jr, 23.4

8.1, 50%, 3%, 4.3, Joel Berry, North Carolina, So, 12.3

7.9, 26%, 6%, 20.4, Ja'Quan Newton, Miami FL, So, 11.9

7.2, 14%, 10%, 16.7, Chinanu Onuaku, Louisville, So, 10.2

6.6, 40%, 0%, -1.2, +Bonzie Colson, Jr., Notre Dame, So, 12.2

6.4, 20%, 5%, 5.9, Abdul-Malik Abu, North Carolina St., So, 12.7

6.2, 38%, 1%, 0.7, Caleb Martin, North Carolina St., So, 11.1

6.1, 30%, 2%, 8.0, Matt Jones, Duke, Jr, 12.1

6.0, 49%, 3%, -8.8, Marshall Plumlee, Duke, Sr, 8.2

5.9, 45%, -2%, 7.7, +V.J. Beachem, Notre Dame, Jr, 11.8

5.5, 31%, 2%, 25.5, Quentin Snider, Louisville, So, 9.6

5.3, 22%, 3%, 10.3, +Amile Jefferson, Duke, Sr, 11.4

4.8, 2%, 4%, 17.0, London Perrantes, Virginia, Jr, 11.3

4.5, 3%, 8%, 19.8, Mangok Mathiang, Louisville, Jr, 7.1

Players marked with a + are players we projected as breakout players at SI.com. We were 4 for 4 in the ACC as Allen, Colson, Beachem, and Jefferson have all scored at a much higher level than last year when healthy.

As discussed earlier, Terry Henderson’s injury opened the door for Anthony Barber to be even more aggressive for North Carolina St. Joel Berry also benefited from Marcus Paige missing the start of the season. He’s become a confident polished player as a sophomore.

Louisville’s Chinanu Onuaku is the ACC player to show the biggest increase in aggressiveness. Onuaku used just 13% of his team’s possessions last year. This year he uses 23%. And he’s lowered his turnovers and improved slightly at his free throw shooting at the same time which is a great accomplishment. Mangok Mathiang was making similar progress though an injury interrupted that. Meanwhile Quentin Snider has become a much more efficient player this year. Rick Pitino is mostly winning because he is a dominant defensive coach, but he knows a thing or two about developing players too.

Ja’Quan Newton has an argument for the most improved player in the ACC as he is tied for third with a huge 6% jump in aggressiveness, and his efficiency has jumped by 20 points. Newton’s turnover rate, free throw shooting, and two point percentage are all much better than last year.

 

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

4.5, 10%, 4%, 6.1, Michael Gbinije, Syracuse, Sr, 17.2

4.2, 7%, 0%, 13.6, Devin Thomas, Wake Forest, Sr, 16.3

4.1, 6%, 1%, 11.7, Jaron Blossomgame, Clemson, Jr, 17.2

3.9, 12%, 4%, 16.0, Sheldon Jeter, Pittsburgh, Jr, 8.6

3.8, 5%, 0%, 14.4, Brice Johnson, North Carolina, Sr, 16.7

3.8, 2%, 2%, 8.7, Malcolm Brogdon, Virginia, Sr, 17.8

3.7, -8%, 6%, 2.9, Mike Young, Pittsburgh, Jr, 17.0

3.6, 1%, 6%, -0.4, Demetrius Jackson, Notre Dame, Jr, 16.0

3.1, 9%, -1%, 22.2, Isaiah Hicks, North Carolina, Jr, 9.8

3.0, 32%, -4%, 17.7, Jordan Roper, Clemson, Sr, 9.7

3.0, 9%, 0%, 1.3, Anthony Gill, Virginia, Sr, 14.6

3.0, 10%, 6%, 8.1, Sidy Djitte, Clemson, Jr, 5.1

2.6, 23%, 1%, 17.5, Devon Hall, Virginia, So, 4.4

2.6, 8%, 3%, -0.5, Steve Vasturia, Notre Dame, Jr, 12.6

2.5, 28%, -2%, 27.5, Isaiah Wilkins, Virginia, So, 4.2

2.5, 30%, 2%, 0.2, Theo Pinson, North Carolina, So, 5.4

Virginia's Isaiah Wilkins turnover rate has plummeted this year leading to the biggest jump in efficiency in the ACC, but he is such a low-usage role player that it matters less than you might think.

 

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

2.1, 13%, 3%, -9.4, Davon Reed, Miami FL, Jr, 10.3

2.0, 2%, 1%, 7.4, Marcus Georges-Hunt, Georgia Tech, Sr, 15.6

1.8, -8%, 3%, 2.4, Jamel Artis, Pittsburgh, Jr, 15.5

1.7, -2%, -1%, 11.1, Sheldon McClellan, Miami FL, Sr, 16.1

1.6, 13%, 2%, 4.2, Tyler Roberson, Syracuse, Jr, 9.8

1.5, 7%, -1%, 9.8, Donte Grantham, Clemson, So, 10.3

1.4, 10%, -4%, -2.8, Jalen Hudson, Virginia Tech, So, 8.3

1.3, 3%, 6%, -18.9, Dennis Clifford, Boston College, Sr, 8.2

1.2, 2%, 1%, -0.3, Justin Jackson, North Carolina, So, 12.0

1.2, 5%, 1%, -1.0, Nate Britt, North Carolina, Jr, 6.7

1.1, 9%, -3%, 8.3, Charles Mitchell, Georgia Tech, Sr, 10.9

1.1, 14%, 1%, -8.7, Zach Auguste, Notre Dame, Sr, 13.9

1.0, -10%, 0%, 12.6, James Robinson, Pittsburgh, Sr, 9.9

0.9, 3%, -2%, 20.2, Ivan Cruz Uceda, Miami FL, Sr, 6.1

0.9, -7%, 3%, 5.5, Landry Christ Nnoko, Clemson, Sr, 8.5

Dennis Clifford has had to take a larger role in the Boston College offense this year and he has seen the biggest drop in efficiency in the ACC. And certainly, the increase in shot volume explains his increase in turnover rate and lower shooting percentage. But what explains his drop in free throw percentage?

 

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

0.8, 4%, 0%, 0.1, Kostas Mitoglou, Wake Forest, So, 10.5

0.8, 11%, -8%, 27.5, Justin Bibbs, Virginia Tech, So, 12.2

0.7, 4%, 1%, -6.2, Boris Bojanovsky, Florida St., Sr, 5.8

0.6, 7%, 3%, -4.9, Garland Owens, Boston College, Jr, 4.0

0.4, 1%, 2%, 1.1, Joel James, North Carolina, Sr, 2.9

0.3, -8%, 1%, 13.0, Greg McClinton, Wake Forest, So, 3.7

0.3, 9%, -2%, 6.7, Lennard Freeman, North Carolina St., Jr, 3.9

0.2, -3%, -1%, 5.1, Mike Tobey, Virginia, Sr, 7.1

0.2, -1%, 1%, 2.8, Trevor Cooney, Syracuse, Sr, 13.5

0.1, 8%, 0%, 0.3, Mitchell Wilbekin, Wake Forest, So, 7.3

0.1, -1%, 0%, 5.5, Marial Shayok, Virginia, So, 3.9

0.1, -3%, 0%, 6.9, James Palmer, Miami FL, So, 3.8

0.1, 0%, -4%, 4.6, Shane Henry, Virginia Tech, Sr, 2.4

0.0, -1%, -1%, 4.1, Kennedy Meeks, North Carolina, Jr, 11.3

Justin Bibbs is tied with the biggest jump in efficiency in the ACC, but that is largely because he has become a more passive player. He is taking less bad two point jumpers this season.

 

ChPPG, ChMin, ChPoss, ChORtg, Player, Team, Class, CurrentPPG

-0.1, 9%, -1%, -9.3, BeeJay Anya, North Carolina St., Jr, 4.4

-0.3, 12%, -5%, 10.7, Angel Rodriguez, Miami FL, Sr, 11.7

-0.3, 0%, -4%, 9.5, Tadric Jackson, Georgia Tech, So, 5.1

-0.6, 1%, -3%, 3.1, Tonye Jekiri, Miami FL, Sr, 8.0

-0.7, 4%, 1%, -12.6, Cornelius Hudson, Wake Forest, So, 6.8

-0.8, -2%, -2%, -6.0, Josh Smith, Clemson, Sr, 1.6

-0.9, -12%, 0%, 14.2, Devon Bookert, Florida St., Sr, 9.1

-1.0, 3%, -4%, 13.3, Josh Heath, Georgia Tech, Jr, 3.3

-1.0, -13%, -3%, 23.5, Travis Jorgenson, Georgia Tech, Jr, 2.7

-1.1, -7%, -1%, 8.8, Quinton Stephens, Georgia Tech, Jr, 4.9

-1.6, -7%, -1%, 0.9, Marcus Paige, North Carolina, Sr, 12.4

-1.7, -22%, 3%, -17.8, Evan Nolte, Virginia, Sr, 1.4

-2.0, -9%, -1%, -13.4, Jarquez Smith, Florida St., Jr, 4.1

-2.7, -26%, 0%, 4.4, Chris Jones, Pittsburgh, Jr, 5.8

-3.1, -26%, -4%, 14.0, Phil Cofer, Florida St., So, 3.8

-3.2, -10%, -4%, 5.9, Xavier Rathan-Mayes, Florida St., So, 11.7

-4.1, -20%, -7%, -15.5, Devin Wilson, Virginia Tech, Jr, 2.4

-7.3, -4%, -8%, -14.3, Codi Miller-McIntyre, Wake Forest, Sr, 7.2

-8.1, -32%, -7%, -11.2, Montay Brandon, Florida St., Sr, 3.7

Several Florida St. players, most notably Montay Brandon, have seen their playing time and shot volume squeezed out by Florida St.’s elite recruiting class. Wake Forest’s Codi Miller-McIntyre hasn’t been the same player since returning from his injury. It is sad to see the senior go out like this.