Tag Archives: advanced statistics

Mbakwe’s 8.8 Rebounds Don’t Tell The Full Story

March 4, 2013

New article is now up at GopherHole.com. It takes a look at Minnesota’s Trevor Mbakwe’s impressive work on both the defensive and offensive glass this season.

Below is just one of the tables included in that article. It shows total rebound percentage leaders among the six “BCS” conferences over the past four seasons and each player’s current status (NBA lottery, first rounder, second rounder, undrafted… or current college player).

Averaging both 24% DR% and 16% OR% as Mbakwe is doing this season is quite rare.


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Big Ten Value Add Insights – 2/23/13

February 23, 2013
Big Ten Value Add Insights (through games of 2/21/2013)

See www.valueaddbasketball.com and Breitbart Sports for further information on Value Add Basketball.

The table below lists the top 20 Big Ten players according to Value Add Basketball, through games of February 21, 2013. It’s no surprise that Trey Burke, Victor Oladipo and Cody Zeller are the top three, but there are some interesting inclusions and exclusions further down the list.Prior to the season beginning we talked about Minnesota’s “fallacy of depth”:

Having healthy bodies available is not the same thing as having great depth. We believe there are two optimal lineups (depending on the opponent) for Minnesota this year and also believe that Minnesota’s best players can add significantly more value than the rest of the roster.


However, Tubby Smith has used a relatively large bench in the past and frequently has subbed in three to five players at the same time within the first 10 minutes of games. The difference between winning and losing a game in the Big Ten and against competitive nonconference opponents is not large and lineup choices can greatly influence outcomes.

Minnesota and Indiana are the only teams with 4 players in the top 20 of Value Add. While the Hoosiers are the top team in the nation, the Gophers are sitting alone at 8th place in the conference.

Minnesota has plenty of talent and, on balance, they have gotten very good production out of that talent. However, the bizarre utilization of their roster has cost them games.

D1 Rank Player Team OFF DEF PG/PER TOTAL
1 Burke, Trey Michigan 9.78 -0.42 1.5 11.71
3 Oladipo, Victor Indiana 6.21 -3.31 0.5 10.03
6 Zeller, Cody Indiana 6.85 -2.53 0 9.38
34 Thomas, Deshaun Ohio St. 7.08 0.21 0 6.87
37 Hollins, Austin Minnesota 4.83 -1.48 0.5 6.81
38 Hulls, Jordan Indiana 5.14 -0.16 1.5 6.79
43 Brust, Ben Wisconsin 4.22 -1.51 1 6.72
49 Berggren, Jared Wisconsin 4.42 -2.19 0 6.61
70 Watford, Christian Indiana 4.68 -1.38 0 6.06
80 Richardson, DJ Illinois 3.89 -1.52 0.5 5.91
86 Payne, Adreian Michigan St. 3.7 -2.09 0 5.8
87 Appling, Keith Michigan St. 3.39 -0.89 1.5 5.78
93 White, Aaron Iowa 4.42 -1.26 0 5.68
97 Hollins, Andre Minnesota 4.76 -0.85 0 5.61
100 Mbakwe, Trevor Minnesota 3.19 -2.39 0 5.57
101 Craft, Aaron Ohio St. 2.61 -1.44 1.5 5.55
102 Robinson, Glenn Michigan 5.46 -0.06 0 5.52
123 Paul, Brandon Illinois 3.61 -1.6 0 5.21
153 Swopshire, Jared Northwestern 3.01 -1.81 0 4.82
165 Williams, Rodney Minnesota 3.63 -1.05 0 4.68

Other notes:
Only one freshman – Michigan’s Glenn Robinson – is in the Value Add top 20. Other top freshmen (although outside of the top 20) include Gary Harris, Nik Stauskas, Sam Dekker, Mitch McGary and AJ Hammons.

Top 10 Offensive Value Add Players:

Player Team OFF
Burke, Trey Michigan 9.78
Thomas, Deshaun Ohio St. 7.08
Zeller, Cody Indiana 6.85
Oladipo, Victor Indiana 6.21
Robinson, Glenn Michigan 5.46
Hulls, Jordan Indiana 5.14
Stauskas, Nik Michigan 5
Hollins, Austin Minnesota 4.83
Hollins, Andre Minnesota 4.76
Watford, Christian Indiana 4.68

Top 10 Defensive Value Add Players:

Oladipo, Victor Indiana -3.31
Evans, Ryan Wisconsin -2.7
Zeller, Cody Indiana -2.53
Dawson, Branden Michigan St. -2.42
Mbakwe, Trevor Minnesota -2.39
Berggren, Jared Wisconsin -2.19
Payne, Adreian Michigan St. -2.09
Swopshire, Jared Northwestern -1.81
McGary, Mitch Michigan -1.78
Paul, Brandon Illinois -1.6

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Doing the Splits: Andre Hollins

January 24, 2013

In early December we wrote Andre Hollins: A Tale of Two Games? which looked at Dre’s stats for all games excluding Memphis and South Dakota State games. Today, we’ll do the same.

As discussed in the earlier article, Joe Jackson of Memphis played just seven minutes against the Gophers and was on the floor at the same time as Andre for less than five (4:38). Also, SDSU star Nate Wolters did not play at all due to injury. In his place the Jackrabbits started a true freshman who turned the ball over seven times.

Dre has had several high-scoring games other than the two that are excluded below. However, the splits of (1) the Memphis & SDSU games compared to (2) all other games are interesting.

  PPG eFG% 2FG% 3FG% FT%
MEM & SDSU 31.5 102.0% 69.2% 91.7% 92.3%
All Other 11.8 47.2% 43.2% 34.2% 74.2%
TOTAL 13.8 54.6% 46.8% 41.8% 77.2%

Now, let’s look at this season’s “All Other” performance compared to Dre’s freshman year:

  Pts/40 eFG% 2FG% 3FG% FT%
Soph, All Other 16.9 47.2% 43.2% 34.2% 74.2%
Freshman 16.5 48.2% 40.5% 37.9% 90.4%

Even after 19 games, it’s apparent what a big factor the Memphis and South Dakota State games have on Dre’s 2012-13 statistics.

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Big Ten Efficiencies: Raw vs. Adjusted

January 20, 2013
Numbers alone rarely tell a complete story and that can be a blessing or a curse, depending on who is using them and how they are doing so. We’re not going to deep into explanations here, but below is a bit of food for thought. If you have specific questions or thoughts, please feel free to contact us.

Kenpom.com offers a wealth of data and we strongly recommend everyone in the world visit that site. Understanding the methodology and assumptions used by Pomeroy and other advanced ranking systems, at least with some degree of clarity, can greatly enhance the usefulness of the data and predictions.

The overall predictive rankings of teams is based largely on their respective offensive and defensive efficiency figures. Although there are often immaterial differences in methodologies used to calculate actual efficiency figures when comparing one system to another, most should approximate one another.

The focus of most users (and rightfully so) of Kenpom and other advanced rating systems is squarely on the adjusted figures. Most people are fine with accepting limitations of different systems without understanding the impact and sensitivity of those limitations on the figures they’re using.

As you’ll see below, it might be best that people don’t get too into the details because you could spend hours making small adjustments to the detail only to come up with answers that aren’t all that different from what you started with. Still, considering the methodologies and assumptions of different ranking systems can be enlightening and useful for some.

BIG TEN DATA (through D-I games of 1/19/2013)

The tables below lists Kenpom offensive and defensive efficiency data for Big Ten teams (all D-I games including nonconference through 1/19/2013).

Offense Example: Minnesota’s OffEff of 4.5 means that their Adjusted Offensive Efficiency is 4.5 better (higher) than their Raw Offensive Efficiency (Note: the average D-I Adjusted Efficiency figure is 99.5). Minnesota’s OffEffRank of 3 means that their Adjusted Offensive Efficiency rank among 347 D-I teams is 3 spots higher as compared to their Raw Offensive Efficiency rank.

 OFFENSE OffEff OffEffRank
Michigan St. 4.9 47
Minnesota 4.5 3
Michigan 4.4 0
Illinois 3 28
Nebraska 2 39
Purdue 2 27
Ohio St. 1.9 4
Penn St. 1.5 31
Wisconsin 0.7 -5
Northwestern 0.5 -4
Indiana 0.2 -2
Iowa -0.1 -12

Defense Example: Minnesota’s DefEff of 5.1 means that their Adjusted Defensive Efficiency is 5.1 better (lower) than their Raw Defensive Efficiency (Note: the average D-I Adjusted Efficiency figure is 99.5). Minnesota’s DefEffRank of 38 means that their Adjusted Offensive Efficiency rank among 347 D-I teams is 38 spots higher as compared to their Raw Offensive Efficiency rank.

 DEFENSE DefEff DefEffRank
Minnesota 5.1 38
Nebraska 4.2 63
Illinois 2.8 39
Iowa 2.6 11
Wisconsin 2.5 7
Ohio St. 2 5
Michigan 1.9 14
Penn St. 1.8 38
Michigan St. 1.3 -2
Northwestern 1.2 9
Purdue 0.6 1
Indiana -0.2 -3

A high-level answer is that a team’s performance each game is adjusted for the level of their competition (and there are other factors to a team’s adjusted efficiency figures including preseason rankings and higher weighting of more recent games). Minnesota, relative to other Big Ten teams, has played a strong nonconference schedule and therefore it’s not surprising they would have some of the larger adjustments.

One thing Kenpom doesn’t take into account is whether a key player was out for a particular game. Thus, when the Gophers hosted South Dakota State and Nate Wolters was out with an injury, Kenpom effectively assumes that Wolters played about 35 minutes.

Minnesota’s defensive efficiency against SDSU was 93.6 and this was one of the Jackrabbits’ worst offensive performances of the season. However, because SDSU’s adjusted offensive efficiency for the season is a strong 108.2, Kenpom adjusts Minnesota’s defensive efficiency for the game down to a much better 85.8.

Logically, the size of this adjustment doesn’t make sense because Wolters was injured and didn’t play in the game. We have estimated the impact of the Wolters’ injury on Minnesota’s overall adjusted defensive efficiency for the season, but that’s too much detail for this article.

However, something to be cognizant of is that there are many games across the world of college basketball for which adjustments, both positive and negative, may not be warranted (logically that is, although under the ranking system they make perfect sense).

In the case of Minnesota there are few examples with more than an insignificant impact, including the SDSU and Memphis games (Joe Jackson sat after playing just 7 minutes; Geron Johnson’s first game back, etc.). At the same time one can point to Trevor Mbakwe having played in less than 55% of the team’s minutes so far this season. As it’s reasonable to assume he’ll play more than that throughout the remainder of this season, an additional adjustment to the predictive adjusted efficiency figures is warranted.

Now, you could spend days running through adjustment exercises for all D-I teams and there probably wouldn’t be many earth-shattering changes in rankings. However, understanding unusual and significant factors in reaching predictive rankings can be worthwhile.

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Gophers’ 2FG% in Nonconference Play Down From 2011-12

Over at GopherHole.com, you can read More Than a Number: Minnesota’s 2-Point Field Goal Shooting.

The article looks at the Gophers’ 2-point field goal shooting and how they can and need to improve their eFG% simply by deferring some lower percentage shots.

Last night Northwestern allowed Michigan to shoot 71% eFG, including 60% 2FG, in a 94-66 Wolverine win. Minnesota hosts the Wildcats Sunday evening at 6pm.

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Minnesota Rebounding: Gophers Only Cleaning One Side of the Glass

In recent years, Minnesota teams have excelled at blocking shots and offensive rebounding. Contrary to what you might expect, however, the defensive rebounding of the Gophers has ranged from mediocre to poor when compared to the rest of the Big Ten and other D1 teams. So far in 2012-13, these trends have continued.

According to StatSheet.com, Minnesota’s offensive rebounding percentage this year is second best in the nation and tops in the Big Ten. On the defensive boards, the Gophers are dead last in the Big Ten and one of the worst in the nation at 329.

Minnesota’s performance on the defensive glass isn’t skewed by a game or two. In fact, the team’s defensive rebounding percentage has been better than the national average in only one game this year (Toledo).

As illustrated in the tables below, during Tubby’s years as head coach the team’s offensive rebounding percentage has been impressive while their defensive rebounding percentage has been relatively poor.

5-Year conference rankings for Minnesota’s offensive & defensive rebounding percentages:

Conference OR% & DR%










5-Year national rankings for Minnesota’s offensive & defensive rebounding percentages:

Overall OR% & DR%










A renewed focus on defensive rebounding could be directed by the coaching staff, but how much might stressing this area hurt the team’s transition into their offense? Minnesota has been particularly successful this year when they strike quickly after a defensive rebound. According to Hoop-Math.com, the Gophers have an effective field goal percentage (eFG%) of 73% this season when they shoot within 10 seconds of a defensive rebound. Last year, that figure was 54%.

The figure of 73% eFG% is going to fall as the season goes on as it’s been boosted by an unsustainable 59% 3-point conversion rate. Still, for a team that is often stale in half court sets, anything that detracts from their ability to score in transition could do more harm than good.

We see a few things that could be done, including:

  • Better utilization of the roster, especially Trevor Mbakwe. He’s one of the better rebounders in the college game and should be playing 30+ minutes per game, not fewer than 20.
  • Centers Elliot Eliason (15.8 mpg) and especially Maurice Walker (7.8 mpg) could be given more minutes. At times, we believe it will be appropriate to play one of these two along with Trevor Mbakwe and Rodney Williams.
  • Push the others to improve their tenacity and consistency. Rodney Williams (who has been sensational in most aspects of his game), Andre Ingram (8% DR%) and Joe Coleman all need to improve their contribution on the defensive glass. In the last four games, Minnesota’s opponents have pulled down offensive rebounds at a 39% rate in the first half, but the percentage jumps to 52% in the second half.
What do you think? CONTACT US with your thoughts on this and other articles, as well as any suggestions, comments and critiques.


Additional Data for Consideration
Using KenPom.com data through games of November 29, 2012, we looked at who makes up the top 48 defensive rebounders in the Big Ten. Only those who have played in at least 40% of their team’s minutes were included.

If all teams were created equal, we’d expect four players from each of the 12 Big Ten teams to be listed. All but two teams are within one of that expectation (i.e., 10 teams have three, four or five players in the top 48). The outliers are Penn State (six) and Minnesota (one).

For the Gophers, Maurice Walker would be in the Top 10, but has played in less than 20% of the team’s minutes. Elliot Eliason is just short of 40% in minutes and ranked at #30.

Details are listed below:

Rank Name Team DR% Min%
9 Jermaine Marshall Penn St. 19.3 81.2
15 Ross Travis Penn St. 17.9 84.5
29 D.J. Newbill Penn St. 15.3 87.3
36 Brandon Taylor Penn St. 14.4 40.4
38 Sasa Borovnjak Penn St. 13.7 42.2
41 Jon Graham Penn St. 12.6 50.6
17 Eric May Iowa 17.4 48.9
19 Adam Woodbury Iowa 16.8 41.8
32 Zach McCabe Iowa 14.9 44.6
35 Aaron White Iowa 14.5 73.9
40 Melsahn Basabe Iowa 12.9 48.9
1 Adreian Payne Michigan St. 28.2 28.2
7 Derrick Nix Michigan St. 20.3 68.2
21 Denzel Valentine Michigan St. 16 61.1
33 Branden Dawson Michigan St. 14.7 69.3
46 Keith Appling Michigan St. 12.3 89.3
4 Alex Olah Northwestern 23.8 45.3
16 Jared Swopshire Northwestern 17.7 67.4
28 Mike Turner Northwestern 15.4 45.3
43 Reggie Hearn Northwestern 12.5 73.7
45 Drew Crawford Northwestern 12.4 74.7
11 Sam Thompson Ohio St. 19 61
22 Deshaun Thomas Ohio St. 16 80
30 Lenzelle Smith Ohio St. 15.1 76.5
44 Evan Ravenel Ohio St. 12.4 49
48 LaQuinton Ross Ohio St. 11.9 41
10 Tim Hardaway Michigan 19.1 82.5
26 Glenn Robinson Michigan 15.7 80.8
42 Jordan Morgan Michigan 12.6 48.8
47 Nik Stauskas Michigan 12 65.8
6 Andre Almeida Nebraska 20.5 51.7
12 Brandon Ubel Nebraska 18.9 75.4
18 David Rivers Nebraska 17.4 60.8
20 Dylan Talley Nebraska 16.7 88.8
2 Ben Brust Wisconsin 24.6 75.4
8 Ryan Evans Wisconsin 19.4 72.5
24 Jared Berggren Wisconsin 15.8 66.8
39 Mike Bruesewitz Wisconsin 13.7 54.6
23 Joseph Bertrand Illinois 16 52.9
25 D.J. Richardson Illinois 15.8 78.2
27 Brandon Paul Illinois 15.6 77.2
3 Christian Watford Indiana 24.1 62.1
13 Cody Zeller Indiana 18 67.4
37 Will Sheehey Indiana 14.3 52.3
14 A.J. Hammons Purdue 18 43.7
31 Anthony Johnson Purdue 15 66.9
34 Ronnie Johnson Purdue 14.7 65.3
5 Trevor Mbakwe Minnesota 22.5 45.6
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Minnesota Returns One of the Best Shooters Among Big Ten Point Guards

After considering the statistics below, which player do you think had a better season – A or B?

2011-12 Player Comparison

Player A

Player B

Games started



Offensive Rating



2-pt FG%



3-pt FG%



REB / 40 min



AST / 40 min



TO / 40 min



STL / 40 min



Also, keep in mind the following:

  • Player A made more shots in fewer attempts than Player B when shooting 2-point field goals.
  • Player A also made more shots in fewer attempts than Player B when shooting 3-point field goals.
  • Each player turned the ball over and secured rebounds at approximately the same rates.

Andre Hollins had a fine freshman campaign and his progression over the course of the season could be seen.  He’ll be much improved as a sophomore and looks to be a key piece of Minnesota basketball for the next few years.

However, as a freshman his 2-point field goal percentage was the worst of all Gophers (excluding walk-ons), he had a turnover rate of about 26% and was prone to picking up bad fouls.  These are areas that often improve significantly between a player’s first and second years and Dre projects to be very good.

Although Hollins did average 15.0 ppg in the Gophers’ NIT run, his effective field goal percentage was only 47.4% and the young guard turned the ball over at an average of 5.0 per 40 minutes (25% higher than his average for the full season).  Also, it’s fair to note that in the NIT Minnesota didn’t face any teams in the top 50 for defensive efficiency until Stanford (19th).  To be sure, the confidence is there and things will come together for Andre, but in 2011-12 the Gophers’ best point guard was Julian Welch (Player A).

People will remember some late game missed free throws from Welch, but he was a fine 78% from the line overall.  If anything more than coincidence, misses in crunch time are mostly mental and fans should do what Julian needs to do whenever he’s at the line – forget about the past.  It’s just another free throw.

The junior guard from California proved to be capable of hitting key shots on many occasions.  Just a sample:

  • With 5:38 to play against Michigan in the Big Ten Tourney, his 3-pointer put Minnesota up 49-45.  25 seconds later, he buried another trey to make it 52-45 in favor of the Gophers.
  • In overtime against Northwestern, Julian connected from deep to break a 62-62 tie and the Gophers never gave the lead back.
  • With less than three minutes on the clock and down by 5, Welch’s 3-pointer made the score 55-53 Michigan in a regular season contest.  Less than a minute later, another long range basket cut the lead to 57-56.
  • At Illinois, his 3-point baskets late in the second half tied the game up at 54 and 57, respectively.
  • Down by 5 with 4:36 to play, Welch nailed a triple to reduce Indiana State’s lead to 2 points.  A minute later, his layup would give Minnesota a 63-62 lead and his 4/4 free throw shooting in the last 1:23 of the game sealed the victory for the Gophers.

Welch started and ended the season playing through injury, but even after his first three games as a Gopher in which he shot just 2/9 from the field, had 4 assists and 8 turnovers, he put together a solid 2011-12 campaign.  His 56.1 eFG% was so good that it will be difficult to duplicate (to compare, Andre Hollins had a 48.2 eFG% and in 2010-11 senior Blake Hoffarber shot 53.5%), but if he can cut down on turnovers and not take a huge step back shooting the ball, the 5th year senior will be a valuable part of the team once again.

The time is now for sophomore Andre Hollins, but there’s no reason why he and Julian Welch can’t play together.  No matter who carries the ball up the court, you’ve then got two ballhandlers that are threats from 3-point range.  While Julian adds in a nifty mid-range game, Andre has the ability to get all the way to the bucket.  Combine those two with Austin Hollins and the defense has to worry about three deep ball threats who can attack at multiple levels.  Not bad.  Add in an all-conference talent down low in Trevor Mbakwe along with an athletic Rodney Williams cutting toward the hoop and opponents are going to have their hands full.

Match ups and a number of other variables will dictate who plays with who, but don’t forget about Julian Welch as a potential difference maker for the 2012-13 Golden Gophers.  No matter where you see Welch fitting in with next year’s team, he deserves a lot of credit for a solid first year at Minnesota.

The table below is not meant to be an exhaustive list of everyone who played point guard in the Big Ten, but it does help to illustrate where the Gophers’ guards stacked up against their peers.

B1G Point Guards – Effective Field Goal Percentage in 2011-12




Jordan Hulls



Julian Welch



Aaron Craft

Ohio State


Trey Burke



Dave Sobolewski



Andre Hollins



Jordan Taylor



Lewis Jackson



Keith Appling

Michigan State


Tim Frazier

Penn State


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