Tag Archives: advanced statistics

2015 FIBA Americas U16 Advanced Stats

2015 FIBA Americas U16 Advanced Stats

We have calculated various advanced statistics for all teams which competed in this year’s 2015 FIBA Americas U16 Championship.

This article highlights certain key statistics. The attached PDF includes additional data. If you would like an Excel version of player statistics, please contact us at LateNightHoops@LateNightHoops.com.

We start off with the top 20 Offensive Ratings (30% minutes played minimum for all stats listed below), led by Minnesota’s Gary Trent Jr.

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EYBL 2015 Session 2: Howard Pulley Advanced Stats

EYBL 2015 Session 2: Howard Pulley Advanced Stats

 

Howard Pulley finished this weekend’s session with a 74-70 victory over Boo Williams. Pulley (3-5) had started the session with three losses, but an impressive 13 point, 12 rebound performance by 2016 center Brock Bertram helped propel the Panthers to the win.

Continue reading below for select team and individual advanced statistics from the weekend.

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Ask LNH: Doesn’t kenpom treat all games equally?

Ask LNH: Doesn’t kenpom treat all games equally?

This question came in response to our article regarding Wisconsin’s adjusted offensive efficiency. The Badgers now have a positive points-per-100 possessions adjustment of 7.0, or 5.8%, given to their actual per game average offensive efficiency. Both of these adjustments are larger than those given to any other team in the nation.

The answer to the question is “no.” When thinking about kenpom’s ranking system, always keep in mind that it’s a predictive system. Giving more weigh to recent games when predicting the immediate future doesn’t seem odd at all.

Let’s do some quick math to see if treating the Kentucky equally to all others would cause a different answer. Coming into the Final Four, Wisconsin’s AdjOE was 127.5. They had played 38 games. 127.5 * 38 = 4,845. After the Kentucky game, Wisconsin’s AdjOE is 128.5. An AdjOE of 128.5 * 39 games = 5,011.5.

If all games were treated equally, you’d expect Wisconsin’s AdjOE against Kentucky to be 166.5 (5,011.5 – 4,845). The Badgers scored 123.3 pp100p on a neutral court against Kentucky and their 86.5 AdjDE.

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Fact Check: CBS Claims Badgers Scoring 1.28 PPP

Fact Check: CBS Claims Badgers Scoring 1.28 PPP

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The growing usage of KenPom.com by fans and media can be a great thing. However, quite often the commentary from folks regarding KenPom’s predictive system is flawed and illogical.

Just another example is Matt Norlander of CBSsports.com, who this week wrote, “The Badgers have an offensive rating of 127.5, meaning they are dousing foes at a blazing rate. UW’s scoring nearly 128 points per 100 possessions. Unheard of at the college level… hat UW is flirting with 1.3 PPP on a per-game basis is flatly freaky.”

The truth is that Wisconsin’s offense isn’t producing anywhere near 1.3 points per possession.  Let’s take a further look…

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Minnesota’s Mo Walker: Stealing The Show

Minnesota’s Mo Walker: Stealing The Show

Known for his offensive prowess, Gophers’ fifth-year senior Maurice Walker has made a statistically remarkable impact on the other side of the court in 2014-15.

The Gophers have the nation’s second-highest steal rate and their style of play has helped Walker to register a high steal percent, but as the team’s last game at Iowa reminded us, a lot of it is square on him.

Walker’s steal from Iowa guard Mike Gesell late in the game helped to seal Minnesota’s important 64-59 road win on Thursday. Earlier in the game – as he has many times this season – Mo stepped around his man to get his arm into the passing lane and deflect an attempted delivery to the low block, resulting in a turnover.

The figures below are from KenPom.com and include only players who have been on the court for at least 40% of their team’s minutes. To put into context, there are 88 Big Ten players who meet that minimum through games of February 13, 2015.

The Gophers have the top four thieves in the conference (all games, including nonconference):

Rank Player Team Ht Wt Yr %Stls
1 Nate Mason Minnesota 6-1 180 Fr 4.82
2 Deandre Mathieu Minnesota 5-9 165 Sr 4.36
3 Carlos Morris Minnesota 6-5 180 Jr 4.35
4 Maurice Walker Minnesota 6-10 250 Sr 4.17

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Top Freshmen Rebounders; Seton Hall Visits Marquette

Top Freshmen Rebounders; Seton Hall Visits Marquette

Last May, ESPN’s Reggie Rankin put together his Class of 2014 Best Rebounders. Missing from the list was 6’9” Seton Hall freshman Angel Delgado who will visit Milwaukee on Wednesday. To his credit, when asked about Delgado after releasing his top 5 rebounders, Rankin indicated that Delgado belonged in the conversation.

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With Marquette’s next opponent being Seton Hall, today we take a look at top freshman rebounders including the impressive figures Delgado has produced this season. For purposes of this article, data is through January 24, 2015 and comes from basketball-reference.com.

D-I’s top 5 freshmen (minimum of 225 minutes played) in total rebounding percentage this season are as follows:

Rk Player School MP ORB% DRB% TRB%
1 Josh Ibarra Houston Baptist 261 17.4 30.4 24.1
2 Rokas Gustys Hofstra 236 20.1 23.9 22.0
3 Angel Delgado Seton Hall 469 16.9 24 20.5
4 Jakob Poeltl Utah 402 16.9 23.2 20.4
5 Domantas Sabonis Gonzaga 449 11.5 24.1 18.6

Based on what we saw in travel and international play we expected Rokas Gustys to do well rebounding the ball from day one, but he’s been even better than expected. Gustys has missed time due to injury, but still has maintained a 20-20 OR-DR combo over 236 minutes of play.

Top 5 Offensive Rebounding Percentages

Rk Player School MP ORB%
1 Rokas Gustys Hofstra 236 20.1
2 DeSean Murray Presbyterian 291 17.5
3 Josh Ibarra Houston Baptist 261 17.4
4 Angel Delgado Seton Hall 469 16.9
5 Jakob Poeltl Utah 402 16.9

Top 5 Defensive Rebounding Percentages

Rk Player School MP DRB%
1 Josh Ibarra Houston Baptist 261 30.4
2 Leron Black Illinois 314 25.0
3 Tyler Rawson Southern Utah 288 24.8
4 Domantas Sabonis Gonzaga 449 24.1
5 Angel Delgado Seton Hall 469 24.0

ESPN’s May ’14 Picks – Top 5 Rebounders – Current Rank

Jahlil Okafor – #12 TR%, #6 OR%, #41 DR%
Cliff Alexander – #11, #14, #13
Goodluck Okonoboh – #75, #103, #180
Reid Travis – #31, #40, #41
Abdul-Malik Abu – #60, #78, #55

Other Seton Hall Notes:

  • The Pirates provide another fine example of a team that can be great on one side of the glass, but not the other. Their OR% is #34 in the nation per KenPom.com, but their DR% is #303.
  • 6’2″ guard Sterling Gibbs has been terrific scoring and distributing the ball, but he’s allergic to rebounds (1.7% OR and 3.9% DR). His DR% is easily the worst among all Big East regulars (next worst is at 5.7%).
  • 6’6″ freshman Desi Rodriguez doesn’t get the minutes that Delgado does, but he’s also been very strong on the boards (8.8% OR; 20.3% DR).
  • True, Marquette allows a lot of offensive rebounds for opponents, but in Big East play the Warriors have a 35.1% Def OR%, a fair amount better than Seton Hall’s Def OR% of 38.7%.
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Minnesota: Conference Advanced Player Stats

Minnesota: Conference Advanced Player Stats

Notes and details on the Gophers’ team and player stats (see PDF) through the first four Big Ten games are included in this article.

Eff. eFG% TO% OR% FTR
Minnesota 96.0 45.8% 21.0% 35.6% 33.5%
Opponents 104.6 49.8% 20.4% 34.6% 40.5%

Minnesota’s eFG% lags far behind their opponents, but in two of their four losses the Gophers have shot better than the other team.

at Purdue – 72-68 loss: Minnesota was the better shooting team, but Purdue held slight edges in turnovers and rebounding and a big advantage in free throw rate.

at Maryland – 70-58 loss: The Gophers shot a miserable 36.1 eFG%, the worst performance of any Richard Pitino-coached team (including FIU).

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Gophers: 2014 vs. 2013 Nonconference Advanced Stats

Gophers: 2014 vs. 2013 Nonconference Advanced Stats

First off, there is a lack of strength at the top of the Big Ten. A mediocre team can absolutely finish in the conference’s top 4 and the margin of error for a team to finish 8-10 instead of 10-8 is small.

The Gophers have an excellent opportunity given this season, but so do a number of their peers.

Late Night Hoops calculated advance statistical data for both the team and individual players for pre-conference, non-conference games against D-I opponents. In other words, we calculated statistics for the first 12 games of this year (excluding Franklin Pierce) and compared them to last year (excluding Chaminade). Although Minnesota’s efficiency margin (offensive efficiency less defensive efficiency) is higher this season, we see reason for concern. (See also: Does Minnesota Have an Assist Problem?)

OFFENSE Eff. eFG% TO% OR% FTR
2014 110.38 55.4% 18.7% 30.1% 35.6%
2013 114.17 51.0% 16.3% 36.4% 39.9%

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