Kansas at Oklahoma (Norman, OK)| | Kansas | Oklahoma
| Performance Indicators
| | | Record (conference)
| 22-5 (11-1) | 25-2 (11-1) | | AP Rank | 15 (last week)
| 2 (last week)
| Pomeroy Rating (Updated daily) | 10
| 18
| Consensus Ranking (Updated periodically - avg several computer ratings and polls) | 12 (last week) | 4 (last week)
| Best opponents defeated this season (Ranking from Pomeroy) | vs Washington (#16) W 73-54 Home and Away vs Kansas St. (#37) | vs Purdue (#17) W 87-82 (OT) vs Texas (#25) W 78-63 | RPI (Used for schedule strength, not team strength. Current and forecast RPI from RPIForecast .) | Current: 7 Forecast: 8 | Current: 2 Forecast: 2 | Prediction Models | | | | Vegas Oddsmakers | | Win by 4.0 Est. Projection: TBD
| Prediction Tracker (Average of several power ratings) | | Win by 5.4
| | Sagarin Power Ratings (Predictor) | | Win by 3.5 | Pomeroy (Efficiency and Tempo-Adjusted) | | Win 76-73 61% chance of victory | TeamRankings.com
(Use home rating for home team, road for road. If fewer than 3 games played at corresponding locations, use "predictive" ratings for both teams but use specific home advantage rather than standard average homecourt advantage for all NCAA teams.) | | Win by 6.8
| AccuScore Game Forecast
(Models how players and coaches have individually responded to similar conditions. Games are then simulated play-by-play over 10,000 times.) | | Win by 7.2 Est. Projection: 77-69 72% chance of victory
| Last 7 Games (Venue Adjusted) (Uses team performance and consistency over last 5 home/non-home games, whichever pertains to this game + 2 other most recent games regardless of location. NEW - This takes offense and defense into account separately to reflect how consistent teams have played on each end of the court) | Win by 3.2 Est. Projection: 78-75 59% chance of victory | | Weighted Average of All Models Above (40% Vegas + 8% Pred Trckr + 8% SagPred + 8% Pom + 8 % TmRnkgs + 8% Accu + 20% Last 7) | | Win by 3.0 Est. Projection: 77-74 |
PSAN-Related Player Ratings - Cumulative This Season(PSAN-O = Offensive impact, PSAN-D = Defensive impact. For PSAN-D, lower ratings are better. PSAN70 ratings are just PSAN expressed as "per 70 possessions" to reflect efficiency. The difference between ePSAN and PSAN is that "e" is enhanced and weighs recent games more - used for Kansas only.) Kansas Impact Ratings
| PLAYER | ePSAN-O | ePSAN-D | ePSAN-Comp | | Cole Aldrich | 84.51 | -90.21 | 174.72 | | Brady Morningstar | 42.88 | -33.16 | 76.04 | | Sherron Collins | 45.05 | -24.84 | 69.89 | | Marcus Morris | 18.24 | -31.06 | 49.30 | | Markieff Morris | 13.25 | -22.77 | 36.01 | | Tyrel Reed | 20.87 | -12.84 | 33.70 | | Tyshawn Taylor | 16.03 | -15.47 | 31.50 | | Mario Little | 20.62 | -7.03 | 27.65 | | Travis Releford* | 3.08 | -6.78 | 9.87 | | Quintrell Thomas* | -0.67 | -3.95 | 3.28 | | Matt Kleinmann* | 1.85 | -1.22 | 3.06 | | Chase Buford* | -0.94 | -0.34 | -0.60 | | Jordan Juenemann* | -0.66 | 0.22 | -0.87 | | Tyrone Appleton* | -1.28 | 0.69 | -1.98 | | Brennan Bechard* | -1.49 | 0.82 | -2.31 | | Conner Teahan* | -6.49 | -2.15 | -4.34 | Efficiency Ratings
| PLAYER | ePSAN70-O | ePSAN70-D | ePSAN70-Comp | | Cole Aldrich | 4.22 | -4.51 | 8.73 | | Matt Kleinmann* | 3.01 | -1.98 | 4.99 | | Mario Little | 3.28 | -1.12 | 4.40 | | Marcus Morris | 1.51 | -2.56 | 4.07 | | Markieff Morris | 1.35 | -2.32 | 3.67 | | Brady Morningstar | 2.03 | -1.57 | 3.61 | | Sherron Collins | 1.92 | -1.06 | 2.98 | | Tyrel Reed | 1.47 | -0.90 | 2.37 | | Travis Releford* | 0.68 | -1.49 | 2.17 | | Tyshawn Taylor | 0.96 | -0.92 | 1.88 | | Quintrell Thomas* | -0.26 | -1.52 | 1.27 | | Tyrone Appleton* | -1.45 | 0.78 | -2.23 | | Chase Buford* | -3.77 | -1.35 | -2.42 | | Conner Teahan* | -4.58 | -1.51 | -3.06 | | Brennan Bechard* | -5.21 | 2.89 | -8.10 | | Jordan Juenemann* | -6.25 | 2.06 | -8.31 | * Rating not based on enough data. | Oklahoma Impact Ratings | PLAYER | PSAN-O | PSAN-D | PSAN-Comp | | Blake Griffin | 103.77 | -98.48 | 202.25 | | Taylor Griffin | 45.61 | -22.14 | 67.75 | | Austin Johnson | 48.52 | -6.96 | 55.48 | | Willie Warren | 72.23 | 16.86 | 55.38 | | Cade Davis | 25.46 | 3.45 | 22.01 | | Juan Pattillo | 12.32 | -8.14 | 20.47 | | Tony Crocker | 29.01 | 12.33 | 16.68 | | Omar Leary* | 4.78 | -6.12 | 10.89 | | Ray Willis* | 2.89 | -7.17 | 10.07 | | Ryan Wright* | -5.04 | -13.61 | 8.57 | | Orlando Allen* | 3.64 | -2.96 | 6.59 | | Kyle Cannon* | -1.91 | -3.15 | 1.24 | | Beau Gerber* | 1.11 | 0.25 | 0.85 | | T.J. Franklin* | -7.22 | -1.19 | -6.04 | Efficiency Ratings | PLAYER | PSAN70-O | PSAN70-D | PSAN70-Comp | | Blake Griffin | 4.88 | -4.63 | 9.50 | | Juan Pattillo | 3.28 | -2.17 | 5.45 | | Ray Willis* | 1.19 | -2.94 | 4.13 | | Orlando Allen* | 2.10 | -1.71 | 3.81 | | Taylor Griffin | 2.34 | -1.14 | 3.48 | | Austin Johnson | 2.41 | -0.35 | 2.75 | | Willie Warren | 3.53 | 0.82 | 2.70 | | Cade Davis | 2.62 | 0.36 | 2.27 | | Omar Leary* | 0.84 | -1.07 | 1.91 | | Beau Gerber* | 2.07 | 0.47 | 1.59 | | Ryan Wright* | -0.92 | -2.47 | 1.56 | | Tony Crocker | 1.49 | 0.63 | 0.86 | | Kyle Cannon* | -1.28 | -2.12 | 0.84 | | T.J. Franklin* | -12.34 | -2.03 | -10.31 | * Rating not based on enough data. |
Last 7 Game Analysis | | Kansas | Oklahoma | | Expected Score | 78.4 | 75.0 | | Win | 58.7% | 41.3% | | Win by 3 or less | 8.2% | 7.3% | | Win by 10 or more | 33.1% | 19.2% | Down to the Wire?
Margin of game was less than 1 point in 5.1% of simulated games from "Last 7 Game Analysis." Many of these would be "overtime" games. (Methodology of Last 7 Game Analysis: Here, we look at the last seven venue-appropriate games to see how the teams are performing. If the game takes place on the road for Kansas, for example, the analysis looks at the five most recent non-home games for Kansas. In addition, the two most recent games, regardless of venue, are added. That way, we get a picture of the how the team is performing of late. This season, the analysis also splits offense and defense. Teams often are more or less consistent on one side of the court than the other. This analysis will reflect that. Based on the strength of the opposing offense and defense they've played over the last seven games, each team's offense and defense is evaluated based on strength and consistency. Those numbers are then plugged into a simulation of 8,000 games. The results are what you see in the table.) Opponent Four Factor Analysis
Based on the cumulative season boxscore for the opponent, we can look at the Four Factors to see where the team has derived the bulk of its (dis)advantage in terms of scoring margin versus its opponents to date. Team 1 is KU's opponent, while Team 2 represents that team's opponents. Here is the breakdown for KU's opponent this game: | | Team 1 | Team 2 | Advantage | | | eFG% | 55.20% | 45.24% | 314.5 | | | TO Rate | 18.90% | 19.12% | 4.3 | | | OREB% | 36.45% | 32.47% | 41.7 | | | FTA/FGA | 46.71% | 28.77% | 5.1 | FT Pct | | | | | 161.9 | FT Attempts | ANALYSIS: Like most elite teams, Oklahoma gets most of its advantage from getting better shots, thus shooting a much better percentage from the field. But in OU's case, they are phenomenal at getting to the FT line much more often than their opponents. Statistical Strengths and Weaknesses Analysis(Note: These are based on raw statistics that are unadjusted for strength of opposition.) | ** Denotes that team with advantage also ranks in Top 50 in that category | | Clear Advantage for Kansas | No Clear Advantage | Clear Advantage for Oklahoma | | Kansas 3pt FG%** | | | | Kansas OREB** | | | | | Kansas FT% | | | | Kansas PTS/Poss | | | | Oklahoma OREB | | | | Kansas TO rate | | | | Kansas eFG% | | | | Oklahoma 3pt FG% | | | | Oklahoma eFG% | | | | Oklahoma 2pt FG% | | | | Oklahoma PTS/Poss | | | | Kansas 2pt FG% | | | | Oklahoma % own 2FGA's blocked | | | | Kansas FT Rate | | | | Kansas % own 2FGA's blocked | | | | Oklahoma % Poss STL by Opp | | | | Oklahoma FT% | | | | Kansas % Poss STL by Opp | | | | | Oklahoma TO rate | | | | Oklahoma FT Rate** | ************************************************************* | Oklahoma will have above avg % of FG's assisted | | Expect uptempo game | |
Game Projections(Not a prediction. Read more details in "FAQ & Terms" section.) Manual adjustments: None.
Projected Boxscore | Kansas | 70 | | | | | | | | | | | | | | | | Oklahoma | 70 | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Kansas | | | | | | | | | | | | | | | | | PLAYER | MIN | 2FGM | 2FGA | 3FGM | 3FGA | FTM | FTA | PTS | OREB | DREB | TREB | AST | TO | STL | BLK | | Brady Morningstar | 32 | 1 | 2 | 2 | 4 | 1 | 1 | 9 | 1 | 2 | 3 | 2 | 1 | 1 | 0 | | Cole Aldrich | 31 | 5 | 9 | 0 | 0 | 3 | 4 | 13 | 3 | 7 | 10 | 1 | 2 | 1 | 2 | | Marcus Morris | 19 | 2 | 5 | 0 | 1 | 2 | 3 | 6 | 2 | 3 | 5 | 1 | 2 | 1 | 0 | | Mario Little | 9 | 2 | 3 | 0 | 1 | 1 | 1 | 5 | 1 | 2 | 3 | 1 | 1 | 0 | 0 | | Markieff Morris | 16 | 1 | 3 | 0 | 0 | 1 | 2 | 3 | 2 | 2 | 4 | 1 | 1 | 1 | 1 | | Sherron Collins | 37 | 3 | 8 | 2 | 6 | 4 | 4 | 16 | 0 | 2 | 2 | 4 | 4 | 1 | 0 | | Travis Releford | 6 | 1 | 2 | 0 | 0 | 0 | 1 | 2 | 1 | 1 | 2 | 0 | 1 | 0 | 0 | | Tyrel Reed | 23 | 0 | 1 | 2 | 4 | 1 | 2 | 7 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | | Tyshawn Taylor | 27 | 2 | 4 | 1 | 2 | 2 | 3 | 9 | 0 | 2 | 2 | 3 | 3 | 1 | 0 | | TOTALS | 200 | 17 | 37 | 7 | 18 | 15 | 21 | 70 | 10 | 22 | 32 | 14 | 16 | 7 | 3 | | | | | | | | | | | | | | | | | | | Oklahoma | | | | | | | | | | | | | | | | | PLAYER | MIN | 2FGM | 2FGA | 3FGM | 3FGA | FTM | FTA | PTS | OREB | DREB | TREB | AST | TO | STL | BLK | | Austin Johnson | 33 | 1 | 3 | 1 | 3 | 1 | 2 | 6 | 0 | 2 | 2 | 4 | 2 | 2 | 1 | | Blake Griffin | 34 | 6 | 12 | 0 | 0 | 6 | 11 | 18 | 3 | 8 | 11 | 2 | 4 | 1 | 1 | | Cade Davis | 16 | 0 | 1 | 1 | 4 | 1 | 1 | 4 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | | Juan Pattillo | 9 | 2 | 4 | 0 | 0 | 2 | 2 | 6 | 1 | 2 | 3 | 0 | 1 | 1 | 1 | | Omar Leary | 6 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | | Ryan Wright | 6 | 1 | 1 | 0 | 0 | 1 | 2 | 3 | 1 | 1 | 2 | 0 | 1 | 0 | 0 | | Taylor Griffin | 32 | 2 | 5 | 0 | 0 | 3 | 4 | 7 | 2 | 3 | 5 | 1 | 2 | 1 | 1 | | Tony Crocker | 31 | 1 | 3 | 2 | 5 | 2 | 2 | 10 | 1 | 2 | 3 | 1 | 2 | 1 | 0 | | Willie Warren | 33 | 3 | 5 | 2 | 5 | 4 | 5 | 16 | 0 | 1 | 1 | 3 | 2 | 1 | 0 | | TOTALS | 200 | 16 | 34 | 6 | 18 | 20 | 29 | 70 | 8 | 20 | 28 | 13 | 15 | 8 | 4 | Projection Summary | | Projection | Comments | OVERALL RESULTS | | Final Score | Tie 70-70 (Oklahoma wins in overtime) | Projected tie goes to OU in overtime given OU's raw calculated advantage of 70.8 to 70.7 before adjustments to better fit player averages. | Tempo (# poss)
| 71 (in regulation)
| | FOUR FACTORS ADVANTAGES
| | eFG% | KU 50-48% | | | TO Rate (lo better) | OU 23-21% |
| | O-Reb% | KU 33-27%
| | | FT Rate | OU 56-38%
| | Four Factors Overall
| Every category is pretty tight, with the exception of FT attempts in favor of OU. But they all roughly even out ... this is projected to be close. |
| PLAYER PROJECTIONS (10+ min played) | | Leading Scorers | KU - Collins, Aldrich Opp - B. Griffin, Warren | | Highest PSAN-Comp (game impact)
| KU - Aldrich Opp - B. Griffin | | Highest PSAN70-Comp (efficiency)
| KU - Aldrich Opp - B. Griffin | | | Highest efficiency vs season-to-date | KU - Markieff Morris, Morningstar Opp - Warren, Crocker | | | Lowest efficiency vs season-to-date | KU - Marcus Morris, Collins Opp - B. Griffin, Davis | Even though he's projected to have the best game for OU, he may struggle more than anyone else compared to his season average. |
Sports and Numbers ProjectionTie in Regulation 70-70 Oklahoma wins in overtime (all prediction models included/complete) |
Adjustment If Blake Griffin (OU) Does Not Play The dynamics of the game would adjust in a way that is too difficult to assess quantitatively in any automated way. What we can attempt to do is replace the efficiency of Blake Griffin with that of those players whose minutes would presumably increase. The offensive and defensive efficiencies would translate into point differentials expected on either side of the ball with Griffin out. One important caveat to this is that the "whole is not equal to the sum of the parts" in this case. The team will operate differently, and most likely the removal of Griffin would mean more than just the removal of his usual ratings impact. But in this case, we are simply trying to find a quantitative estimate of the impact of his absence. Blake Griffin's offensive efficiency (PSAN70-O) of +4.88 translates to a +4.21 points impact in this game. This accounts for the fact that he was projected to play 34 of the available 40 minutes, but also that the tempo woud be 71 possessions instead of the standard 70 used in the efficiency ratings. On defense, he was to have a -3.99 effect on KU's points. Thus, the loss of Griffin results in a net differential of 8.2 points in favor of Kansas. However, those 34 minutes will be played by other players, most of whom have positive efficiency ratings. By increasing all other player minutes by a proportional amount, calculating each of those player's changes in impact as a result of the increased playing time, we can see what the overall change in score is projected to be when Blake Griffin's minutes are replaced. The analysis shows that Blake's brother, Taylor, picks up more slack than anyone else, although it isn't much. Taylor Griffin's net impact projects to be +0.53 higher with the increased playing time, while Warren's projects to be +0.48 points better. Johnson comes in just above +0.4, while Pattillo and Davis each project to add about a quarter of a point. The net impact of the loss of Griffin is thus -2.2 on offense for OU and +3.86 more points for KU. That means the scoring margin would shift approximately 6 points in favor of Kansas with Griffin out. Without changing the overall points scored, that would project to a 73-67 KU victory. |