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| Preview: Kansas at Texas |
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| Feb 8, 2010 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kansas at Texas (Austin, TX)
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.)
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| Kansas | Texas | |
| Expected Score | 88.5 | 77.2 |
| Win | 71.4% | 28.6% |
| Win by 3 or less | 4.9% | 5.0% |
| Win by 10 or more | 53.0% | 14.7% |
Margin of game was less than 1 point in 3.5% 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.)
| Kansas | Texas | |
| Expected Score | 85.0 | 77.2 |
| Win | 64.6% | 35.4% |
| Win by 3 or less | 5.5% | 5.3% |
| Win by 10 or more | 45.9% | 19.8% |
Margin of game was less than 1 point in 3.3% of simulated games from "Last 7 Game Analysis." Many of these would be "overtime" games.
(Methodology of Similar Opponent Analysis: Here, we look at games against opponents with similar offensive and defensive profiles to the opponent of interest to see how the teams are performing. For Kansas, we would look at its offensive performances against teams that have a defense that is within 5 pts/100 possessions efficiency above or below that of the opponent in this game. If this does not result in at least three appropriate comparisons, the threshold will be adjusted until it finds three. If there are more than three that are within the original threshold, all of those will be used. The same is done for defense but using offensive profiles of opponents. The analysis 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. Those numbers are then plugged into a simulation of 8,000 games. The results are what you see in the table.)
KenPom.com's "Game Plan" feature shows the Four Factors results for every game a team has played. Below the results, there is a table with correlation coefficients that show how closely related each of the Four Factors is to a team's offensive and defensive efficiency (both for itself and its opponent). Unfortunately, the correlations are based on raw efficiencies, which of course has much less value because a team's true efficiency is significantly affected by the strength of the opponent. Below, I have taken each team's Four Factors results and run a multiple regression analysis with the Four Factors as the variables of interest and the adjusted efficiencies as the outcome of interest to see whether a team's eFG%, for example, is related to its true offensive efficiency.
Statistical Significance = There is less than a 10% chance that the relationship between this statistic and the team's adjusted offensive or defensive efficiency is due merely to chance.
Four Factors Rank = In ascending order, which of the Four Factors has the lowest chance of being related to efficiency due merely to chance (i.e., best significance).
Kansas
This team's offensive efficiency (points per 100 poss.) can be estimated by the following equation:
1.0*eFG% - 0.71*TO% -0.80*oppTO% + 0.44*oppFTR + 81.05 Standard Error: 9.28
This team's defensive efficiency (points allowed per 100 poss.) can be estimated by the following equation:
1.04*OppeFG% - 0.60*OppTO% + 0.35*OppOREB% + 0.45*eFG% + 18.01 Standard Error: 5.30 | Texas
This team's offensive efficiency (points per 100 poss.) can be estimated by the following equation:
1.10*eFG% - 1.55*TO% + 0.41*OppeFG% + 65.61 Standard Error: 5.69
This team's defensive efficiency (points allowed per 100 poss.) can be estimated by the following equation:
1.37*OppeFG% + 26.18 Standard Error: 5.73 | |
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Statistical Strengths and Weaknesses Analysis(Note: These are based on raw statistics that are unadjusted for strength of opposition.)
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(Not a prediction. Read more details in "FAQ & Terms" section.)
Manual adjustments: Brady Morningstar to play 15 minutes. His end-of-season stats from last year are used for this projection.
| Kansas | 78 | ||||||||||||||
| Texas | 76 | ||||||||||||||
| Kansas | |||||||||||||||
| PLAYER | MIN | 2FGM | 2FGA | 3FGM | 3FGA | FTM | FTA | PTS | OREB | DREB | TREB | AST | TO | STL | BLK |
| Brady Morningstar | 26 | 1 | 2 | 1 | 2 | 1 | 1 | 6 | 1 | 2 | 3 | 3 | 2 | 1 | 0 |
| Cole Aldrich | 27 | 4 | 8 | 0 | 0 | 4 | 4 | 12 | 4 | 8 | 12 | 1 | 2 | 1 | 3 |
| Marcus Morris | 26 | 5 | 8 | 0 | 1 | 3 | 5 | 13 | 3 | 4 | 7 | 1 | 1 | 1 | 0 |
| Markieff Morris | 16 | 2 | 4 | 0 | 1 | 1 | 3 | 5 | 2 | 4 | 6 | 1 | 1 | 1 | 1 |
| Sherron Collins | 33 | 3 | 7 | 2 | 5 | 3 | 4 | 15 | 0 | 2 | 2 | 3 | 3 | 1 | 0 |
| Thomas Robinson | 6 | 1 | 3 | 0 | 0 | 1 | 2 | 3 | 1 | 2 | 3 | 0 | 1 | 0 | 1 |
| Tyrel Reed | 16 | 0 | 1 | 1 | 3 | 0 | 0 | 3 | 0 | 1 | 1 | 1 | 1 | 1 | 0 |
| Tyshawn Taylor | 23 | 2 | 4 | 1 | 2 | 2 | 3 | 9 | 1 | 2 | 3 | 3 | 2 | 1 | 0 |
| Xavier Henry | 27 | 2 | 6 | 2 | 5 | 2 | 3 | 12 | 1 | 3 | 4 | 2 | 3 | 2 | 1 |
| TOTALS | 200 | 20 | 43 | 7 | 19 | 17 | 25 | 78 | 13 | 28 | 41 | 15 | 16 | 9 | 6 |
| Texas | |||||||||||||||
| PLAYER | MIN | 2FGM | 2FGA | 3FGM | 3FGA | FTM | FTA | PTS | OREB | DREB | TREB | AST | TO | STL | BLK |
| Alexis Wangmene | 6 | 1 | 2 | 0 | 0 | 1 | 1 | 3 | 1 | 1 | 2 | 0 | 0 | 0 | 1 |
| Avery Bradley | 30 | 3 | 8 | 2 | 4 | 1 | 1 | 13 | 1 | 2 | 3 | 2 | 2 | 1 | 0 |
| Damion James | 32 | 5 | 11 | 1 | 3 | 4 | 7 | 17 | 4 | 7 | 11 | 1 | 3 | 2 | 1 |
| Dexter Pittman | 22 | 4 | 7 | 0 | 0 | 2 | 4 | 10 | 4 | 3 | 7 | 1 | 2 | 0 | 2 |
| Dogus Balbay | 25 | 1 | 3 | 0 | 1 | 1 | 2 | 3 | 1 | 2 | 3 | 4 | 2 | 1 | 1 |
| Gary Johnson | 23 | 3 | 6 | 0 | 0 | 2 | 2 | 8 | 2 | 3 | 5 | 1 | 1 | 0 | 0 |
| J'Covan Brown | 24 | 1 | 4 | 2 | 5 | 2 | 3 | 10 | 1 | 2 | 3 | 2 | 3 | 1 | 0 |
| Jordan Hamilton | 19 | 1 | 4 | 2 | 5 | 1 | 2 | 9 | 1 | 2 | 3 | 2 | 1 | 1 | 0 |
| Justin Mason | 19 | 1 | 3 | 0 | 1 | 1 | 2 | 3 | 1 | 1 | 2 | 2 | 1 | 1 | 0 |
| TOTALS | 200 | 20 | 48 | 7 | 19 | 15 | 24 | 76 | 16 | 23 | 39 | 15 | 15 | 7 | 5 |
Projection | Comments | |
OVERALL RESULTS | ||
| Final Score | KU 78-76 | |
| Tempo (# poss) | 76 | |
FOUR FACTORS ADVANTAGES | ||
| eFG% | KU 49-46% | |
| TO Rate (lo better) | UT 21-20% | |
| O-Reb% | UT 36.4-36.1% | |
| FT Rate | KU 40-36% | |
| Four Factors Overall | Pretty even across the board, with just under a 5-point edge in eFG% being the difference for KU. | |
PLAYER PROJECTIONS (10+ min played) | ||
| Leading Scorers | KU - Collins, Marcus Morris Opp - James, Bradley | |
| Highest PSAN-Comp (game impact) | KU - Aldrich Opp - James | |
| Highest PSAN70-Comp (efficiency) | KU - Aldrich Opp - Pittman | |
| Highest efficiency vs season-to-date | KU - Taylor, Aldrich Opp - Brown, Hamilton | Looks like KU is really banking on Aldrich this game. Look to see if he is in foul trouble or playing passively and not getting his shots. |
| Lowest efficiency vs season-to-date | KU - Reed, Collins Opp - Balbay, Mason | Reed to struggle based on limited shooting. Making one shot would be a big difference here. Collins is another story. |
Sports and Numbers ProjectionKansas wins 78-76(all prediction models included/complete) |
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