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Preview: Texas Tech at Kansas Print E-mail
Jan 16, 2010

Texas Tech at Kansas (Lawrence, KS)

  Kansas Texas Tech

Performance Indicators

   
Record (conference)
15-1 (1-0) 12-4 (0-2)
AP Rank 3
NR
(40th most votes)
Pomeroy Rating
(Updated daily)
2
89
Consensus Ranking
(Updated periodically - avg several computer ratings and polls)
2
67
Best opponents defeated this season
(Ranking from Pomeroy)

vs California (#17) W 84-69
@ Temple (#26) W 84-52

vs UTEP (#62) W 86-78
vs Washington (#68) W 99-92 OT
RPI
(Used for schedule strength, not team strength. Current and forecast RPI from RPIForecast .)

Current: 3

Forecast: 2

Current: 48

Forecast: 66

Projected NCAA Tournament Seed
(Latest consensus from The Bracket Matrix)
 #1 Seed
 One of "First Four Out"

Prediction Models

   
Vegas Oddsmakers Win by 21.0
Est. Projection: 89-68
 
Prediction Tracker
(Average of several power ratings)
 Win by 19.56
 
Sagarin Power Ratings (Predictor)  Win by 19.90  
Pomeroy
(Efficiency and Tempo-Adjusted)

 Win 93-67
98% 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 15.4  
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.  This takes offense and defense into account separately to reflect how consistent teams have played on each end of the court)
 Est. Projection: 88-73
81.8% chance of victory
 
Similar Opponent
(Examines offensive performance against similar defensive teams and defensive performance against similar offensive teams.  Threshold for similarity set at efficiencies of 5 pts/100 possessions above or below that of opponent in this game.  If necessary, threshold adjusted to find a minimum of three games to analyze for offense and defense.)
  Est. Projection: 90-71
83.4% chance of victory
 
Weighted Average of All Models Above
(40% Vegas + 10% Pred Trckr + 10% SagP + 10% Pom + 10% TmRnk + 10% SimOpp + 10% Last 7)
 Win by 20.2
Est. Projection: 89-69
 

 

 

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 32.50 -59.52 92.01
Sherron Collins 49.03 -15.81 64.84
Marcus Morris 38.07 -20.72 58.79
Xavier Henry 25.22 -28.49 53.72
Markieff Morris 25.10 -19.11 44.21
Tyrel Reed 19.83 -13.52 33.36
Tyshawn Taylor 15.68 -13.67 29.35
Brady Morningstar 15.95 -4.85 20.80
C.J. Henry* 14.59 -1.28 15.87
Elijah Johnson 9.90 -4.14 14.04
Thomas Robinson -1.62 -9.52 7.91
Conner Teahan* 1.31 -4.11 5.41
Jeff Withey* -0.51 -0.68 0.16
Jordan Juenemann* 0.16 0.45 -0.29
Chase Buford* -0.45 0.49 -0.95

 

 Efficiency Ratings

 

PLAYER ePSAN70-O ePSAN70-D ePSAN70-Comp
C.J. Henry* 8.98 -0.79 9.76
Cole Aldrich 3.13 -5.73 8.86
Markieff Morris 4.06 -3.09 7.15
Marcus Morris 3.97 -2.16 6.13
Tyrel Reed 3.39 -2.31 5.69
Sherron Collins 3.83 -1.23 5.06
Brady Morningstar 3.78 -1.15 4.93
Elijah Johnson 3.33 -1.39 4.72
Xavier Henry 2.21 -2.49 4.70
Conner Teahan* 0.95 -3.00 3.95
Tyshawn Taylor 1.58 -1.38 2.95
Thomas Robinson -0.41 -2.44 2.03
Jeff Withey* -2.10 -2.77 0.67
Jordan Juenemann* 0.44 1.25 -0.81
Chase Buford* -0.90 0.97 -1.87

 

* Rating not based on enough data.

Texas Tech

  

Impact Ratings

 

PLAYER PSAN-O PSAN-D PSAN-Comp
D'Walyn Roberts 36.86 -15.16 52.02
David Tairu 35.73 11.07 24.66
Mike Singletary 7.79 -13.97 21.76
John Roberson 23.03 2.09 20.94
Robert Lewandowski* -5.95 -12.47 6.52
Darko Cohadarevic 7.81 4.21 3.60
Wally Dunn* 0.47 -0.65 1.13
Theron Jenkins -3.30 -3.71 0.42
Corbin Ray* 0.30 0.62 -0.31
Brad Reese -7.01 -3.69 -3.32
Mike Davis* -5.10 -0.11 -5.00
Nick Okorie -8.05 -1.26 -6.79

 

 

Efficiency Ratings

 

PLAYER PSAN70-O PSAN70-D PSAN70-Comp
D'Walyn Roberts 3.67 -1.51 5.18
David Tairu 3.76 1.17 2.60
Wally Dunn* 0.79 -1.09 1.89
Robert Lewandowski* -1.63 -3.41 1.78
Mike Singletary 0.59 -1.05 1.64
John Roberson 1.56 0.14 1.42
Darko Cohadarevic 0.93 0.50 0.43
Theron Jenkins -0.71 -0.80 0.09
Brad Reese -0.91 -0.48 -0.43
Nick Okorie -0.91 -0.14 -0.76
Mike Davis* -1.95 -0.04 -1.91
Corbin Ray* 1.96 3.96 -2.01

 

* Rating not based on enough data.




Player Analysis:

(largely in context of ratings above)

 

There aren't a lot of high-impact guys for TTU.  Roberts is head and shoulders above the rest, but he uses a mere 14% of possessions when he's in.  Who will carry this team if they are to have a shot at the upset?  Tairu and Singletary are your best bets, but don't count on it.

 

 

Last 7 Game Projection

 

  Kansas Texas Tech
Expected Score 88.3 72.5
Win 81.8% 18.2%
Win by 3 or less 5.3% 4.2%
Win by 10 or more 63.3% 7.2%

 

Down to the Wire?

 Margin of game was less than 1 point in 3.0% 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.)

 

Similar Opponent Projection

 

  Kansas Texas Tech
Expected Score 89.5 71.1
Win 83.4% 16.6%
Win by 3 or less 3.9% 3.6%
Win by 10 or more 67.6% 6.7%

 

Down to the Wire?

 Margin of game was less than 1 point in 2.7% 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.)

 

 

Four Factors Breakdown

 

Based on the cumulative season boxscore for each team, we can look at the Four Factors to see where each team has derived the bulk of its (dis)advantage in terms of scoring margin versus its opponents to date.  For each team, Team 1 is the team itself and Team 2 is its opponents.  Here is the breakdown:

 

Kansas

 

  Team 1 Team 2 Advantage  
eFG% 57.77% 40.65% 323.8  
TO Rate 17.76% 20.56% 32.6  
OREB% 37.11% 27.41% 53.2  
FTA/FGA 29.29% 20.48% 11.8 FT Pct
      68.2 FT Attempts

Texas Tech

 

  Team 1 Team 2 Advantage  
eFG% 49.58% 46.40% 60.7  
TO Rate 19.92% 21.70% 21.6  
OREB% 34.47% 34.09% 2.3  
FTA/FGA 33.82% 28.47% 9.4 FT Pct
      39.6 FT Attempts

 

FOUR FACTORS ANALYSIS:  While TTU has an edge in every single category like KU, they are all very modest.  Meanwhile, the Jayhawks blow everyone away in the single most important factor, eFG%.

 

 

Four Factors Regression Analysis

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

 

Offense Statistical Significance Four Factors Rank
Overall Regression Yes  
eFG% Yes
1
TO%   2
OREB%   3
FTA/FGA   4
     
Defense    
Overall Regression Yes  
eFG% Yes
1
TO% Yes 3
OREB% Yes
2
FTA/FGA   4
Texas Tech

 

Offense Statistical Significance Four Factors Rank
Overall Regression Yes  
eFG% Yes
2
TO%   4
OREB% Yes
1
FTA/FGA Yes
3
     
Defense    
Overall Regression Yes  
eFG% Yes
1
TO% Yes 3
OREB% Yes
2

FTA/FGA

  4
 
Key Factors This Game

 

Using the p-values from the regression analyses above, we can calculate the probabability that a factor will be statistically significant in this game.

 

At least 75% likely to be important:

  • Texas Tech OREB%
  • Texas Tech eFG%
  • Kansas eFG%
  • Kansas TO%

Between 50-75% likely to be important:

  • None

 

Between 25-50% likely to be important:

  • Texas Tech FTA/FGA
  • Kansas OREB%

 

 

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 Texas Tech
Kansas FT Rate    
Kansas 3pt FG%**    
Kansas OREB**    
Texas Tech 2pt FG%**    
Texas Tech eFG%**    
Kansas % Poss STL by Opp    
Texas Tech % Poss STL by Opp**    
Kansas PTS/Poss**    
Kansas TO rate**    
Texas Tech 3pt FG%**    
  Kansas eFG%  
  Texas Tech PTS/Poss  
  Kansas 2pt FG%  
  Kansas FT%  
  Kansas % own 2FGA's blocked  
  Texas Tech OREB  
  Texas Tech FT%  
  Texas Tech % own 2FGA's blocked  
  Texas Tech TO rate  
  Texas Tech FT Rate  

 

************************************************************* 

Texas Tech will take below avg % of its FG's from 3-pt
Expect uptempo game

 

 

 

Game Projections

(Not a prediction.  Read more details in "FAQ & Terms" section.)

Manual adjustments: None.

 


Projected Boxscore

 

Kansas 89                            
Texas Tech 67                            
                               
Kansas                              
PLAYER MIN 2FGM 2FGA 3FGM 3FGA FTM FTA PTS OREB DREB TREB AST TO STL BLK
Brady Morningstar 21 1 1 1 2 0 1 5 0 1 1 3 1 1 0
Cole Aldrich 26 4 8 0 0 4 5 12 4 7 11 1 2 1 2
Elijah Johnson 8 1 2 0 1 1 1 3 1 1 2 2 1 0 0
Marcus Morris 24 4 6 1 1 3 5 14 2 3 5 1 1 1 0
Markieff Morris 15 2 4 0 1 2 3 6 2 3 5 1 1 1 1
Sherron Collins 32 3 7 2 5 4 4 16 0 2 2 3 2 1 0
Thomas Robinson 9 1 3 0 0 1 3 3 2 2 4 0 1 0 1
Tyrel Reed 12 1 1 1 3 0 0 5 0 1 1 1 1 1 0
Tyshawn Taylor 25 2 5 1 2 2 3 9 1 2 3 3 2 1 0
Xavier Henry 28 3 6 2 5 4 5 16 1 3 4 1 2 2 0
TOTALS 200 22 43 8 20 21 30 89 13 25 38 16 14 9 4
                               
Texas Tech                              
PLAYER MIN 2FGM 2FGA 3FGM 3FGA FTM FTA PTS OREB DREB TREB AST TO STL BLK
Brad Reese 19 1 4 1 3 1 1 6 0 1 1 1 2 1 1
Darko Cohadarevic 21 2 6 0 0 1 1 5 3 3 6 1 2 0 0
David Tairu 24 3 6 1 2 3 3 12 2 2 4 1 1 0 0
D'Walyn Roberts 25 2 5 0 0 2 3 6 3 4 7 0 1 0 1
John Roberson 37 2 5 2 6 3 4 13 0 2 2 5 3 2 0
Mike Davis 5 0 0 0 1 0 1 0 1 0 1 0 0 0 0
Mike Singletary 33 4 7 0 2 5 7 13 1 5 6 2 4 1 1
Nick Okorie 23 1 5 1 3 2 3 7 0 2 2 2 2 1 0
Robert Lewandowski 6 1 2 0 0 0 1 2 1 1 2 0 1 0 0
Theron Jenkins 7 1 3 0 0 1 1 3 1 1 2 1 1 1 0
TOTALS 200 17 43 5 17 18 25 67 12 21 33 13 17 6 3

 

 

Projection Summary

 

 
Projection
Comments

 OVERALL RESULTS

 Final Score  KU 89-67  
 Tempo (# poss)
 77 

 FOUR FACTORS ADVANTAGES

 eFG%  KU 54-41%  
 TO Rate (lo better)  KU 22-18%  Hard to believe KU will force this many TO's given recent trends (3 of last 4 opp had <15%)
 O-Reb% KU 38-32%
 
 FT Rate KU 48-42%
 
 Four Factors Overall
 Mostly the eFG% edge, but a little bit in other categories to help give KU a blowout victory.
 
 

PLAYER PROJECTIONS (10+ min played)

 Leading Scorers

 KU - Collins/X. Henry

 Opp - Roberson/Singletary

 
 Highest PSAN-Comp
(game impact)

 KU - Aldrich

 Opp - Tairu

 
 Highest PSAN70-Comp
(efficiency)

 KU - Aldrich

 Opp - Tairu

 
 Highest efficiency vs season-to-date

 KU - Marcus Morris

 Opp - Tairu, Singletary

 
 Lowest efficiency vs season-to-date

 KU - Collins, Markieff Morris

 Opp - Roberts, Okorie

 

 

Sports and Numbers Projection

Kansas wins 89-67

(all prediction models included/complete)

 

 

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