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Preview: Siena at Kansas Print E-mail
Jan 5, 2009

Siena at Kansas (Lawrence, KS)

 KansasSiena

Performance Indicators

  
Record10-310-4
AP RankNR
(37th most votes)
NR
Pomeroy Rating
(Updated daily)
1771
Consensus Ranking
(Updated periodically - avg several computer ratings and polls)
42 64
Best opponents defeated this season
(Ranking from Pomeroy)

vs Washington (#18) W 73-54
vs Tennessee (#22) W 92-85

none vs Top 100
RPI
(Used for schedule strength, not team strength. Current and forecast RPI from RPIForecast .)

Current: 64

Forecast: 19

Current: 43

Forecast: 44

Prediction Models

  
Vegas OddsmakersWin by 12
Est. Projection: 80-68 
 
Prediction Tracker
(Average of several power ratings)
 Win by 11.9
 
Sagarin Power Ratings (Predictor)Win by 11.7 
Pomeroy
(Efficiency and Tempo-Adjusted)

Win 74-62
89% chance of victory

 
 TeamRankings.com
(Use home rating for home team, road for road, specific home advantage for home team.  If fewer than 3 games played at corresponding locations, use "predictive" ratings for both teams but still use specific home advantage if home team has played >3 home games.)
 Win by 17.8 
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)
 Est. Projection: 78-68
76% chance of victory
 
Weighted Average of All Models Above
(40% Vegas + 10% Pred Trckr + 10% SagPred + 10% Pom + 10% TmRnkgs.com +10% Last 7)

 Win by 12.3
Est. Projection: 78-66

 

 

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 46.89 -37.32 84.21
Brady Morningstar 22.44 -7.13 29.57
Sherron Collins 15.07 -11.58 26.66
Marcus Morris 8.14 -16.79 24.93
Tyshawn Taylor 10.93 -12.04 22.97
Markieff Morris 5.09 -11.71 16.80
Tyrel Reed 9.41 -6.38 15.79
Travis Releford* 5.75 -4.54 10.29
Quintrell Thomas* 4.07 -5.84 9.91
Matt Kleinmann* 1.80 -0.35 2.15
Chase Buford* 1.16 0.20 0.96
Tyrone Appleton* 0.44 0.20 0.25
Mario Little -1.54 -1.10 -0.44
Conner Teahan* -4.05 -3.13 -0.93
Jordan Juenemann* -1.01 0.33 -1.34
Brennan Bechard* -2.79 0.21 -3.00

 

 Efficiency Ratings

 

PLAYER ePSAN70-O ePSAN70-D ePSAN70-Comp
Cole Aldrich 5.26 -4.19 9.45
Chase Buford* 5.62 0.99 4.63
Travis Releford* 2.33 -1.84 4.18
Quintrell Thomas* 1.67 -2.40 4.08
Marcus Morris 1.25 -2.57 3.82
Matt Kleinmann* 2.94 -0.58 3.52
Brady Morningstar 2.49 -0.79 3.28
Markieff Morris 0.90 -2.08 2.99
Tyshawn Taylor 1.23 -1.36 2.59
Sherron Collins 1.35 -1.04 2.39
Tyrel Reed 1.30 -0.88 2.19
Tyrone Appleton* 0.71 0.32 0.40
Conner Teahan* -2.49 -1.92 -0.57
Mario Little -4.44 -3.18 -1.26
Brennan Bechard* -10.84 0.81 -11.66
Jordan Juenemann* -10.11 3.34 -13.45

 

* Rating not based on enough data.

Siena

  

Impact Ratings

 

PLAYER PSAN-O PSAN-D PSAN-Comp
Ryan Rossiter 24.83 -15.15 39.98
Alex Franklin 20.81 -12.23 33.03
Edwin Ubiles 7.86 -13.66 21.52
Kyle Downey* 11.38 -3.45 14.83
Owen Wignot 4.18 -5.76 9.95
Steven Priestley* 1.99 -6.14 8.13
Erik Harris* 4.48 -0.54 5.01
Josh Duell 3.17 1.35 1.82
Ronald Moore -0.09 -1.28 1.19
Conner Fenlon* 0.00 0.00 0.00
Kenny Hasbrouck -15.30 -4.33 -10.97
Clarence Jackson -9.66 2.56 -12.22

 

 

 

Efficiency Ratings

 

PLAYER PSAN70-O PSAN70-D PSAN70-Comp
Steven Priestley* 2.24 -6.92 9.16
Erik Harris* 4.77 -0.57 5.35
Ryan Rossiter 2.94 -1.79 4.74
Kyle Downey* 3.32 -1.01 4.33
Alex Franklin 1.84 -1.08 2.92
Owen Wignot 1.07 -1.48 2.55
Edwin Ubiles 0.67 -1.17 1.85
Josh Duell 0.80 0.34 0.46
Ronald Moore -0.01 -0.12 0.11
Conner Fenlon* 0.00 0.00 0.00
Kenny Hasbrouck -1.48 -0.42 -1.06
Clarence Jackson -1.86 0.49 -2.35

 

* Rating not based on enough data.




Player Analysis:

(largely in context of ratings above)

 

Siena has surprised some people with their strong season thus far.  The bulk of the contributions have come from Rossiter and Franklin, but Rossiter has been much more efficient.  While both shoot the ball similarly well from the field, Rossiter has the edge in FT%, OREB% and BLK.  On paper, it is clear that Siena doesn't have the roster talent to compete if KU is playing well.  Given the inconsistency we've seen from the Jayhawks this season though (bottom 25% in country), you just never know which KU team will show up, particularly after an emotional victory over Tennessee three days earlier.

 

If Siena is to have a chance, they must limit the damage that some of their negative rated players inflict.  For a guy shooting 40 eFG%, Hasbrouck sure uses up a lot of possessions (24.3%).  But then, he's a senior guard who is used to shooting above 50 eFG% and having much better overall efficiency on offense.  In a game like this, he could actually be the guy who steps it up.  You can't say the same for Jackson, a sophomore guard, who uses up even more possessions (27.9%) while shooting only 46 eFG%.  While Hasbrouck balances his TO's with roughly equal AST numbers, Jackson has an anemic 0.2 AST:TO ratio.  You're not in good hands there. 

 

 

Last 7 Game Analysis

 

  Kansas Siena
Expected Score 78.4 67.7
Win 76.2% 23.8%
Win by 3 or less 7.0% 5.8%
Win by 10 or more 51.4% 8.4%

 

Down to the Wire?

 Margin of game was less than 1 point in 4.2% 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.  Here is the breakdown for KU's opponent this game:

 

  Siena Opp Advantage  
eFG% 49.64% 48.04% 26.9  
TO Rate 19.22% 24.46% 51.6  
OREB% 33.33% 34.77% -7.3  
FT Rate 23.83% 16.31% -11.5 FT Pct
      73.5 FT Attempts

 

ANALYSIS:  Siena struggles on the boards, but otherwise they've done quite well in most everything.  Interestingly, their single biggest advantage has been FT attempts, which is something that could well be continued against Kansas, which has tended to give up lots of them.  The turnover advantage could also carry into this game.  But the eFG% advantage is derived mostly from their opposition's low %, because Siena has not shot well.

 

Highlighted Efficiency Rankings
Note: There are 344 Div-I teams
(Source: KenPom.com)

Kansas

Siena

Offense #28 - Defense #25 - Tempo #166
Strong defensive eFG% (#22), particularly 2FG% defense (#13)
Shoot the ball pretty well overall (#50 eFG%)
Excellent offensive rebounding (#24)
Rank #43 in 2FG%
Great job on defense of BLK (#37)
Allow opp high % of FG's assisted (#250) but also have a high % themselves (#23)

Size (Tall = Position is Top 50 in minutes-weighted height, Short = #250 or worse)
Tall: C
Short: None

 

Other Factors:

Team is #333 in experience
Unusually high/low % of points scored by positions:  Hi - PG ... Lo - SG, SF


Individual Player Highlights: (thru Jan 1)

Sherron Collins - #176 AST rate
Tyshawn Taylor - #192 STL%
Brady Morningstar - #124 eFG%
Cole Aldrich - #88 eFG%, #50 OREB%, #29 DREB%, #38 BLK%
Marcus Morris - #58 OREB%
Markieff Morris - #196 DREB%

Offense #92 - Defense #68 - Tempo #39
Shut down opp use of FT line (#12 opp FT Rate)
Terrible 3FG% (#293) and FT% (#293)
Avoid getting own 2FGA's blocked (#43 BLK% on offense)
Very low % of FG attempts are 3FG's (#317)
Very high % of opp FG's assisted (#284 lowest)

 

Size (Tall = Position is Top 50 in minutes-weighted height, Short = #250 or worse)
Tall: None
Short: C, PF

 

Other Factors:

Not deep (#318 in % of minutes played by bench)
Unusually high/low % of points scored by positions:  Hi - None ... Lo - C


Individual Player Highlights: (thru Jan 1)

Alex Franklin - #197 eFG%
Ronald Moore - #61 AST Rate
Ryan Rossiter - #180 OREB%

Scoring Distribution:

On offense, KU relies somewhat less on 3FG's, while its opponents get a low percentage of points from 2FG's but more than average from FT's.
On offense, SU relies a ridiculously low amount on 3FG's (#9 in 2FG's as % of scoring), while its opponents share a very similar profile from the field and the 2nd lowest % of points from FT's.

 

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

 

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

Kansas will take below avg % of its FG's from 3-pt
Kansas will have above avg % of FG's assisted
Siena will take below avg % of its FG's from 3-pt
Siena plays faster tempo than Kansas

 

 

 

Game Projections

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

Manual adjustments: None.

 


Projected Boxscore

 

Kansas 81                            
Siena 68                            
                               
Kansas                              
PLAYER MIN 2FGM 2FGA 3FGM 3FGA FTM FTA PTS OREB DREB TREB AST TO STL BLK
Brady Morningstar 30 1 2 2 4 1 1 9 1 2 3 3 2 1 0
Cole Aldrich 29 6 9 0 0 3 4 15 4 6 10 2 2 1 2
Marcus Morris 16 4 7 0 0 2 3 10 3 3 6 2 2 1 0
Mario Little 8 0 2 0 1 0 0 0 1 4 5 2 1 0 0
Markieff Morris 14 2 3 0 1 1 2 5 1 3 4 1 2 0 1
Quintrell Thomas 7 1 1 0 0 1 1 3 1 2 3 0 1 0 0
Sherron Collins 36 4 9 2 6 3 4 17 1 1 2 6 3 1 0
Travis Releford 7 1 2 0 0 0 1 2 1 1 2 0 1 0 0
Tyrel Reed 24 1 1 2 4 1 1 9 0 1 1 2 1 1 0
Tyshawn Taylor 29 3 6 1 2 2 2 11 0 2 2 4 2 2 0
TOTALS 200 23 42 7 18 14 19 81 13 25 38 22 17 7 3
                               
Siena                              
PLAYER MIN 2FGM 2FGA 3FGM 3FGA FTM FTA PTS OREB DREB TREB AST TO STL BLK
Alex Franklin 36 4 8 0 0 4 8 12 3 4 7 1 3 1 1
Clarence Jackson 10 2 3 1 5 1 2 8 1 1 2 0 1 1 0
Edwin Ubiles 37 4 9 1 2 3 4 14 1 3 4 2 2 1 1
Josh Duell 8 0 0 1 1 0 0 3 1 1 2 0 0 0 0
Kenny Hasbrouck 33 2 7 1 4 3 5 10 0 2 2 3 3 2 0
Kyle Downey 6 1 2 0 1 1 2 3 0 1 1 1 1 0 0
Owen Wignot 7 0 1 0 1 0 0 0 1 1 2 1 0 1 0
Ronald Moore 34 2 5 1 3 2 2 9 1 2 3 5 3 1 0
Ryan Rossiter 29 3 5 0 0 3 3 9 3 3 6 1 2 1 1
TOTALS 200 18 40 5 17 17 26 68 11 18 29 14 15 8 3

 

 

Projection Summary

 

 
Projection
Comments

 OVERALL RESULTS

 Final Score  KU 81-68  
 Tempo (# poss)
 72 

 FOUR FACTORS ADVANTAGES

 eFG%  KU 56-45%  
 TO Rate (lo better)  SU 23-21%  
 O-Reb% KU 42-31%
 
 FT Rate SU 30-23%
 
 Four Factors Overall
 Too big a shooting advantage to KU for Siena to overcome with expected edges in TO's and FT's.  
 

PLAYER PROJECTIONS (10+ min played)

 Leading Scorers

 KU - Collins, Aldrich

 Opp - Ubiles, Franklin

 
 Highest PSAN-Comp
(game impact)

 KU - Aldrich

 Opp - Rossiter

 
 Highest PSAN70-Comp
(efficiency)

 KU - Aldrich

 Opp - Rossiter

 
 Highest efficiency vs season-to-date

 KU - Marcus Morris, Reed

 Opp - Jackson

 Seems like the Morris twins like to flip the projections I usually put here.  So, based on that trend, expect Markieff to have a great game and Marcus to struggle!
 Lowest efficiency vs season-to-date

 KU - Collins, Markieff Morris

 Opp - Hasbrouck, Franklin

 

 

Sports and Numbers Projection

Kansas wins 81-68

(all prediction models included)

 

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