Kansas Shortcuts
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| Preview: Kansas at UCLA |
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| Dec 6, 2009 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Kansas at UCLA (Los Angeles, CA)
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 | UCLA | |
| Expected Score | 81.9 | 53.0 |
| Win | 95.0% | 5.0% |
| Win by 3 or less | 2.0% | 1.4% |
| Win by 10 or more | 85.8% | 1.4% |
Down to the Wire?
Margin of game was less than 1 point in 1.2% 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. Team 1 is KU's opponent, while Team 2 represents that team's opponents. Here is the breakdown for KU's opponent this game:
| UCLA | Opp | Advantage | ||
| eFG% | 48.15% | 50.32% | -14.5 | |
| TO Rate | 21.11% | 23.06% | 7.8 | |
| OREB% | 31.96% | 28.86% | 6.3 | |
| FTA/FGA | 15.67% | 27.44% | -11.4 | FT Pct |
| -20.6 | FT Attempts |
ANALYSIS: Again, it's very difficult to say much about a team that's nothing like the one that's put up these numbers. So far this season, UCLA has only manageg to squeak out advantages in turnovers and rebounding, but the huge disadvantages at the FT line (both attempts and percentage) along with giving up way too high eFG% have made it a dismal start for the usually-mighty Bruins.
Statistical Strengths and Weaknesses Analysis(Note: These are based on raw statistics that are unadjusted for strength of opposition.)
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Game Projections
(Not a prediction. Read more details in "FAQ & Terms" section.)
Manual adjustments: None.
Projected Boxscore
Could not do a projected boxscore given all the uncertainty of UCLA's roster. Two players may play for the first time this game, and the key player has transferred. Dividing that playing time was an exercise in futility and certainly a very speculative one. Below, you may still see the trends for the overall game.
Projection Summary
Projection | Comments | |
OVERALL RESULTS | ||
| Final Score | KU 77-52 | |
| Tempo (# poss) | 69 | |
FOUR FACTORS ADVANTAGES | ||
| eFG% | KU 67-37% | Hard to believe this kind of performance against a Howland coached UCLA team though. |
| TO Rate (lo better) | Tie 23% | |
| O-Reb% | UCLA 32-24% | One of the keys to the Jayhawks taking their game to the next level will be to reverse this trend. |
| FT Rate | KU 60-18% | |
| Four Factors Overall | An even battle in TO and rebounding will set the stage for KU's domination in eFG% and FT attempts to rout the Bruins. | |
PLAYER PROJECTIONS (10+ min played) | ||
| Leading Scorers | KU - Collins/X. Henry (15 pts each) Opp - | |
| Highest PSAN-Comp (game impact) | KU - Collins Opp - | |
| Highest PSAN70-Comp (efficiency) | KU - Markieff Morris Opp - | |
| Highest efficiency vs season-to-date | KU - Collins, Taylor Opp - | |
| Lowest efficiency vs season-to-date | KU - Johnson, Reed Opp - | |
Sports and Numbers ProjectionKansas wins 77-52(all prediction models included/complete) |
Pre-Game Keys to Watch For | |||
Keys to Watch For | Metric | Result | Edge (Comments) |
| KU's performance on both sides of the ball depends most on shooting and turnovers. The expected eFG% advantage must materialize for the Jayhawks or this game could get close, and in a hostile environment, with all the pressure on Kansas, who knows what could happen. | KU eFG% to be at least 8% higher than UCLA. | ||
| Rebounding will be another key. KU has done a great job at getting second-chance points, but the Bruins have shut down their opponents in that area. If KU can't get OREB's, there will be even more pressure for the 1st key above to materialize. | KU to grab at least 36 OREB% | ||
| For a variety of reasons, the FT line is predicted to be a huge advantage for KU. The Bruins have done a remarkable job at avoiding blocked shots, so it may frustrate KU, which is accustomed to swatting lots of them away. If this results in foul trouble and leads to more FT attempts for UCLA, this category may not materialize into much of advantage. And of course, KU's FT shooting woes must come to an end. | KU to score at least as many from FT line as UCLA | ||
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