California at Kansas (Lawrence, KS)
| Kansas | California | |
| Performance Indicators | ||
| Record (conference) | 10-0 | 6-3 |
| AP Rank | 1 | NR (48th most votes) |
| Pomeroy Rating (Updated daily) | 3 | 10 |
| Consensus Ranking (Updated periodically - avg several computer ratings and polls) | 6 | 19 |
| Best opponents defeated this season (Ranking from Pomeroy) | vs Memphis (#17) W 57-55 | vs Murray St. (#60) W 75-70 vs Iowa St. (#70) W 82-63 |
| RPI (Used for schedule strength, not team strength. Current and forecast RPI from RPIForecast .) | Current: 20 Forecast: 4 | Current: 12 Forecast: 11 |
| Projected NCAA Tournament Seed (Latest consensus from The Bracket Matrix) | #1 Seed | #7 Seed |
| Prediction Models | ||
| Vegas Oddsmakers | Win by 13.5 Est. Projection: 85-71 | |
| Prediction Tracker (Average of several power ratings) | Win by 11.21 | |
| Sagarin Power Ratings (Predictor) | Win by 7.13 | |
| Pomeroy (Efficiency and Tempo-Adjusted) | Win 82-72 | |
| 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 7.2 | |
| 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: 79-73 63.4% chance of victory | |
| Similar Opponent (New!) (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: 92-68 97.9% 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 14.1 Est. Projection: 84-70 |
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
Efficiency Ratings
* Rating not based on enough data. | California
Impact Ratings
Efficiency Ratings
* Rating not based on enough data. |
Last 7 Game Analysis
| Kansas | California | |
| Expected Score | 79.3 | 72.6 |
| Win | 63.4% | 36.6% |
| Win by 3 or less | 5.7% | 5.8% |
| Win by 10 or more | 43.1% | 19.6% |
Down to the Wire?
Margin of game was less than 1 point in 3.6% 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 Analysis
| Kansas | California | |
| Expected Score | 92.4 | 67.6 |
| Win | 97.9% | 2.1% |
| Win by 3 or less | 1.3% | 1.0% |
| Win by 10 or more | 88.8% | 0.3% |
Down to the Wire?
Margin of game was less than 1 point in 0.8% 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 Factor Analysis
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
| California
|
ANALYSIS: With the sole exception of FT attempts, California has a good but not great edge in all the other factors. The Jayhawks dominate in multiple categories, most notably the eFG%, the most important of the four factors. The key highlights here are that KU has a strength in a California weakness, FT attempts. Look for that to be a factor in this contest. Meanwhile, Cal shoots much better FT% than opponents, which may help mitigate that a bit.
Season Performance Trends
The charts below show the trend for each team's performance this season. For each game, a team's offensive, defensive and overall performance is standardized. Thus, performance indicates how many points per 100 possessions a team would score (offense), yield (defense) or net (average of offense and inverse defense) for a game. It is based purely on its opponent's adjusted efficiencies and the resulting efficiency of the game played. The dotted lines represent the best-fit line (linear regression), indicating which way a team may be trending for the season overall.
ANALYSIS: This doesn't paint a pretty picture for the Jayhawks and makes CAL look particularly dangerous. Every trend is in the wrong direction for KU and the right direction for California. The Bears are coming off their best overall performance of the season, while KU is coming off its worst. Trends are not guaranteed to continue, but it certainly puts the pressure on KU.
Highlighted Efficiency Rankings | |
Kansas | California |
Offense #2 - Defense #10 - Tempo #98
Other Factors: Team is #25 in Effective Height
| Offense #4 - Defense #38 - Tempo #94 Size (Tall = Position is Top 50 in minutes-weighted height, Short = #250 or worse)
Other Factors: Team is #39 in Experience
|
Scoring Distribution: On offense, KU is fairly balanced, while its opponents get a higher percentage of points from 2FG's than 3FG's. | |
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
| Kansas | 79 | ||||||||||||||
| California | 70 | ||||||||||||||
| Kansas | |||||||||||||||
| PLAYER | MIN | 2FGM | 2FGA | 3FGM | 3FGA | FTM | FTA | PTS | OREB | DREB | TREB | AST | TO | STL | BLK |
| Brady Morningstar | 22 | 1 | 1 | 0 | 1 | 0 | 0 | 2 | 1 | 1 | 2 | 2 | 0 | 1 | 0 |
| Cole Aldrich | 26 | 3 | 6 | 0 | 0 | 4 | 6 | 10 | 2 | 4 | 6 | 1 | 2 | 0 | 2 |
| Elijah Johnson | 8 | 1 | 2 | 0 | 1 | 1 | 1 | 3 | 0 | 1 | 1 | 2 | 1 | 0 | 0 |
| Marcus Morris | 23 | 3 | 5 | 0 | 1 | 4 | 5 | 10 | 1 | 2 | 3 | 1 | 2 | 1 | 0 |
| Markieff Morris | 16 | 2 | 3 | 0 | 1 | 2 | 3 | 6 | 1 | 3 | 4 | 1 | 1 | 0 | 1 |
| Sherron Collins | 30 | 2 | 5 | 2 | 3 | 2 | 3 | 12 | 0 | 1 | 1 | 3 | 2 | 1 | 0 |
| Thomas Robinson | 8 | 2 | 2 | 0 | 0 | 2 | 4 | 6 | 1 | 2 | 3 | 0 | 1 | 0 | 1 |
| Tyrel Reed | 16 | 0 | 1 | 1 | 3 | 0 | 1 | 3 | 0 | 1 | 1 | 1 | 1 | 0 | 0 |
| Tyshawn Taylor | 23 | 2 | 4 | 1 | 2 | 2 | 2 | 9 | 0 | 2 | 2 | 3 | 2 | 1 | 0 |
| Xavier Henry | 28 | 3 | 5 | 3 | 5 | 3 | 5 | 18 | 1 | 2 | 3 | 1 | 2 | 1 | 1 |
| TOTALS | 200 | 19 | 34 | 7 | 17 | 20 | 30 | 79 | 7 | 19 | 26 | 15 | 14 | 5 | 5 |
| California | |||||||||||||||
| PLAYER | MIN | 2FGM | 2FGA | 3FGM | 3FGA | FTM | FTA | PTS | OREB | DREB | TREB | AST | TO | STL | BLK |
| Brandon Smith | 5 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 |
| D.J. Seeley | 5 | 1 | 1 | 0 | 1 | 0 | 0 | 2 | 0 | 1 | 1 | 1 | 1 | 0 | 0 |
| Jamal Boykin | 25 | 5 | 8 | 0 | 0 | 1 | 1 | 11 | 2 | 3 | 5 | 1 | 2 | 1 | 0 |
| Jerome Randle | 32 | 3 | 6 | 2 | 6 | 4 | 4 | 16 | 0 | 1 | 1 | 4 | 3 | 1 | 0 |
| Jorge Gutierrez | 22 | 1 | 3 | 1 | 2 | 1 | 2 | 6 | 1 | 2 | 3 | 3 | 1 | 1 | 0 |
| Markhuri Sanders-Frison | 17 | 1 | 3 | 0 | 0 | 0 | 1 | 2 | 1 | 2 | 3 | 1 | 1 | 0 | 0 |
| Max Zhang | 9 | 2 | 3 | 0 | 0 | 0 | 1 | 4 | 1 | 2 | 3 | 0 | 1 | 0 | 1 |
| Nikola Knezevic | 7 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 |
| Omondi Amoke | 17 | 1 | 4 | 0 | 0 | 2 | 2 | 4 | 3 | 3 | 6 | 0 | 1 | 0 | 0 |
| Patrick Christopher | 32 | 3 | 8 | 2 | 5 | 1 | 1 | 13 | 2 | 3 | 5 | 2 | 2 | 1 | 0 |
| Theo Robertson | 29 | 3 | 5 | 1 | 2 | 3 | 3 | 12 | 1 | 2 | 3 | 1 | 2 | 0 | 1 |
| TOTALS | 200 | 20 | 43 | 6 | 17 | 12 | 16 | 70 | 11 | 19 | 30 | 14 | 15 | 5 | 2 |
Projection Summary
Projection | Comments | |
OVERALL RESULTS | ||
| Final Score | KU 79-70 | |
| Tempo (# poss) | 71 | |
FOUR FACTORS ADVANTAGES | ||
| eFG% | KU 58-48% | Could get frustrating for KU fans, as they are not used to giving up this high a percentage (would be highest this season by far). |
| TO Rate (lo better) | KU 21-20% | |
| O-Reb% | CAL 37-27% | Look out for Amoke, he's a beast on the boards. |
| FT Rate | KU 59-27% | Should negate the OREB% edge for CAL nicely. Heavily a result of expected FT attempt advantage for KU. |
| Four Factors Overall | FT attempts will be an equal partner with eFG% in helping KU to a modest margin of victory. | |
PLAYER PROJECTIONS (10+ min played) | ||
| Leading Scorers | KU - X. Henry, Collins Opp - Randle, Christopher | |
| Highest PSAN-Comp (game impact) | KU - X. Henry Opp - Boykin | |
| Highest PSAN70-Comp (efficiency) | KU - X. Henry Opp - Boykin | |
| Highest efficiency vs season-to-date | KU - Taylor, Morningstar Opp - Gutierrez, Robertson | |
| Lowest efficiency vs season-to-date | KU - Reed, Markieff Morris Opp - Amoke, Sanders-Frison | |
Sports and Numbers ProjectionKansas wins 79-70(all prediction models included/complete) |
Pre-Game Keys to Watch For | |||
Keys to Watch For | Metric | Result | Edge (Comments) |
| Though it is always important, KU's eFG% in this game is of particular interest. For some reason, not only is CAL's opp eFG% significantly correlated to its defensive officiency but also to its offensive efficiency (negatively). Since KU is projected to give up 48 eFG%, that 58 eFG% of its own had better come to close to materializing to help ease the pressure in other aspects of the game. | KU to shoot at least 55 eFG% | ||
| Cole Aldrich is the current "Key Player" based on this site's analysis. He is going up against very talented players in Boykin and Amoke, but they are both at least 3 inches shorter than he is. If this is not the game where Aldrich snaps out of his shooting funk, it could spell trouble for KU. He is projected to make 3-of-6 FG's, so 50% is a nice benchmark to hit. | Aldrich to make at least 50% of FG's. | ||
| Markieff Morris is the most efficient player on KU so far this season, but he isn't going to do much if he's saddled with foul trouble. He must get his typical 15-20 minutes to help with second-chance points and give Aldrich some fresh legs. | Markieff Morris to play at least 15 MIN. | ||
| FT attempts advantage is a key because it's a KU strength and CAL weakness. It must materialize for the Jayhawks to make things easier. | KU to attempt at least 10 more FT's than CAL | ||