Sports and Numbers

Kansas at Colorado (Boulder, CO)

Last 7 Game Projection

Down to the Wire?

 Margin of game was less than 1 point in 2.5% 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.)

Similar Opponent Projection

Down to the Wire?

 Margin of game was less than 1 point in 2.9% 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:

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).

Game Projections

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

Manual adjustments: Trent Beckley (CU) out due to injury.

Projected Boxscore

Projection Summary