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Welcome to EvanMiya.com, trusted by over 100+ Division 1 programs! My name is Evan Miyakawa, and I am a Ph.D. statistician and data scientist. You can read more about me on the About Page, and you can find me on Twitter, TikTok, and Instagram.



CBB Player Ratings Glossary:

  • OBPR: Offensive Bayesian Performance Rating reflects the offensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the offensive strength of other teammates on the floor with him, along with the defensive strength of the opponent’s players on the floor. OBPR is interpreted as the number of offensive points per 100 possessions above D1 average expected by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • DBPR: Defensive Bayesian Performance Rating reflects the defensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the defensive strength of other teammates on the floor with him, along with the offensive strength of the opponent’s players on the floor. DBPR is interpreted as the number of defensive points per 100 possessions better than (below) D1 average expected to be allowed by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • BPR: Bayesian Performance Rating is the sum of a player’s OBPR and DBPR. This rating is the ultimate measure of a player’s overall value to his team when he is on the floor. BPR is interpreted as the number of points per 100 possessions better than the opponent the player’s team is expected to be if the player were on the court with 9 other average players. A higher rating is better.
  • Change: Improvement in BPR over the last 30 days.
  • Off Poss: Number of offensive possessions played.
  • Def Poss: Number of defensive possessions played.
  • Box OBPR: Box Offensive Bayesian Performance Rating is an estimate of a player’s offensive value, based only on his individual box stats. This serves as a prior starting point when calculating OBPR.
  • Box DBPR: Box Defensive Bayesian Performance Rating is an estimate of a player’s defensive value, based only on his individual box stats. This serves as a prior starting point when calculating DBPR.
  • Box BPR: Box Bayesian Performance Rating is the sum of a player’s Box OBPR and Box DBPR. This rating is an estimate of a player’s overall value, based only on his individual box stats.
  • Adj Team Off Eff: Team offensive efficiency (points scored per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A higher value is better.
  • Adj Team Def Eff: Team defensive efficiency (points allowed by opponent per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A lower value is better.
  • Adj Team Eff Margin: Difference between adjusted team offensive and adjusted defensive efficiency with player on the court. A higher value is better.
  • +/-: Number of points scored for the player’s team with him on the court, minus the number of points scored by the opponent with him on the court.
  • Position: An estimate of a player’s position based on his individual stats and team contributions. An estimated position of 1 corresponds to being a point guard, and a 5 corresponds to being a center. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.
  • Role: An estimate of a player’s offensive role based on his individual stats and team contributions. An estimated role of 1 corresponds to being the “creator” in the offense, and a 5 corresponds to being the “receiver”. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.

BPR Interpretation Example: If Jimmer Fredette had an Offensive BPR of 4.5, a Defensive BPR of -0.5, and a BPR of 4.0, this would mean the following: If Fredette were on the court with 9 other D1 average players, his team’s offense would be 4.5 points per 100 possessions better than average, or if he were not on the floor and were replaced by another D1 average player. Similarly, his team’s defense would be expected to be 0.5 points per 100 possessions worse (conceding 0.5 PP100 more) while he’s on the floor. Overall, his team would be expected to outscore the opponent by 4.0 points in a 100 possession game.



CBB Team Ratings Glossary:

  • Relative Ranking: Each team is ranked based on how it would be expected to perform head-to-head against other similarly ranked teams. If a team is ranked 4th, it is predicted to lose against each of the top three teams, but predicted to beat teams ranked 5th, 6th, and so on. Each head-to-head prediction is based on both teams’ efficiency ratings, opponent adjustment, and pace adjustment.
  • O-Rate: Team Offensive Efficiency Rating reflects a team’s expected offensive efficiency. This number can be interpreted as the points per 100 possessions better than average expected when playing against an average D1 team. However, each team’s O-Rate is actually based on how its offense would perform against other similarly ranked teams. A higher rating is better.
  • D-Rate: Team Defensive Efficiency Rating reflects a team’s expected defensive efficiency. This number can be interpreted as the defensive points per 100 possessions better than average expected when playing against an average D1 team. However, each team’s D-Rate is actually based on how its defense would perform against other similarly ranked teams. A higher rating is better.
  • Relative Rating: Team Net Relative Rating is the sum of a team’s O-Rate and D-Rate. This rating is the ultimate measure of a team’s expected overall strength, relative to other teams ranked similarly. The Relative Rating value can be interpreted as the number of points the team is expected to outscore an average D1 team by in an 100 possession game. However, each team’s Relative Rating is actually based on how it would be expected to perform against other similarly ranked teams. See the example at the bottom of the page.
  • Change: Improvement in BPR over the last 30 days.
  • Opponent Adjust: This measures how well each team performs above or below expectation based on if they are playing an above average opponent on their schedule or a below average opponent. There are some teams that perform better than anticipated when they face really tough teams but struggle to dismantle teams that are worse than them (positive red bar). This concept is sometimes referred to as “playing up/down to competition”. Other teams are the opposite; they can easily crush inferior opponents but are disappointing against high quality teams (negative blue bar). Note that being positive isn’t better than being negative in this variable. A team that has a really high red bar is more likely to succeed against elite competition but is also equally likely to have a stunning loss to an inferior team. Teams with a really low blue bar are trustworthy to handle business against teams they should beat, but are less likely to win against the best teams.
  • Pace Adjust: This measures how well each team performs above or below expectation in games that are played at a higher or lower pace than usual. Some teams perform slightly better when they play in up-tempo games (positive orange), and some teams are more comfortable in slow-paced games (negative blue bar).
  • Kill Shots Per Game: The number of double digit scoring runs per game (10 points or more scored in a row without the opposing team scoring).
  • Kill Shots Allowed Per Game: The number of double digit scoring runs conceded per game (10 points or more scored in a row by the opponent without the team scoring).
  • Kill Shots Margin Per Game: How many more 10-0 runs a team has per game than their opponents.
  • Total Kill Shots: The total number of double digit scoring runs in the season.
  • Total Kill Shots Allowed: The total number of double digit scoring runs conceded in the season.
  • True Tempo: A measure of a team’s true game pace. This number reflects the estimated number of possessions played in a game against an average paced D1 opponent.
  • Off Rank: A team’s rank in OBPR.
  • Def Rank: A team’s rank in DBPR.
  • Tempo Rank: A team’s rank in True Tempo
  • Injury Rank: A team’s overall ranking after accounting for the absence of all currently injured players.
  • Roster Rank: A crude ranking of each team’s strength of roster. This is largely based on the individual BPR values of all players on the roster.
  • Resume Rank: A ranking of each team’s in-season resume, treating all teams as equal at the start of the season. Think of it as a better version of the NET.
  • Home Rank: A team’s rank in how much better they perform at home versus road games. A team ranked higher will play much better at home than on the road.

Relative Rating Interpretation Example: If Kansas has a Relative Ranking of 3rd, this means that they are expected to lose head-to-head to the teams ranked 1st and 2nd, but win head-to-head against the teams ranked 4th, 5th, and so on. Suppose Michigan State is 4th, and Kansas has a Relative Rating of 25.0 and MSU has a Relative Rating of 23.0. This means that Kansas is expected to beat Michigan State by 2 points per 100 possessions. If they played a typical 70 possession game, the game prediction would have Kansas favored by 1.4 points.

Kansas’s Relative Rating of 25.0 would roughly translate to them being predicted to beat a D1 average opponent by 25 points per 100 possessions. However, since each team’s Relative Rating is calculated based on how they are predicted to perform against other similarly ranked teams, the rating of 25 can’t be directly interpreted this way.

For example, at the end of 2022-23, UConn’s Relative Rating was 26.1 (1st in the country), and Houston’s Relative Rating was 24.7 (3rd in the country). However, since UConn’s Opponent Adjustment coefficient indicates that they excel against good teams (large positive red bar), but struggle against weaker teams, they were only predicted to beat an average D1 opponent by 24.0 points per 100 possessions. By contrast, Houston was great at dismantling weaker opponents (large negative blue bar), but struggled against stronger teams. As a result, they were predicted to beat an average D1 opponent by 28.1 points per 100 possessions, a larger margin of victory than for #1 UConn. Against each other, UConn would be predicted to beat Houston by 3.8 points per 100 possessions.


Glossary:

  • Resume Quality: The number of wins a team has above what would be expected from a team on the at-large cutline against their schedule. A team above a value of 0 should receive an at-large bid, and a team below 0 does not have a resume good enough to get a bid. It can be calculated by adding Win Quality + Loss Quality.
  • Win Quality: A measure of how good a team’s wins are, based on how a team right on the tournament at-large bid cutline would fare in those wins. Hover over a team’s number to see how much each win is worth.
  • Loss Quality: A measure of how bad a team’s losses are, based on how a team right on the tournament at-large bid cutline would fare in those losses. Hover over a team’s number to see how much each loss is worth. The more negative the number, the worse the losses.
  • Expected Bubble Wins: The number of wins a team right on the tourney at-large cutline would be expected to win against this team’s schedule. The difference between this number and the actual number of wins equals the Resume Quality.

Resume Quality Example: Let’s say Kansas beats Utah at home. Based on Utah’s team strength, if an average bubble team (defined here as a team right on the tournament at-large cutline) would have a 78% chance of beating Utah at home, then Kansas’s win would have a win quality of +0.22, the difference between 1 and 0.78. If Kansas were to lose, however, the loss quality would be -0.78. This system, very similar to Wins Above Bubble, which you can find at BartTorvik.com, properly rewards every win and counts every loss against you, based on how difficult a matchup it is.

For a more detailed explanation, read up on it here.


Player Overall Grades

Player Individual Skill Projection Grades

Player Projections Explanation:

All player projections take a single stat, such as three point percentage, and predict that stat for the rest of the year, taking a player’s game-by-game history over time and accounting for opponent strength, offensive usage, expected year-by-year improvement, and recent form. For younger players, high-school recruiting profiles are also used to form a starting projection at the beginning of their freshman year, which become less informative toward their current projection as they play more games in college. For some statistics, recent form (how a player is performing in that statistical category recently) is much more important than their overall career average in that stat, while for others recent form isn’t as predictive of future performance. For a more detailed explanation, read up on it here.

Player Tiers:

Player Projections Explanation:

All player projections take a single stat, such as three point percentage, and predict that stat for the rest of the year, taking a player’s game-by-game history over time and accounting for opponent strength, offensive usage, expected year-by-year improvement, and recent form. For younger players, high-school recruiting profiles are also used to form a starting projection at the beginning of their freshman year, which become less informative toward their current projection as they play more games in college. For some statistics, recent form (how a player is performing in that statistical category recently) is much more important than their overall career average in that stat, while for others recent form isn’t as predictive of future performance. For a more detailed explanation, read up on it here.

Player Projections Leaderboard Glossary:

  • 3PT%: A player’s predicted three-point shooting percentage against an average opponent, adjusted for usage.
  • 2PT%: A player’s predicted two-point shooting percentage against an average opponent, adjusted for usage.
  • FT%: A player’s predicted free throw shooting percentage against an average opponent.
  • Scoring Volume: A player’s predicted points per 100 possessions based on predicted shot usage and efficiency.
  • Assist Rate: A player’s predicted assist rate against an average opponent, adjusted for usage. Assist Rate is the percentage of teammate made field goals that the player assisted while on the court.
  • Turnover %: A player’s predicted turnover percentage against an average opponent, adjusted for usage. Turnover percentage is the percentage of offensive possessions that end in the player turning the ball over while on the court.
  • Playmaking Score: A player’s predicted playmaking score, which combines predicted assist rate and turnover rate to measure a player’s ability to create plays for others with the ball in his hands.
  • O-Reb %: A player’s predicted offensive rebound percentage against an average opponent, adjusted for usage. Offensive rebound percentage is the percentage of possible offensive rebounds that the player secured while on the court.
  • D-Reb %: A player’s predicted defensive rebound percentage against an average opponent, adjusted for usage. Defensive rebound percentage is the percentage of possible defensive rebounds that the player secured while on the court.
  • Rebounding %: A player’s predicted offensive + defensive rebounding rate. See O-Reb % and D-Reb % for more detail.
  • Steal %: A player’s predicted steal percentage against an average opponent. Steal percentage is percentage of defensive possessions that end in the player stealing the ball while on the court.
  • Block %: A player’s predicted block percentage against an average opponent, adjusted for usage.. Block percentage is the percentage of opponent two-point field goal attempts that the player blocked while on the court.
  • Foul %: A player’s predicted personal fouls committed per 100 possessions.
  • Defensive Value: A player’s defensive per-possession value to a team, against an average opponent, as measured by Defensive BPR. DBPR reflects the defensive value a player brings to his team when he is on the court.

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Glossary:

  • OBPR: Offensive Bayesian Performance Rating reflects the offensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the offensive strength of other teammates on the floor with him, along with the defensive strength of the opponent’s players on the floor. OBPR is interpreted as the number of offensive points per 100 possessions above D1 average expected by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • DBPR: Defensive Bayesian Performance Rating reflects the defensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the defensive strength of other teammates on the floor with him, along with the offensive strength of the opponent’s players on the floor. DBPR is interpreted as the number of defensive points per 100 possessions better than (below) D1 average expected to be allowed by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • BPR: Bayesian Performance Rating is the sum of a player’s OBPR and DBPR. This rating is the ultimate measure of a player’s overall value to his team when he is on the floor. BPR is interpreted as the number of points per 100 possessions better than the opponent the player’s team is expected to be if the player were on the court with 9 other average players. A higher rating is better.
  • Change: Improvement in BPR over the last 30 days.
  • Off Poss: Number of offensive possessions played.
  • Def Poss: Number of defensive possessions played.
  • Box OBPR: Box Offensive Bayesian Performance Rating is an estimate of a player’s offensive value, based only on his individual stats. This serves as a prior starting point when calculating OBPR.
  • Box DBPR: Box Defensive Bayesian Performance Rating is an estimate of a player’s defensive value, based only on his individual stats. This serves as a prior starting point when calculating DBPR.
  • Box BPR: Box Bayesian Performance Rating is the sum of a player’s Box OBPR and Box DBPR. This rating is an estimate of a player’s overall value, based only on his individual stats.
  • Adj Team Off Eff: Team offensive efficiency (points scored per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A higher value is better.
  • Adj Team Def Eff: Team defensive efficiency (points allowed by opponent per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A lower value is better.
  • Adj Team Eff Margin: Difference between adjusted team offensive and adjusted defensive efficiency with player on the court. A higher value is better.
  • +/-: Number of points scored for the player’s team with him on the court, minus the number of points scored by the opponent with him on the court.
  • Position: An estimate of a player’s position based on his individual stats and team contributions. An estimated position of 1 corresponds to being a point guard, and a 5 corresponds to being a center. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.
  • Role: An estimate of a player’s offensive role based on his individual stats and team contributions. An estimated role of 1 corresponds to being the “creator” in the offense, and a 5 corresponds to being the “receiver”. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the player. A higher rating indicates that the player played against tougher opposition.
  • Position: An estimate of a player’s position based on his individual stats and team contributions. An estimated position of 1 corresponds to being a point guard, and a 5 corresponds to being a center. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.
  • Role: An estimate of a player’s offensive role based on his individual stats and team contributions. An estimated position of 1 corresponds to being the “creator” in the offense, and a 5 corresponds to being the “receiver”. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.

BPR Interpretation Example: If Jimmer Fredette had an Offensive BPR of 4.5, a Defensive BPR of -0.5, and a BPR of 4.0, this would mean the following: If Fredette were on the court with 9 other D1 average players, his team’s offense would be 4.5 points per 100 possessions better than average, or if he were not on the floor and were replaced by another D1 average player. Similarly, his team’s defense would be expected to be 0.5 points per 100 possessions worse (conceding 0.5 PP100 more) while he’s on the floor. Overall, his team would be expected to outscore the opponent by 4.0 points in a 100 possession game.

Glossary:

  • Team Off Eff: Team offensive efficiency (points per possession scored) with those two player on the court at the same. A higher value is better.
  • Team Def Eff: Team defensive efficiency (points per possessions by opponent) with those two players on the court at the same time. A lower value is better.
  • Team Eff Margin: Difference between team offensive and defensive efficiency with those two players on the court at the same time. A higher value is better.
  • Off Poss: Number of offensive possessions with those two players on the court at the same time.
  • Def Poss: Number of defensive possessions with those two players on the court at the same time.
  • Above / Below Average: A measure of how much better the teammate played when he was on the court with the player, compared to the teammate’s average play. This calculates the team’s efficiency when these two players were on the court, minus the team’s efficiency for all possessions when the teammate was on the court, regardless of who he played with.


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Glossary:

  • Poss: Number of possessions played.
  • Poss %: Percentage of team possessions played.
  • On-Off Offense Splits: How much better the team played offensively with that player on the floor, compared to without them, measured in points per 100 possessions, adjusted for opponent strength faced. A positive number indicates that the team was better offensively with the player on the floor.
  • On-Off Defense Splits: How much better the team played defensively with that player on the floor, compared to without them, measured in points per 100 possessions, adjusted for opponent strength faced. A positive number indicates that the team was better defensively with the player on the floor.
  • On-Off Margin Splits: How much better the team played overall with that player on the floor, compared to without them, measured in points per 100 possessions, adjusted for opponent strength faced. A positive number indicates that the team was better overall with the player on the floor.
  • Adj Team Off Eff: Team offensive efficiency (points scored per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A higher value is better.
  • Adj Team Def Eff: Team defensive efficiency (points allowed by opponent per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A lower value is better.
  • Adj Team Eff Margin: Difference between adjusted team offensive and adjusted defensive efficiency with player on the court. A higher value is better.
  • +/-: Number of points scored for the player’s team with him on the court, minus the number of points scored by the opponent with him on the court.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the player. A higher rating indicates that the player played against tougher opposition.

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Glossary:

  • Team Off Eff: Team offensive efficiency (points scored per 100 possession) with those two player on the court at the same. A higher value is better.
  • Team Def Eff: Team defensive efficiency (points allowed by opponent per possessions) with those two players on the court at the same time. A lower value is better.
  • Team Eff Margin: Difference between team offensive and defensive efficiency with those two players on the court. A higher value is better.
  • Adj Team Eff Margin: Team Efficiency Margin, adjusted for the quality of opponent players faced by the pair of players.
  • Off Poss: Number of offensive possessions with those two players on the court at the same time.
  • Def Poss: Number of defensive possessions with those two players on the court at the same time.
  • Chemistry: A score that reflects how much better than average the team performs when these two players on the court together, compared to team averages when they are on the court individually.
  • Weighted Chemistry: This is a more reliable metric for teammate chemistry. The Chemistry score is multiplied by the number of possessions shared by the two players, to give more weight to player pairs who were on the floor more.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the pair of teammates. A higher rating indicates that the players played against tougher opposition.

Glossary:

  • Team Off Eff: Team offensive efficiency (points scored per 100 possession) with the lineup on the floor. A higher value is better.
  • Team Def Eff: Team defensive efficiency (points allowed by opponent per possessions) with the lineup on the floor. A lower value is better.
  • Team Eff Margin: Difference between team offensive and defensive efficiency with the lineup on the floor. A higher value is better.
  • Adj Team Eff Margin: Team Efficiency Margin, adjusted for the quality of opponent players faced by the lineup.
  • Off Poss: Number of offensive possessions with the lineup on the floor.
  • Def Poss: Number of defensive possessions with the lineup on the floor.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the lineup. A higher rating indicates that the lineup played against tougher opposition.

Glossary:

  • Team Off Eff: Team offensive efficiency (points scored per 100 possession) with the lineup on the floor. A higher value is better.
  • Team Def Eff: Team defensive efficiency (points allowed by opponent per possessions) with the lineup on the floor. A lower value is better.
  • Team Eff Margin: Difference between team offensive and defensive efficiency with the lineup on the floor. A higher value is better.
  • Adj Team Eff Margin: Team Efficiency Margin, adjusted for the quality of opponent players faced by the lineup.
  • Off Poss: Number of offensive possessions with the lineup on the floor.
  • Def Poss: Number of defensive possessions with the lineup on the floor.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the lineup. A higher rating indicates that the lineup played against tougher opposition.

Glossary:

  • Team Off Eff: Team offensive efficiency (points scored per 100 possession) with the lineup on the floor. A higher value is better.
  • Team Def Eff: Team defensive efficiency (points allowed by opponent per possessions) with the lineup on the floor. A lower value is better.
  • Team Eff Margin: Difference between team offensive and defensive efficiency with the lineup on the floor. A higher value is better.
  • Adj Team Eff Margin: Team Efficiency Margin, adjusted for the quality of opponent players faced by the lineup.
  • Off Poss: Number of offensive possessions with the lineup on the floor.
  • Def Poss: Number of defensive possessions with the lineup on the floor.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the lineup. A higher rating indicates that the lineup played against tougher opposition.

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Lineup Explorer

This graph allows you to visualize the performance of each lineup combo, and allows you to filter by number of possessions played, or choose lineups that have specific players.

Instructions: Select the number of players to view in each lineup (2, 3, 4, or 5). You can also choose to filter lineups by the number of possessions played. Interactively hover over points on the graph to see the performance of each lineup combo. The size of the bubble corresponds to how much that lineup combo played, and the color corresponds to how efficient that lineup was on a per possession basis (lighter is better). Below the graph, you can also choose to only view lineups with specific players.



Keys to Victory Automated Team Report


Style Metrics Report:




Keys to Victory Metrics Tables


Key to Victory Metrics Explorer

Keys To Victory Overview

The Keys to Victory section provides a very unique look at what factors are most important for each team’s success in games. For each team, we have looked at every game played over the last several years and identified which metrics have been the most crucial to winning or losing a game for that team. There is a report for each team that provides important metrics, as well as pages for exploring the data in table and visual form.

  • Key Metrics Report: We provide a detailed report that identifies certain statistics that have been crucial to the team’s success over the last several years. We look at usual team statistics, along with stylistic variables like tempo.
  • Key Metrics Table: This page lets you choose different key metrics (and their target values) and see how they have varied game-to-game.
  • Key Metrics Explorer: This graph allows for you to visualize the different key metric targets, and how they varied game-to-game.

How to practically use the Keys To Victory section for your team: Focus your gameplan on the most important aspects of team performance.

The Key Metrics Report uses an advanced statistical analysis to determine which game stats are most critical for each team’s success in each game, based on every performance over the last several years. The key factors that we identify are not only very crucial to winning and losing, but are even more important for that team than for others. We have provided specific target values for each metric (shooting at least 38% from three, for example), to help you determine performance levels to aim for as a team in each game.

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Glossary:

  • Non-Garbage Score: The team’s score after filtering out possessions when the game was already decided. See “How It Works” page for details.
  • Non-Garbage Opp Score: The opponent’s score after filtering out possessions when the game was already decided.
  • Off Eff: The team’s offensive efficiency (points scored per 100 possessions), adjusted for home court advantage. A higher value is better.
  • Def Eff: The team’s defensive efficiency (points allowed by opponent per 100 possessions), adjusted for home court advantage. A lower value is better.
  • Non-Garbage Off Eff: The team’s offensive efficiency after filtering out possessions when the game was already decided. This is a more accurate assessment of how the team played on offense than Off Eff.
  • Non-Garbage Def Eff: The team’s defensive efficiency after filtering out possessions when the game was already decided. This is a more accurate assessment of how the team played on defense than Def Eff.
  • Off Poss: Number of offensive possessions
  • Def Poss: Number of defensive possessions
  • Non-Garbage Off Poss: Number of offensive possessions after filtering out possessions when the game was already decided.
  • Non-Garbage Def Poss: Number of defensive possessions after filtering out possessions when the game was already decided.

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Game Explorer

This graph lets you view each game over a season(s), looking at how a specified game stat (such as turnovers) varied over that time. It is a unique way to see how different team stats impacted the final outcome. You can pick a number of variables and see how the team fared game-by-game for each one over time.

Instructions: Select the season to view, and then pick a game statistic to be on the vertical axis. Interactively hover over points on the graph to see the result of the game and how the team fared in that particular stat. Green dots indicate wins, and red dots indicate losses.



CBB Lineup Ratings Glossary:

  • Observed Off Eff: Team offensive efficiency (points scored per 100 possession) with the lineup on the floor, adjusted for the strength of opposing players faced. A higher value is better.
  • Observed Def Eff: Team defensive efficiency (points allowed by opponent per possessions) with the lineup on the floor, adjusted for the strength of opposing players faced. A lower value is better.
  • Observed Eff Margin: Difference between adjusted team offensive and adjusted defensive efficiency with the lineup on the floor. A higher value is better.
  • Predicted Eff Margin: A lineup’s predicted team efficiency margin against an average D1 opponent, in points per 100 possessions. This prediction takes into account how well the lineup has performed on the floor together (if at all), along with the individual skills of the players in that lineup, and positional and offensive role balance in that lineup. See the Lineup Projections / Grades page for more detail.
  • Off Poss: Number of offensive possessions with the lineup on the floor.
  • Def Poss: Number of defensive possessions with the lineup on the floor.
  • Avg Opp BPR: The average BPR of the opponent’s players on the floor at the same time as the lineup. A higher rating indicates that the lineup played against tougher opposition.
  • Raw Team Off Eff: Raw team offensive efficiency (points scored per 100 possession) with the lineup on the floor, not adjusted for strength of opposition. A higher value is better.
  • Raw Team Def Eff: Raw team defensive efficiency (points allowed by opponent per possessions) with the lineup on the floor, not adjusted for strength of opposition.. A lower value is better.
  • Raw Team Eff Margin: Difference between raw team offensive and defensive efficiency with the lineup on the floor. A higher value is better.

Lineup Tiers:

Lineup Projections Explanation:

All lineup projections predict how efficient a particular lineup of five players will be on offense and defense going forward. The model takes into account the lineup’s observed performance on the court during the current season, along with the skills and positional qualities of the individual players. Even if a lineup of five players hasn’t been seen on the floor together much (or at all), we can still get a fairly accurate prediction of how effective the lineup will be based on the strengths and weaknesses of the individual players, along with considerations of for the positional and role balance in that lineup. Read more detail at the EvanMiya Blog.

Lineup Projections/Grades Glossary:

  • Poss: Number of possessions with the lineup on the floor.
  • Observed Eff Margin:: Difference between adjusted observed on-court team offensive and adjusted defensive efficiency with the lineup on the floor, adjusted for quality of opponent players faced by the lineup. A higher value is better.
  • Predicted Eff Margin: A lineup’s predicted team efficiency margin against an average D1 opponent, in points per 100 possessions. This prediction takes into account how well the lineup has performed on the floor together (if at all), along with the individual skills of the players in that lineup, and positional and offensive role balance in that lineup.
  • Offense: A lineup’s predicted offensive efficiency against an average D1 opponent in points per 100 possessions.
  • Defense: A lineup’s predicted defensive efficiency against an average D1 opponent in points per 100 possessions.
  • 3PT%: A lineup’s predicted three-point shooting percentage against an average opponent.
  • 2PT%: A lineup’s predicted two-point shooting percentage against an average opponent.
  • FT%: A lineup’s predicted free throw shooting percentage against an average opponent.
  • Scoring Volume: A lineup’s average predicted points per 100 possessions among all 5 players, based on predicted shot usage and efficiency.
  • Usage: A lineups’s average usage rate, which measures how much a player is used to create opportunities for the offense.
  • Assist Rate: A lineup’s predicted assist rate against an average opponent. Assist Rate is the percentage of teammate made field goals that the player assisted while on the court.
  • Turnover %: A lineup’s predicted turnover percentage against an average opponent. Turnover percentage is the percentage of offensive possessions that end in the player turning the ball over while on the court.
  • O-Reb %: A lineup’s predicted offensive rebound percentage against an average opponent. Offensive rebound percentage is the percentage of possible offensive rebounds that the player secured while on the court.
  • D-Reb %: A lineup’s predicted defensive rebound percentage against an average opponent. Defensive rebound percentage is the percentage of possible defensive rebounds that the player secured while on the court.
  • Steal %: A lineup’s predicted steal percentage against an average opponent. Steal percentage is percentage of defensive possessions that end in the player stealing the ball while on the court.
  • Block %: A lineup’s predicted block percentage against an average opponent. Block percentage is the percentage of opponent two-point field goal attempts that the player blocked while on the court.”
  • Foul %: A lineup’s predicted personal fouls committed per 100 possessions.
  • Experience: A lineups’s average number of career games played.
  • Height: A lineup’s average height in inches.

Observed On-Court Lineup Performance:

Lineup Projections and Grades:

Lineup Balance Grades:




Glossary:

  • MVP Score: An overall score that rates players by how worthy they are to be called the “most valuable player”. This combines the Indispensability Score and some of the Bayesian Performance Rating and Box BPR metrics.
  • Indispensability Score: A value that quantifies how much worse off the player’s team would be if he were not available. This is a good starting point for evaluating how valuable a player is to his team, without being biased towards players on better teams.
  • OBPR: Offensive Bayesian Performance Rating reflects the offensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the offensive strength of other teammates on the floor with him, along with the defensive strength of the opponent’s players on the floor. OBPR is interpreted as the number of offensive points per 100 possessions above D1 average expected by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • DBPR: Defensive Bayesian Performance Rating reflects the defensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the defensive strength of other teammates on the floor with him, along with the offensive strength of the opponent’s players on the floor. DBPR is interpreted as the number of defensive points per 100 possessions better than (below) D1 average expected to be allowed by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • BPR: Bayesian Performance Rating is the sum of a player’s OBPR and DBPR. This rating is the ultimate measure of a player’s overall value to his team when he is on the floor. BPR is interpreted as the number of points per 100 possessions better than the opponent the player’s team is expected to be if the player were on the court with 9 other average players. A higher rating is better.
  • Box OBPR: Box Offensive Bayesian Performance Rating is an estimate of a player’s offensive value, based only on his individual stats. This serves as a prior starting point when calculating OBPR.
  • Box DBPR: Box Defensive Bayesian Performance Rating is an estimate of a player’s defensive value, based only on his individual stats. This serves as a prior starting point when calculating DBPR.
  • Box BPR: Box Bayesian Performance Rating is the sum of a player’s Box OBPR and Box DBPR. This rating is an estimate of a player’s overall value, based only on his individual stats.



This service has been approved in accordance with NCAA bylaws, policies, and procedures. NCAA Division basketball coaches are permitted to subscribe to this recruiting/scouting service. All transfers reported by VerbalCommits.com

Transfer Portal Rankings Glossary:

  • Transfer Ranking: The quality of the transfer based on a 5-star ranking system, using our projections for each player.
  • OBPR 2025*: A player’s projected Offensive BPR for the upcoming season. Offensive Bayesian Performance Rating reflects the offensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the offensive strength of other teammates on the floor with him, along with the defensive strength of the opponent’s players on the floor. OBPR is interpreted as the number of offensive points per 100 possessions above D1 average expected by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • DBPR 2025*: A player’s projected Defensive BPR for the upcoming season. Defensive Bayesian Performance Rating reflects the defensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the defensive strength of other teammates on the floor with him, along with the offensive strength of the opponent’s players on the floor. DBPR is interpreted as the number of defensive points per 100 possessions better than (below) D1 average expected to be allowed by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • BPR 2025*: A player’s projected BPR for the upcoming season. Bayesian Performance Rating is the sum of a player’s OBPR and DBPR. This rating is the ultimate measure of a player’s overall value to his team when he is on the floor. BPR is interpreted as the number of points per 100 possessions better than the opponent the player’s team is expected to be if the player were on the court with 9 other average players. A higher rating is better.
  • HS Recruit Ranking: The quality of the player as a high school prospect based on high school composite recruiting rankings.
  • Poss: Number of possessions played in the most recent season.
  • Box OBPR: A player’s Box OBPR for the most recent season played. Box Offensive Bayesian Performance Rating is an estimate of a player’s offensive value, based only on his individual stats. This serves as a prior starting point when calculating OBPR. It also usually aligns closely with the general public consensus on a player’s offensive ability based on common stats.
  • Box DBPR: A player’s Box DBPR for the most recent season played. Box Defensive Bayesian Performance Rating is an estimate of a player’s defensive value, based only on his individual stats. This serves as a prior starting point when calculating DBPR. It also usually aligns closely with the general public consensus on a player’s defensive ability based on common stats.
  • Box BPR: A player’s Box BPR for the most recent season played. Box Bayesian Performance Rating is the sum of a player’s Box OBPR and Box DBPR. This rating is an estimate of a player’s overall value, based only on his individual stats.
  • +/-: A player’s plus-minus for the most recent season played. It is the number of points scored for the player’s team with him on the court, minus the number of points scored by the opponent with him on the court.
  • Adj Team Off Eff: A player’s Adjusted Team Offensive Efficiency for the most recent season played. It is the team’s offensive efficiency (points scored per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A higher value is better.
  • Adj Team Def Eff: A player’s Adjusted Team Defensive Efficiency for the most recent season played. It is the team defensive efficiency (points allowed by opponent per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A lower value is better.
  • Adj Team Eff Margin: A player’s Adjusted Team Efficiency Margin for the most recent season played. It is the difference between adjusted team offensive and adjusted defensive efficiency with player on the court. A higher value is better.
  • Role: An estimate of a player’s offensive role based on his individual stats and team contributions. An estimated role of 1 corresponds to being the “creator” in the offense, and a 5 corresponds to being the “receiver”. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.

BPR Interpretation Example: If Jimmer Fredette had an Offensive BPR of 4.5, a Defensive BPR of -0.5, and a BPR of 4.0, this would mean the following: If Fredette were on the court with 9 other D1 average players, his team’s offense would be 4.5 points per 100 possessions better than average, or if he were not on the floor and were replaced by another D1 average player. Similarly, his team’s defense would be expected to be 0.5 points per 100 possessions worse (conceding 0.5 PP100 more) while he’s on the floor. Overall, his team would be expected to outscore the opponent by 4.0 points in a 100 possession game.



CBB Game Predictions


EvanMiya.com Matchup Preview

Or preview a hypothetical matchup by selecting teams below:
Score Calculation
Tale Of The Tape


Bracketology

Play-in teams are denoted in italics. Autobids are denoted in red. Bracketology projections are computed using a deep learning neural network machine learning algorithm.

First Eight Out

March Madness Tournament Probabilities



This service has been approved in accordance with NCAA bylaws, policies, and procedures. NCAA Division basketball coaches are permitted to subscribe to this recruiting/scouting service. All transfers reported by VerbalCommits.com

Transfer Portal Rankings Glossary:

  • Transfer Ranking: The quality of the transfer based on a 5-star ranking system, using our projections for each player.
  • OBPR 2025*: A player’s projected Offensive BPR for the upcoming season. Offensive Bayesian Performance Rating reflects the offensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the offensive strength of other teammates on the floor with him, along with the defensive strength of the opponent’s players on the floor. OBPR is interpreted as the number of offensive points per 100 possessions above D1 average expected by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • DBPR 2025*: A player’s projected Defensive BPR for the upcoming season. Defensive Bayesian Performance Rating reflects the defensive value a player brings to his team when he is on the court. This rating incorporates a player’s individual efficiency stats and on-court play-by-play impact, and also accounts for the defensive strength of other teammates on the floor with him, along with the offensive strength of the opponent’s players on the floor. DBPR is interpreted as the number of defensive points per 100 possessions better than (below) D1 average expected to be allowed by the player’s team if the player were on the court with 9 other average players. A higher rating is better.
  • BPR 2025*: A player’s projected BPR for the upcoming season. Bayesian Performance Rating is the sum of a player’s OBPR and DBPR. This rating is the ultimate measure of a player’s overall value to his team when he is on the floor. BPR is interpreted as the number of points per 100 possessions better than the opponent the player’s team is expected to be if the player were on the court with 9 other average players. A higher rating is better.
  • HS Recruit Ranking: The quality of the player as a high school prospect based on high school composite recruiting rankings.
  • Poss: Number of possessions played in the most recent season.
  • Box OBPR: A player’s Box OBPR for the most recent season played. Box Offensive Bayesian Performance Rating is an estimate of a player’s offensive value, based only on his individual stats. This serves as a prior starting point when calculating OBPR. It also usually aligns closely with the general public consensus on a player’s offensive ability based on common stats.
  • Box DBPR: A player’s Box DBPR for the most recent season played. Box Defensive Bayesian Performance Rating is an estimate of a player’s defensive value, based only on his individual stats. This serves as a prior starting point when calculating DBPR. It also usually aligns closely with the general public consensus on a player’s defensive ability based on common stats.
  • Box BPR: A player’s Box BPR for the most recent season played. Box Bayesian Performance Rating is the sum of a player’s Box OBPR and Box DBPR. This rating is an estimate of a player’s overall value, based only on his individual stats.
  • +/-: A player’s plus-minus for the most recent season played. It is the number of points scored for the player’s team with him on the court, minus the number of points scored by the opponent with him on the court.
  • Adj Team Off Eff: A player’s Adjusted Team Offensive Efficiency for the most recent season played. It is the team’s offensive efficiency (points scored per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A higher value is better.
  • Adj Team Def Eff: A player’s Adjusted Team Defensive Efficiency for the most recent season played. It is the team defensive efficiency (points allowed by opponent per 100 possessions) with player on the court, adjusted for strength of opponent players faced. A lower value is better.
  • Adj Team Eff Margin: A player’s Adjusted Team Efficiency Margin for the most recent season played. It is the difference between adjusted team offensive and adjusted defensive efficiency with player on the court. A higher value is better.
  • Role: An estimate of a player’s offensive role based on his individual stats and team contributions. An estimated role of 1 corresponds to being the “creator” in the offense, and a 5 corresponds to being the “receiver”. This estimate comes from Daniel Myers’ Box Plus Minus 2.0.

BPR Interpretation Example: If Jimmer Fredette had an Offensive BPR of 4.5, a Defensive BPR of -0.5, and a BPR of 4.0, this would mean the following: If Fredette were on the court with 9 other D1 average players, his team’s offense would be 4.5 points per 100 possessions better than average, or if he were not on the floor and were replaced by another D1 average player. Similarly, his team’s defense would be expected to be 0.5 points per 100 possessions worse (conceding 0.5 PP100 more) while he’s on the floor. Overall, his team would be expected to outscore the opponent by 4.0 points in a 100 possession game.

Current Big Board:


Reorder by dragging players up or down 

                        

                      

                      

                        
                        
                      

                    

                  

                  
                

              

            

            
            

              

                

                  

                    

                      

                    

                    

                      

                        

                          

                          

                        

                        

                          

                            
                            

                              
                              
                            

                          

                        

                        

                          

                            
                            

                            

                              

                                
                                
                              

                              

                                
                                
                              

                            

                          

                        

                      

                      

                        

                          

                        

                      

                    

                  

                  
                

                

                  

                    

                      
Player Overall Grades

                    

                    

                      
                    

                  

                  
                

                

                  

                    

                      
Player Individual Skill Projection Grades

                    

                    

                      

                    

                  

                  
                

                

                  

                    

                      

                    

                    

                      

                      

                        
                        

                          
                          
                          
                        

                      

                    

                  

                  
                

                

                  

                    

                      

                    

                    
Player Projections Explanation:


All player projections take a single stat, such as three point percentage, and predict that stat for the rest of the year, taking a player’s game-by-game history over time and accounting for opponent strength, offensive usage, expected year-by-year improvement, and recent form. For younger players, high-school recruiting profiles are also used to form a starting projection at the beginning of their freshman year, which become less informative toward their current projection as they play more games in college. For some statistics, recent form (how a player is performing in that statistical category recently) is much more important than their overall career average in that stat, while for others recent form isn’t as predictive of future performance. For a more detailed explanation, read up on it here.



                  

                  
                

              

              

                
                
              

            

            

              

                

                  

                    

                      

                    

                    

                      

                        

                          

                            
                            

                              
                              
                            

                          

                        

                        

                          

                            
                            

                              
                              
                            

                          

                        

                        

                          

                        

                      

                      

                        

                          

                        

                        

                          

                            
                            

                              
                              
                            

                          

                        

                        

                          

                        

                      

                      

                        

                          Player Tiers:
                        

                      

                      

                        

                          
                            
                          
                        

                      

                      

                        

                          
                        

                      

                      

                        

                      

                      

                        
                      

                      

                      
Player Projections Explanation:


All player projections take a single stat, such as three point percentage, and predict that stat for the rest of the year, taking a player’s game-by-game history over time and accounting for opponent strength, offensive usage, expected year-by-year improvement, and recent form. For younger players, high-school recruiting profiles are also used to form a starting projection at the beginning of their freshman year, which become less informative toward their current projection as they play more games in college. For some statistics, recent form (how a player is performing in that statistical category recently) is much more important than their overall career average in that stat, while for others recent form isn’t as predictive of future performance. For a more detailed explanation, read up on it here.


Player Projections Leaderboard Glossary:


    

  • 3PT%: A player’s predicted three-point shooting percentage against an average opponent, adjusted for usage.
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  • 2PT%: A player’s predicted two-point shooting percentage against an average opponent, adjusted for usage.
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  • FT%: A player’s predicted free throw shooting percentage against an average opponent.
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  • Scoring Volume: A player’s predicted points per 100 possessions based on predicted shot usage and efficiency.
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  • Assist Rate: A player’s predicted assist rate against an average opponent, adjusted for usage. Assist Rate is the percentage of teammate made field goals that the player assisted while on the court.
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  • Turnover %: A player’s predicted turnover percentage against an average opponent, adjusted for usage. Turnover percentage is the percentage of offensive possessions that end in the player turning the ball over while on the court.
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  • Playmaking Score: A player’s predicted playmaking score, which combines predicted assist rate and turnover rate to measure a player’s ability to create plays for others with the ball in his hands.
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  • O-Reb %: A player’s predicted offensive rebound percentage against an average opponent, adjusted for usage. Offensive rebound percentage is the percentage of possible offensive rebounds that the player secured while on the court.
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  • D-Reb %: A player’s predicted defensive rebound percentage against an average opponent, adjusted for usage. Defensive rebound percentage is the percentage of possible defensive rebounds that the player secured while on the court.
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  • Rebounding %: A player’s predicted offensive + defensive rebounding rate. See O-Reb % and D-Reb % for more detail.
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  • Steal %: A player’s predicted steal percentage against an average opponent. Steal percentage is percentage of defensive possessions that end in the player stealing the ball while on the court.
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  • Block %: A player’s predicted block percentage against an average opponent, adjusted for usage.. Block percentage is the percentage of opponent two-point field goal attempts that the player blocked while on the court.
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  • Foul %: A player’s predicted personal fouls committed per 100 possessions.
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  • Defensive Value: A player’s defensive per-possession value to a team, against an average opponent, as measured by Defensive BPR. DBPR reflects the defensive value a player brings to his team when he is on the court.
    • 



                    

                  

                  
                

              

            

            

              

                

                  

                    
                  

                  

                    

                      

                        

                          

                        

                        

                          

                          

                          
                          

                          

                          Observed On-Court Lineup Performance:
                          

                          

                          

                          

                          Lineup Projections and Grades:
                          

                          

                          

                          

                          Lineup Balance Grades:
                          

                          

                          

                          

                          

                        

                      

                      
                    

                  

                

              

              

                
                
              

              

                
                
              

              

                
                
              

              

                
                
              

              

                
                
              

              

                
                
              

              

                
                
              

            

            

              

                

                  

                    
                  

                  

                    

                      

                        

                          

                        

                        

                          

                          

                          

                          

                          

                          

                          
                          

                          

                          

                        

                      

                      
                    

                  

                

              

            

            

              

                

                

                  

                    

                      
NIL Market Value Settings

                    

                    

                      

                        

                          

                        

                      

                      

                        

                          
                        

                      

                      

                        

                          

                        

                      

                      For more detail on how to use the Market Settings as well as everything else in the Suite, check out the video demo here.
                      

                        
                        
                      

                    

                  

                  
                

              

            

            

              

                

                  

                    

                      

                        

                          

                        

                        
What’s New?


June 4th, 2025


A new Roster Outlook tool has been added, which allows you to see preseason outlook for any team based on the custom selection of players you pick.


April 3rd, 2025


The Front Office Suite package is now available for coaches and GMs. You can find the announcement here, and email evanmiyainfo@gmail.com for more details.


February 10th, 2025


The pre-tournament ratings for 2023-24 have been updated after not correctly loading previously.


January 29th, 2025


There’s a new Team Resumes page that measures win quality and loss quality for all teams.


January 22nd, 2025


There’s a new dedicated On-Off Splits page in the Team Breakdown tool.


December 3rd, 2024


The new Lineup Grades, Projections, and Optimizer tool is live for premium subscribers! Find out more here.


October 23rd, 2024


The new Player Skill Projections tool is live for premium subscribers! Find out more here.


October 10th, 2024


Preseason team and player projections for 2024-25 are live!


May 6th, 2024


Added notes for top transfers in the portal. Use the “Show EvanMiya Notes” filter to see them. Available for Strategist members only.


March 16th, 2024


Pre-tournament team ratings from previous seasons are available on the Team Ratings page now. Use the “Use Pre-Tournament Ratings” filter.


March 12th, 2024


You can now preview any hypothetical matchup on the Matchup Preview page by selecting custom teams.


February 28th, 2024


New team ratings model is live on the team ratings page! There is also a new Matchup Preview page available for all upcoming games.


February 5th, 2024


You can now link to specific pages on the website by copying the url.


January 15, 2024


Download to CSV buttons were added to the Player Ratings, Team Ratings, Game Predictions, and D1 Lineups pages.


January 13, 2024


The website has a fresh look, with updated blue-orange color scheme that’s more color-blind friendly, and updated tables that now include tooltips so that you can hover over a column name and see the explanation.


November 6, 2023


Game predictions with Vegas odds for games are live.


October 12, 2023


Preseason team and player projections for the 2023-24 season are live!


A few other offseason notes:


    

  • The Bayesian Performance Rating model for player evaluation has had a few tweaks over the off-season in order to lead to better performance. The main change is that we no longer filter out garbage-time possessions for players or teams anymore. We initially used this method as a way of only evaluating the most meaningful possessions in games. However, after a careful analysis, we found that this led to slightly less accurate player ratings, so we have decided to use all possessions going forward. Historical tables have been updated everywhere to reflect this change.
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  • The team ratings model received a massive overhaul, which will be more fully revealed in the weeks leading up to the start of the season.
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Overview


Welcome to EvanMiya College Basketball Analytics, trusted by over 100 Division 1 CBB programs. On the site you can find team ratings, player ratings, lineup metrics, transfer portal rankings, game predictions, and much more. The main objective of our work is to assess college basketball team and player strength. We have created an advanced statistical metric, Bayesian Performance Rating (BPR), which quantifies how effective a team or player is, using advanced box-score metrics, play-by-play data, and historical information. This metric is predictive in nature, which means that each rating is fine-tuned to predict performance in future games.


There are several pages of analysis (plus several more that appear when appropriate):


    

  • Team Ratings: We assess the strength of each team by calculating offensive and defensive ratings that reflect the team’s offensive and defensive efficiency, while accounting for other factors, such as game pace and opponent strength. Read more about the new team ratings methodology here.
    • 

  • Player Ratings: We quantify the value of each player to his team on both offense and defense. A player’s ratings incorporate his individual efficiency statistics, along with his impact on the court for his team, which is assessed by looking at how successful his team was in every possession he played. These ratings account for the strength of all other players on the floor with that player in each of his possessions that he played.
    • 

  • Player Projections: This tool takes each player’s game-by-game history and quantifies their skill level in every major statistical category (three-point shooting, rebounding, steals, etc.) by predicting how well they will perform in that stat moving forward. These projections adjust for important contextual variables across their career, including opponent strength, offensive usage, expected year-by-year improvement, and recent form. You can read more about the tool here.
    • 

  • Lineup Metrics and Projections: We rate all two, three, four, and five man lineups across all of Division 1 basketball, adjusted for the strength of opposing players faced by each lineup. We also predict lineup performance for every 5-man lineup in the country, grading strengths and weaknesses for each based on player personnel. You can read more about the tool here.
    • 

  • Transfer Portal: This tool provides rankings for every player in the transfer portal, updated daily during the portal season. We also have transfer class rankings and advanced transfer scouting reports.
    • 

  • Team Breakdown Tool: This tool provides a more detailed look into player and lineup metrics for each team.
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  • Keys to Victory: We provide automated keys to victory for every team and provide tables and visualizations for exploring how different metrics impact a team’s performances.
    • 

  • Game Predictions: Our advanced statistical model predicts the results of every game and provides comparisons to Vegas lines as well as “Best Bets”. You can read more about the Game Predictions model here. We also provide Matchup Previews for upcoming games, which includes predicted score calculations, team comparisons, roster breakdowns, and injury reports.
    • 



Now for some more detail into how we get these numbers:


Collecting Data


We have box score data available for every game played in the each college basketball season, along with play-by-play data, which includes substitutions. The possession by possession data is the main component used to drive our analysis.


Adjusting for the strength of opposition


At both a team and player level, our metrics adjust for the strength of opposition for every possession played. For players, this includes an adjustment for the individual level of every single opposing player on the floor for a possession, along with the strength of teammates as well.


Tempo free statistics


All of our metrics adjust for the pace of play in a game by looking at efficiency on a per-possession basis.


Bayesian Performance Rating


We have created an advanced statistical metric, Bayesian Performance Rating (BPR), which quantifies how effective a player is, using advanced box-score metrics, play-by-play data, and historical information (for the basketball metric nerds, this is a highly technical version of an adjusted plus-minus). This metric is predictive in nature, which means that each rating is fine-tuned to predict performance in future games.


BPR quantifies the value of each player to his team on both offense and defense. A player’s ratings incorporate his individual efficiency statistics, along with his impact on the court for his team, which is assessed by looking at how successful his team was in every possession he played. These ratings account for the strength of all other players on the floor with that player in each of his possessions that he played. Each player has an Offensive BPR and a Defensive BPR, which are added together to make the player’s overall BPR. Very good players will have higher positive offensive and defensive ratings, with the average D1 player having an Offensive BPR and Defensive BPR of 0. Like other adjusted plus-minus metrics, BPR values are interpreted as the expected points per 100 possessions better than a D1 average player while on the floor.


The BPR statistical model is trained on data going back to 2011, making it the most fine-tuned player evaluation metric in college basketball.


First Stage: Historical Stats


The first stage in forming a player’s rating is in the form of a projection for the season, based on that player’s statistics and metrics in previous seasons, along with other predictive information, such as recruiting ratings. Though the historical information does not influence BPR much by the end of a season, it is incredibly useful as it allows for Bayesian Performance Rating to be effective in assessing a player’s impact, even when he hasn’t played much (or at all) in the current season.


Second Stage: Individual Stats


The second stage in forming a player’s rating is his Box Bayesian Performance Rating (Box BPR), which is an estimate of a player’s impact on both ends of the court, using only his individual box score statistics. Box BPR, which is essentially our own version of a Box-Plus-Minus, can give us a good initial estimate of a player’s statistical worth. Though we don’t want to use Box BPR as the final representation of a player’s effectiveness, we can still use the metric to help guide our final ratings by using it as a starting point.


Third Stage: Play-by-Play Impact


The third stage looks at every possession a player played, attempting to quantify his value to his team by looking at how efficiently his team performed on offense and defense for those plays. In addition, we also adjust for the strength of his teammates on the court with him, along with the strength of opposing players for each possession he was on the court. Essentially, our model finds the offensive and defensive rating for each player that can best explain the results from every possession that occurred from the season, for all players. The Box BPR is the starting point for a given player, but the rating will move up if he had more of an impact than his individual stats suggested, or vice versa. In some cases, the final BPR will be very close to the Box BPR, and in other cases they will be very different. Players who look really good on the stat sheet often evaluate well, but equally so, guys who control the game beyond what their stats convey will also be credited accordingly.


Team Ratings


We have a new team strength model, called “Relative Ratings”, that ranks teams based on how they would perform head-to-head against other teams of similar quality. Each team has a true offensive and a true defensive rating that best explains all of the real game results that are observed from the season, while also incorporating other predictive statistics, such as team historical information. Additionally, we account for matchup-specific variables, such as how well a team plays against elite competition versus weaker competition, and whether a team performs better in fast paced or slow tempo games. Read more here at the EvanMiya.com blog.


How To Use BPR


The purpose of Bayesian Performance Rating is to identify the players who are having the biggest impact on the offensive and defensive side of the ball. BPR cannot provide everything that an eye-test can, but is a very helpful tool to either confirm what we thought was true of a player, or provide insight into trends we could have missed. By sorting a roster by BPR, the order will often be close to what you might have expected after watching the games. However, it is helpful to note which players evaluate much higher or lower than we might have expected, and to try to explain why.
When I am trying to understand why a player has the rating that he does, I look at three stats, in order, which are all listed in the Team Breakdown Tool - Players page for each player.


    

  1. Box Plus Minus

      

    • Box Offensive BPR and Box Defensive BPR sum up a player’s individual efficiency stats into one number that estimates effectiveness on that side of the court. Since this serves as the starting point for the final BPR calculation, it’s the first place I look if I am trying to explain a particular player’s evaluation. If a player’s Box BPR is higher than expected, it might be because he was more efficient in some statistical category on a per possession basis than I realized. 
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    2. 

  2. Adjusted Team Efficiency

      

    • The metrics in this category tell how many points per 100 possessions a team scored or conceded with that player on the floor. This does a calculation of efficiency on both sides of the court on a per possession basis, and adjusts for the strength of opposition players faced by that lineup. Often, a player who has a higher BPR on his team also has one of the higher Team Efficiency Margins, since this is a huge component to the calculation of the rating.
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    3. 

  3. Average Opponent BPR

      

    • This shows the average rating of the individual opponents faced by a player when he was on the floor. If a player has a higher Avg Opp BPR than other teammates, this indicates that he had to play against better players when he was on the floor, and his BPR will be adjusted higher accordingly.
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    4. 



Additionally, we have also included each player’s estimated position and offensive role in the Team Table, which is based on individual stats and team contributions. An estimated position of 1 corresponds to being a point guard, and a 5 corresponds to being a center. An estimated offensive role of 1 corresponds to being the “creator” in the offense, and a 5 corresponds to being the “receiver”. These can be helpful see if a player’s statistical contribution was similar to how they were envisioned to be helping the team. Bayesian Performance Rating is not biased based on position or offensive role.


                          
                        

                      

                      
                    

                  

                

              

            

            

              

                

                  

                    

                      

                    

                    

                      

                        

                          

                        

                        

                          

                        

                        

                          

                        

                        

                          

                        

                      

                      
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About Me


My name is Evan Miyakawa, and I have my doctorate in statistics. I graduated with my Ph.D. from Baylor and my Bachelor’s Degree from Taylor University. You can find out more on my LinkedIn page.


My college basketball research has been featured in articles by ESPN, Sports Illustrated, CBS Sports, the AP, and many others. I also have a college basketball newsletter that I post content to frequently.


Contact


Feel free to email me at evanmiyainfo@gmail.com with any questions or requests. I regularly appear on radio shows and podcasts to talk about college basketball. I also work with college basketball coaches who want to utilize analytics for their teams.


You can find links to all my social media platforms at the very top or bottom of every page.


In The Media


See all the latest podcast and radio interviews, article features, and media appearances on the homepage, updated daily.