Glossary

This page of our site will include act as an evergreen glossary of statistics used on BBall Index. We will make update as appropriate, and hope to expand into more comprehensive explanations/graphics/videos over time for metrics from us and elsewhere.

Read about our LEBRON impact metric on its introduction page here.

 

Opportunity & Usage Metrics

On-Ball %

On-Ball % is the percentage of the time a player has the ball during their team’s offensive possessions.

On-Ball %= (Time of Possession/Offensive Possessions) / (Seconds on Offense per Possession on Court/Offensive Possessions)

Example: If LeBron James’ On-Ball % is 25%, that means LeBron had the ball in his hands for 25% of his team’s offensive time of possession when he was on-court.

 

Consistency

Our consistency calculations look at game-by-game performance/minutes and calculate their variance, using coefficient of variation. Players that have higher consistency ratings have similar performance/minutes game to game. Higher consistency of performance can be good, but players with lower consistency and outlier performances also have value. For more information on the methodology and calculations, go to this link or this one.

 

Scoring Possessions

A “scoring possession” is any possession ended by a player through a shot (made or missed), turnover, or trip to the foul line.

Some examples for an Anthony Davis post up:

  • He shoots and misses – Yes, this is a scoring possession
  • He is fouled while in the bonus and goes to the free throw line – Yes, this is a scoring possession
  • He passes back out for a reset – No, this is not a scoring possession
  • He shoots and misses, then gets the offensive rebound and scores – Yes, and this would count as 2 scoring possessions
  • He shoots and misses, then gets the offensive rebound and passes out – Yes, and this would count as 1 scoring possession for AD and then whoever ends up shooting/turning the ball over/getting a FT trip would later have a second scoring possession.
  • He turns the ball over on a pass out – Yes, this is a scoring possession
  • He passes to a cutter who scores, giving him an assist – No, this is not a scoring possession

 

Team Minutes/Possession/Touch/etc. Share

These calculations look at the percentage of the team’s minutes/possessions/touches/etc. that an individual player commands. If a player has a 5% touch share, their touches make up 5% of their team’s total touches per game.

Formula: Value Share = Player’s Value / Team Total Value

 

Time of Possession

Time of Possession is the length of time a player has the ball in their hands. At the team level, we use this data to calculate how long the ball is in a player’s hands vs in the air for passes.

Formula: Time of Possession = Touches * Time per Touch

 

Total Offensive Load

Total Offensive Load is an estimate of how much a player directly contributes to an individual possession through their shooting, creating, passing, and turning the ball over (while attempting to shoot, create, or pass).

Offensive load was designed by Ben Taylor (@ElGee35). For more information on methodology, click here.

Formula: Offensive Load = (Assists – (0.38 * Box Creation)) * 0.75) + FGA + FTA * 0.44 + Box Creation + Turnovers

 

True Usage

True Usage is an estimate of usage that incorporates tracking data to better measure the true usage a player has of the team’s offense. This is done by incorporating potential assists.

True Usage was designed by Seth Partnow (@SethPartnow). For more information on methodology, click here.

 

Contextual Data

Teammate ___ Data

Ex: Teammate LEBRON, or Teammate Off-Ball Gravity

These metrics are estimates of the environment a player plays within based on the lineups they’re used in. These will not be uniform for players on the same team. These are calculated by averaging metric performance for all teammates each player has spent time with, weighing by possessions played with them.

 

Matchup Difficulty

Matchup Difficulty is an estimate of the difficulty a defender takes on with their defensive matchups/assignments. We develop matchup difficulty using partial possession player tracking data, to capture switches, help defense, etc., which allows us to capture how much time a player spends defending each opposing defender (rather than 1 player per possession calculations you may find elsewhere).

Calculations look at the average usage of players defended, as well as the average offensive impact (via O-LEBRON) to derive a final difficulty value.

 

Defensive Positional Versatility

This metric measures how balanced a player’s time spent guarding different traditional positions (PG/SG/SF/PF/C) is. We developed it using partial possession player tracking data to capture switches, help defense, etc. which allows us to capture how much time a player spends defending each opposing defender (rather than 1 player per possession calculations you may find elsewhere). It looks only at actual time spend defending those roles, not the performance by those offensive players in those situations.

The highest Defensive Positional Versatility would be obtained if a player guarded PG, SG, SF, PF, and C 20% each for their time on defense.

 

Defensive Role Versatility

Similar to Defensive positional versatility (see above) this metric looks at how often a player spends guarding players in our offensive roles rather than the traditional 5 positions (PG, SG, SF, PF, C).

 

Foul Trouble Percentage

Our Foul Trouble Percentage shows the percentage of a player’s minutes they’re in foul trouble, using data from PBPStats.com. We define foul trouble as having:

  • 2-5 fouls in Q1
  • 3-5 fouls in Q2
  • 4-5 fouls in Q3 and Q4
  • 5 fouls in overtime

Perimeter Shooting

Openness Rating

Openness Ratings show a z-score value estimating the degree of openness a player has on average for their 3-point attempts. Input data from NBA.com/stats is used, along with some internal calculations (to try to increase accuracy), to derive these values.

 

Percent of 3PTA Open

These values estimate the percentage of a player’s 3-point attempts that are completely open and unimpeded by any defensive pressure. Input data from NBA.com/stats is used, along with some internal calculations (to try to increase accuracy), to derive these values.

 

Average 3PT Shot Distance

These values use SportRadar player tracking data to capture average distance (in feet) from the rim for 3-point attempts. Players with the highest values with have higher percentiles. You’ll see a mix of players heaving the ball (like some centers) and guys like Trae Young and Dame Lillard at the top of the leaderboard. A the bottom, taking closer (easier) shots, you’ll find players with a higher percentage of their 3-point attempts from the (shorter) corners.

 

3-Point Ratios

C&S : PU Ratio: ratio of Catch & Shoot 3-point attempts to Pull Up 3-point attempts

C3 : ATB Ratio: ratio of Corner 3-point attempts to Above the Break 3-point attempts

 

3PT Shot Quality

3-point shot quality looks at all of our data on openness, whether a shot is self created or not, location on the court and internal estimates of player movement on 3s (the same used for stationary vs movement shooter designations for our offensive archetypes) to estimate an overall shot quality on 3-point attempts. These values are represented using z-scores.

 

3PT Foul Rate

3-point foul rate captures the percentage of 3-point attempts a player draws a foul on.

Formula: 3PT Foul Rate = (3-shot Fouls + 3PT & 1 fouls) / (3PA + 3PT & 1 fouls)

 

3PTA Rate

3-point attempt rate is the percentage of a player’s shots taken that are from 3-point distance.

Formula: 3PTA Rate = 3PA / FGA

 

3PT Shot Making

Our Shot Making ratings look at 3-point shooting above expectations based on shot quality (as described above). This answers, “Given the player’s degree of difficulty, how well are they shooting?” These values are represented using z-scores.

If you see a player with a high 3PT% but an average Shot Making rating, you’re likely looking at a player in a favorable situation in terms of quality of shots that’s reaping the benefits of their environment. Likewise, we may see a player with a similar 3PT% but lower Shot Quality, that ends up having a higher Shot Making rating.

 

3PT Shot Creation

Our Shot Creation rating looks at a player’s tendencies to create their own 3-point attempts by looking at unassisted 3-pointers attempted per 100 possessions on the court.

Note: 3PT Shot Creation does not look at proficiency. This is purely capturing whether or not the player is creating their own shot on 3s.

 

3PT Shooting Talent Grade

This metric is made up of a combination of our 3PT Shot Making, 3PTShot Quality, and 3 PT Shot Creation. It also accounts for volume to regress down smaller samples. This seeks to capture how well of a 3-point shooter a player is in a neutral environment.

For example, Will Barton and TJ Warren have the same exact 3PT% but very different Perimeter Shooting grades (A- for Barton, D+ for Warren). Barton is achieving his 3PT% on a higher degree of difficulty (looking at his 3 PT Shot Quality), thus has a higher Shot Making rating. He’s also creating 3-point looks at a far higher rate than Warren (A vs F ratings in 3PT Shot Creation). Those two factors combined result in Barton having an A- while Warren has a D+, and would tell us that Barton is the more talented 3-point shooter (that should perform better in a neutral environment).

 

One on One

Total Isolations

Totals isolations capture a player’s scoring possession volume in one on one situations on both the perimeter and interior.

Formula: Total Isolations = Perimeter Isolation Scoring Possessions + Post Up Isolation Scoring Possessions

 

Total Isolation Impact

Total Isolation Impact seeks to capture the points a player adds above/below what an average player would score if given the same volume of possessions in similar situations.

The next update of this metric will include stabilized values for players with volumes below the calculated thresholds based off of their offensive role. For example, if a player is 15 possessions below the threshold and is a Pick & Pop Big, their data will be infused with 15 average efficiency possessions for Pick & Pop Bigs in that play type, then reduced down to the original possession volume.

Formula: Total Isolation Impact = Total Isolation Points – ((Perimeter Isolation Possessions * League Average Perimeter Isolation Efficiency) + (Post Up Possessions * League Average Post Up Efficiency))

 

Isolation Foul Drawn Rate

Isolation Foul Drawn Rate captures the percentage of isolation scoring possessions a player draws a shooting foul.

Formula: Isolation Foul Drawn Rate = Shooting Fouls Drawn during Isolation Possessions / Total Isolation Possessions

 

Isolation Turnover Rate

This metric shows the percentage of a player’s total scoring possessions spent in perimeter isolation and posting up where they turn the ball over.

Formula: Isolation Turnover Rate = Turnovers during Isolation Possessions / Total Isolation Possessions

 

Off-Ball Movement

Movement Attack Rate

Movement Attack Rate measures the percentage of a player’s first chance half court scoring possessions they spend in one of our two movement categories, either cutting to the rim or in an off-screen action.

Formula: (Off Screen Possessions + Cutting Possessions) / (Half Court Possessions – (Miscellaneous Possessions + Putbacks))

 

Movement Distance Rating

Movement Distance Rating seeks to answer: “does the player cover a lot of ground for the offensive role they’re in?” It’s calculated as offensive feet traveled per minute played, with a role adjustment to adjust for the types of actions a player spends their time in and show distance traveled relative to other players in the same offensive role.

 

Movement Speed Rating

Movement Speed Rating is role adjusted average offensive speed, which captures how fast a player moved relative to other players in their offensive role.

 

Movement Points

Movement Points are all points from cuts (no dump offs) and off-screen scoring possessions.

 

Movement Impact

Movement Impact seeks to capture the points a player adds above/below what an average player would score if given the same volume of possessions in similar situations.

The next update of this metric will include stabilized values for players with volumes below the calculated thresholds based off of their offensive role. For example, if a player is 15 possessions below the threshold and is a Pick & Pop Big, their data will be infused with 15 average efficiency possessions for Pick & Pop Bigs in that play type, then reduced down to the original possession volume.

Formula: Movement Impact = Total Movement Points – ((Non-Dump Off Cutting Possessions * League Average Non-Dump Off Cutting Efficiency) + (Off Screen Possessions * League Average Off Screen Efficiency))

 

Finishing

Adjusted Drives

Adjusted Drives per 75 offensive possessions on court is just that, with a regression of league average driving rate possessions to stabilize small samples.

 

Rim Shot Creation

Rim Shot Creation evaluates how well a player can self-create opportunities at the rim.

Note: this metric doesn’t care about assisted shots at the rim. A player driving and getting to the rim, or posting up and creating their own shots at the rim, will be credited.

These values are represented using z-scores.

 

Drive Passout Rate

Drive Passout Rate is the percentage of drives a player passes to a teammate, rather than attempting to score.

 

Drive Assist Rate

Drive Assist Rate is the percentage of drives a player passes to a teammate and is credited with an assist

 

Drive Foul Drawn Rate

Drive Foul Drawn Rate is the percentage of drives a player draws a shooting foul during their drive.

 

Contact Finish Rate

Contact Finish Rate is the percentage of shooting fouls a player converts on. Without other data to measure contact, shooting fouls are proxied in to estimate that aspect of the game.

 

FG% at Rim

FG% at the Rim shows FG% at the rim, with small samples adjusted downward by a Sigmoid function.

 

Stable Rim FG%

A players field goal percentage on shots at the rim, padded to make it more predictive.

 

Rim Shot Quality

Rim Shot Quality measures how difficult a players shot attempts are at the rim. This includes the quality of contest and type of shot attempted.

These values are represented using z-scores.

 

Rim Shot Making

Rim Shot Making captures how well a player shoots at the rim relative to their shot quality.

These values are represented using z-scores.

 

Finishing Talent

This metric evaluates a player’s ability to get to and finish at the rim, using Rim Shot Creation and Rim Shot Making. You can use this metric to compare among players, with the confidence that degree of difficulty is being captured and adjusted for to allow comparison of players’ talent in as neutralized an environment as possible.

 

Playmaking

Role Adjusted Assist Points

Role adjusted Assist Points per 75 offensive possessions on court shows assist point performance relative to expectation based on others in the same role. This metric seeks to answer: “Are they a good passer for their role?”

We like to use this to help identify players in non-traditional playmaking roles that are good ball movers, as well as separate the true playmakers from the rest among players within roles that will accrue assist volumes just based on what the players are asked to do.

 

High Value Assists

High Value Assists, which some also refer to as Morey Assists, are 3-point assists, rim assists, and free throw assists.

 

Box Creation

Box Creation is an estimate of open shots carved out for teammates by drawing defensive attention using box score metrics only.

Calculations developed by Ben Taylor (@ElGee35). You can read more about his methodology here.

 

Passing Creation Volume

Passing Creation Volume looks at a player’s potential assists per 75 possessions. Potential assists are given regardless of if a teammate makes or misses a shot after receiving a pass. We pad these rates to regress smaller samples back towards the average.

These values are represented using z-scores.

 

Passing Efficiency

Passing Efficiency analyzes how well a player takes care of the ball as a passer, and does so by comparing rates of bad pass turnovers with expected rates, given the player’s ball dominance, how often they’re generating shots for teammates (via Passing Creation Volume), the quality of those shots (via Passing Creation Quality), and the versatility in pass types executed (via Passing Versatility).

If you look just at turnover rates, you’re lumping in a lot of turnovers that have nothing to do with passing.

If looking just at rates of bad pass turnovers, real playmakers will naturally look worse and players rarely creating for others will look better.

To be holistic in capturing all of that, we establish the baseline of what’s expected, given a player’s playmaking ask, to compare with instead and enable smarter analysis.

Here’s a visual example showing how generating high value assists has a natural relationship with bad pass turnovers:

These values are represented using z-scores.

 

Passing Versatility

Passing Versatility analyzes a player’s playmaking ability by quantifying how full the passing repertoire is for a player by looking at Synergy passing data from scoring play types as well as SportRadar data on assist locations. This allows us to gauge who has the most range and versatility in their pass types.

A player may have excellent performance within their passing style but not have the range as a playmaker to make other kinds of passes (kick outs on drives, etc.). This metric identifies that spread of playmaking versatility and rewards players who are more versatile.

Several tiers of spread are identified through the data, which is why you’ll see groups of players with the same values. The higher the spread, the fewer players you’ll see in the tier.

These values are represented using z-scores.

 

Passing Creation Quality

Passing Creation Quality analyzes playmaking ability through the quality of scoring opportunities a player creates for their teammates through their passing. Regardless of whether the teammates makes or misses the look generated.

Data used to calculate Passing Creation Quality includes the location of assists, as well as conversion rates on potential assists for players relative to rates for those same players passed to from other teammates and league average on types of scoring looks.

 

Playmaking Talent

Our Playmaking Talent grade analyzes a player’s playmaking for teammates through their ratings in Passing Creation Volume, Passing Creation Quality, Passing Versatility, Passing Efficiency, and On-Ball Gravity (which has a small weight).

This metric is designed to be as context-neutral as possible, enabling values more accurately capturing true playmaking talent and resulting in stability from year to year, even with players changing teams.

 

Roll Gravity

Team Roll Man Share

Team Roll Man Share is a measure of a teams total roll man possessions that go to an individual player.

 

Roll Man Impact

Please refer to the Isolation Impact or Movement Impact notes in the One on One and Off-Ball Movement sections of the glossary.

 

Screen Assists

Screen Assists capture screens that free up players for a score, crediting the screener with a screen assist.

If you’d like to learn more, ask Jazz Twitter and they’ll tell you all about them.

 

Screening Talent

Our Screening Talent metric is calculated via a private BBall Index dataset that captures how well players screen for each other, looking at contact on screens and value add for players utilizing screens

 

Post Play

Post Up Draw Foul Rate

Post Up Draw Foul Rate shows the percentage of a player’s post scoring possessions they draw a shooting foul.

 

Post Up Impact

Please refer to the Isolation Impact or Movement Impact notes in the One on One and Off-Ball Movement sections of the glossary.

 

Potential Assists per Post Pass

Potential Assists per Post Pass capture the facilitation ability of big men from the post by measuring how often their pass-outs directly lead to a shot attempt by a teammate.

 

Roll Gravity

OReb/DReb Chance

OReb/DReb Chances per 75 possessions on court capture how frequently a player has an opportunity to obtain a rebound, based on their position relative to where the ball was rebounded.

 

Adjusted OReb/DReb Success Rate

Adjusted OReb/DReb Success Rate is a Second Spectrum stat capturing success rate on attempted rebounds, adjusted to exclude times the player deferred a rebound to a teammate.

 

OReb/DReb Positioning

OReb/DReb Positioning shows the average feet away from the rim a player was when they captured their rebounds. We can use this to tell how players are generally positioned on the court. Being closer to the rim will yield a higher percentile and letter grade.

From this, we can tell that Bigs with higher values (and thus lower percentiles) are being utilized more on the perimeter than others. The inverse is true for guards grabbing their rebounds closer to the rim.

 

Real Adjusted OReb/DReb Rate

Real Adjusted Rates use ridge regressions to capture the impact a player has on their team’s performance in a specific area based on their presence on-court.

This, along with Adjusted Reb Success Rates and Adjusted Box Out Rates, can help tell us what kind of rebounder a player is, and how much they help their team based on their role and performance within that role.

Source data is calculated at NBAShotCharts and can be found here.

 

Putback Impact

Please refer to the Isolation Impact or Movement Impact notes in the One on One and Off-Ball Movement sections of the glossary.

 

Adjusted Box Out Rate

Adjusted Box Out Rate is an estimate of defensive box outs per shot from the opposing team while a player is on court, with small samples regressed average box out rates by defensive role.

 

Rebounding Crashing Data

Our rebounding crashing data looks at player performance putting themselves in position to rebound, based on player tracking data on player positioning and positioning when obtaining rebounds.

 

Rebounding Conversion Data

Our rebounding conversion data looks at player performance on obtaining rebounds in contested situations, using various data points to estimate their expected conversion to then compare with actual conversion.

 

Overall Rebounding Talent

Our overall rebounding talent data evaluates player skill sets as rebounders, accounting for their crashing and conversion skills. This is made up of offensive Rebounding Talent and Defensive Rebounding Talent.

 

Matchup Data

All matchup data leverages partial possession player tracking data, which captures which offensive player each defender was defending for each portion of each defensive possession.

This better captures real defensive assignments and switches, help defense, etc. than saying that each defensive player defended one offensive player each possession.

 

Perimeter Defense

On-Ball Defense, Ball Handler Screen Defense, & Off-Ball Chaser Defense

Each of these perimeter defensive metrics look at how a defender lowers shot quality and suppresses attempts. Each metric is adjusted for the average skill level of the offensive players guarded.

The video in this tweet explains more about these three perimeter defensive metrics, which evaluate specific components of perimeter defense through the use of tracking data.

 

Real Adjusted Turnover Rate

Please refer to the Real Adjusted OReb/DReb Rate notes in the Offensive/Defensive Rebounding glossary section.

 

Loose Ball Recovery Rate

Loose Ball Recovery Rate seeks to capture a player’s ability to recover loose balls. Since we’ll only have data on specific participants in loose ball situations, those must be relied upon for this calculation.

Loose balls recovered is simple enough via tracking data, but participation in those situations is based off of loose ball fouls (tried, but collected a foul instead), lost ball turnovers off of steals (had the ball taken from you), and loose balls recovered (succeeded). If a player attempted to recover a loose ball but didn’t initially lose it, eventually get it, or commit a foul along the way, it won’t be tracked here.

Formula: Loose Ball Recovery Rate = Loose Balls recovered / (Loose Ball Fouls + Lost Ball Turnovers Off Steals + Loose Balls Recovered).

This metric was originally calculated by BBall Index’s Krishna Narsu. His initial writeup can be found here.

 

Pickpocket Rating

Pickpocket Rating attempts to capture how active a player is on-ball with steals, using Lost Ball Steals per 75 possessions on court defensively.

Formula: Pickpocket Rating = Lost Ball Steals / 75 Possessions

 

Passing Lane Defense

Passing Lane Defense captures how disruptive players are through their ability to intercept passes and deflect the ball. Passing Lane Defense is a rate stat, showing impact per 75 possessions on the court defensively.

Formula: Passing Lane Defense = Deflections / 75 Possessions + Interceptions / 75 Possessions

 

Defensive Miles / 75

Defensive Miles / 75 captures how far a player travels defensively.

 

Lineup Interior Defense

Please refer to the Lineup Talent notes in the Context Data portion of the glossary.

 

Interior Defense

Rim Deterrence

Rim Deterrence is a role adjusted measure of how a player’s presence on-court impacts opponents’ frequency of attacking the rim. This is done by analyzing how a player’s presence on-court relates to opponents’ shooting at the rim, both relative to teammates and to the league as a whole.

We care about this stat for Bigs, not Guards or nearly as much for Wings.

 

% Rim Shots Contested

This is the percentage of shots at the rim while the player is on the court defensively that they contest.

 

Block Rate on Contests

Block Rate on Contests shows a player’s success rate of blocking shots on the ones they contest.

 

Rim dFG% vs Expected

Rim dFG% vs Expected is the FG% players shoot on shots at the rim above/below what Second Spectrum would expect based on shot locations. Low samples are regressed with league average percentages.

This does not adjust for the shooting ability at the rim of specific players faced.

 

Adjusted Rim Points Saved / 75 Possessions

Adjusted Rim Points Saved / 75 Possessions is a measure of rim protection impact through measuring points “saved” on shots at the rim by the defender based off of their activity in contesting shots at the rim, as well as the disruption on shots at the rim they contest by looking at defensive FG% vs expectations.

This concept was first developed by Seth Partnow, and a writeup on the methodology and math behind the metric can be found here or here. We’ve made a few tweaks to these calculations.

 

Screener Rim Defense

Screener Rim Defense estimates how well a player defends in screen coverages where the screener defender’s focus is defending the rim, such as drop coverage.

 

Screener Mobile Defense

Screener Mobile Defense estimates how well a player defends in screen coverages where the screener defender’s focus is containing a ball handler, such as hedging or trapping.

 

Impact Metics

Link back to explanation articles for LEBRON, RAPTOR, RPM, and BPM 2.0 from this page.

Rebounding, Turnover, FT Rate, and eFG% impact metrics use “Real Adjusted ____ Rate” stats from NBAShotCharts, which look at on/off impact by players in different areas of team success, while accounting for teammate and opponent quality.

 

Luck Adjusted Regularized Adjusted Plus-Minus (LA-RAPM)

LA-RAPM is one of the major components that makes up our flagship impact metric, LEBRON. In simple terms, it measures the point differential when a player is in the game vs sitting on the bench, while accounting for teammate and opponent quality and adjusting for variance-driven outcomes.

 

Stable Metrics

These metrics use a similar padding approach as described here (and what we use for LEBRON) to make metric performance more predictive. This is done by infusing the actual sample of performance in the area of question with an expected performance sample.

 

Overall Shooting Talent

Shooting Talent takes into account a player’s shot making, shot quality, and shot creation. These factors help provide context that box score shooting percentages are lacking.

Shooting talent can be sliced and diced to isolate specific skill sets such as:

  • 3PT Shooting Talent
  • Mid-Range Shooting Talent
  • Finishing Talent
  • Half Court shooting Talent
  • Transition Shooting Talent
  • And more!

Shot Making

Each of our Shot Making metrics evaluate player shooting proficiency while accounting for shot quality in the given area.

Shot Quality

Shot Quality measures how difficult a player’s shot attempts are. It accounts for shot location, type, defense, and movement.

Shot Creation

Shot Creation measures how often a player self-generates shot attempts.

On-Ball Gravity

This metric aims to measure how much attention and resources a team uses trying to defend a player while on-ball. Players with high On-Ball Gravity are ones we’d expect to see double teamed more often than others and see more aggressive screen coverages to get the ball out of their hands.

Off-Ball Gravity

This metric aims to measure how much attention and resources a team uses trying to defend a player when they don’t have the ball. Players that are stronger 3-point shooters will do better in this metric, and if players are able to shoot off movement and utilize off-ball screens to generate 3-point attempts they’ll tend to grade out higher in this metric.

 

Quick Decision Making

This metric measures how often a player makes quick decisions once they received the ball. This incorporates, driving, passing, or shooting.

Quick Decision Making Pass %

This metric measures how often a player makes quick pass once they received the ball.

 

P&R Coverage Versatility

This metric measures how often a defending player plays different coverages in pick and roll. This pertains to the player originally guarding the screener.

These principles apply to DHO Coverage Versatility.

 

P&R Coverage Aggression

This metric measures how aggressive a player is in the pick and roll plays. Blitzing more often results in a higher number in this stat while playing mostly drop will result in a lower number. This pertains to the player originally guarding the screener.

These principles apply to DHO Coverage Aggression.

One on One Talent

This metric looks as how effective a player is in isolation on the perimeter and is post ups compared to league average.

 

Points Per Scoring Possession (PPP)

Points Per Scoring Possession looks at how many points a player scores per scoring opportunity. It’s different from shooting percentage because it takes turnovers and free throw trips into account. It can be broken down into play type to see where a player excels.

Foul Contact Finish Rate

This tracks of how often a players makes the shot on their “And1” opportunities, compared to going to the free throw line for 2 shots.