Good ol’ points scored are in fact the highest-weighted category in offensive RAPTOR: Usage rate: A “usage” is any shooting attempt, turnover or foul drawn that results in free throws, except for fouls (e.g., flagrant fouls and clear path fouls) that result in the team getting the ball back after the free-throw attempt.5 Heaves (shots from beyond half-court, which are almost always taken out of desperation at the end of the quarter) count as only a small fraction of a possession. array, Here are the categories in more detail: Points: This is just what it sounds like. RAPTOR also attempts to evaluate an individual player’s impact on his team’s pace. fivethirtyeightdata: Data and Code Behind the Stories and Interactives at 'FiveThirtyEight' goose. Rebound rates are based on results from 2013-14 through 2018-19. We’re pretty excited about it. We also have a historical version of RAPTOR called Approximate RAPTOR dating back to 1976-1977, the first season after the ABA-NBA merger, but that uses a far more limited range of data. In practice, however, there’s rarely a clean one-to-one correspondence between players at different positions. To account for this, we multiply the sum of a team’s player projections by 0.8 in the regular season and by 0.9 in the playoffs. Wide to long/tidy data format in data examples now done with tidyr::pivot_longer() instead of tidyr::gather() Added new data sets: The Federal Government Wasn’t Tracking COVID-19 Cases In Schools, So Emily Oster Decided To Do It Herself, Trump Hasn’t Pardoned Many People -- But So Far They Have Been Mostly His Friends, Shots within 4 feet other than dunks (colloquially, “layups”), Midrange shots (all 2-pointers not in the paint). Empirically, Nearest defender within 2 feet: 100 percent covered, Nearest defender 2 to 4 feet away: 80 percent covered, Nearest defender 4 to 6 feet away: 57 percent covered, Nearest defender 6-plus feet away: 31 percent covered. Either way, they help to reveal something about how RAPTOR thinks about players. Instead, in assigning players to positions for our depth charts, we deliberately draw from multiple sources to make most players eligible at multiple positions. Some players such as Hassan Whiteside are effective at producing their own rebounds but also allow opposing bigs to secure offensive rebounds at relatively high rates. Here, for example, are the 500 best RAPTOR and Approximate RAPTOR seasons of all time, ranked by combined regular season and playoff WAR. Powered by FiveThirtyEight's RAPTOR player ratings. FiveThirtyEight has 24 repositories available. We find that further iterations (i.e., looking at a player’s courtmates’ courtmates’ courtmates’ ratings) don’t contribute toward predicting RAPM. ... FiveThirtyEight. These estimates were built by figuring out how the limited data kept in earlier eras (box score plus team data and RPM for 2001-2013, and just box score/team data … Because RAPM evaluates players by comparing how a team performs when the player is on or off the court, it struggles with situations where a player creates value for his teammates regardless of whether he’s on the court. There are other player-tracking statistics we believe could be highly helpful to RAPTOR, especially more detailed measures of on-ball defense, so we hope to be able to revisit RAPTOR as additional data becomes available. So in theory, RAPM is a truly comprehensive statistic, measuring all the tangible and intangible ways in which a player contributes to his team’s bottom line. These projections basically involve a three-step process: Other than the adoption of RAPTOR rather than BPM and RPM as the basis for our projections, changes to our projection methodology this season are relatively subtle. What this means is that breakouts for young players (or declines for old players) mostly tend to “stick,” whereas you should expect more mean-reversion if a player shows a sharp apparent improvement or decline in mid-career. Unless otherwise noted, our data sets are available under the Creative Commons Attribution … For each game, they publish a point spread and win probability based on each… The NBA also keeps track of deferred rebounds: when a player has a chance at the rebound but passes it up to a teammate. If a certain variable predicted RAPM well in the in-sample, six-year regression, but not in the out-of-sample, three-year regressions, that’s generally a sign that it reflects luck rather than skill or that it’s too noisy to provide for a reliable indicator of player value. UPDATED Oct. 11, 2020, at 10:05 PM . For the regular season and the playoffs combined, and for all teams he played for combined. This stat can pick up on some additional defensive value for Avery Bradley or Iman Shumpert types who are pesky, active perimeter defenders. Since our player projections use data since the 1976-77 NBA season (the first year after the ABA-NBA merger) we also have to approximate RAPTOR ratings for past seasons, even though modern player tracking and play-by-play data wasn’t available then. Opponents’ defensive rating: Finally, we calculate the average defensive rating of the opponents that the player faced14 (excluding possessions against the player himself). Because pace is partly a function of a team’s coach and system, these ratings were derived from an analysis only of players who switched teams, and seeing which factors were persistent in predicting pace from one team context to the next. It should also be an unbiased measure, not overvaluing or undervaluing any particular type of skill relative to its actual value on the court. New algorithms that put a wider set of data together to delivery a more accurate prediction of not only players but of teams. stream all rows, GraphQL API for nba-raptor/modern_RAPTOR_by_player, Introducing RAPTOR, Our New Metric For The Modern NBA, The Best NBA Players This Season, According To RAPTOR, Points above average per 100 possessions added by player on offense, based only on box score estimate, Points above average per 100 possessions added by player on defense, based only on box score estimate, Points above average per 100 possessions added by player, based only on box score estimate, Points above average per 100 possessions added by player on offense, based only on plus-minus data, Points above average per 100 possessions added by player on defense, based only on plus-minus data, Points above average per 100 possessions added by player, based only on plus-minus data, Points above average per 100 possessions added by player on offense, using both box and on-off components, Points above average per 100 possessions added by player on defense, using both box and on-off components, Points above average per 100 possessions added by player on both offense and defense, using both box and on-off components, Wins Above Replacement between regular season and playoffs, Wins Above Replacement for regular season, Predictive points above average per 100 possessions added by player on offense, Predictive points above average per 100 possessions added by player on defense, Predictive points above average per 100 possessions added by player on both offense and defense, Player impact on team possessions per 48 minutes. In general, players who come from wealthy countries and who play in higher-quality international leagues start out of the gate faster but do not necessarily show as much improvement following their first few NBA seasons. While this is a good rule of thumb for players in the middle of their career, it’s too conservative a weighting scheme for very young or very old players. PREDATOR and RAPTOR have a 0.98 correlation on offense, and 0.95 on defense. And defensive rebounds after shots that produce a high rate of offensive rebounds (such as layups and other shots near the rim) are worth more than rebounds on shots that don’t. Green’s +15.2 On/Off RAPTOR (so, using plus/minus data only) in 2015-16 was the best of the tracking era among players with at least 100 minutes in a season. This rating combines player tracking data, play by play data, traditional box score data, and plus minus data to create a new all-in-one metric. 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