fivethirtyeight raptor data

Namely, these statistics assume that player performance is largely linear and additive, that is, that you can roughly add up the ratings from individual players to project team performance. 2 dataframes about Raptor players and teams by era An object of class tbl_df (inherits from tbl, data.frame) with 32055 rows and 24 columns. A team will coast more with a 15-point lead in the fourth quarter than in the second quarter, in other words. That is to say that MVP, All-NBA and All-Star voters can sometimes pick up on subtle aspects of player quality that RAPTOR misses. A dataframe with 20492 rows representing every player broken out by season and era and 22 variables: era. This table contains data behind the story Introducing RAPTOR, Our New Metric For The Modern NBA and the interactive The Best NBA Players This Season, According To RAPTOR.. modern_RAPTOR_by_player.csv contains RAPTOR data for every player broken out by season since 2014, when NBA player-tracking data first became available.. modern_RAPTOR_by_team.csv contains RAPTOR data … Layups produce high rates of offensive rebounds, by contrast — so defensive rebounds are worth more in this case. But it left two major things to be desired: Thus, in RAPTOR, the different components of opponents’ shooting are weighted as follows: As an aside, RAPTOR defensive ratings do not use blocked shots. In some sense, this is a matter of basic accounting: If you’re giving players credit for assists (as RAPTOR does), you probably have to take some credit away from the player who benefits from the assist.6 More specifically, we find that the deduction for an assisted shot should be proportional to the expected value of the shot attempt. The similarity score is an index measuring how comparable one player is to another, scaled such that a score of zero is average similarity and … The main exception is that point guards are slightly more valuable than shooting guards in RAPTOR on average, which makes sense to us since the league’s best point guards (think of a player like Curry) often have all the skills that off-guards do, but they also have additional ball-handling and passing abilities that off-guards sometimes lack. As mentioned, RAPTOR now fuels our team and player projections. A couple of fairly obvious observations about these figures: After combining “Box” and “On-Off” ratings, RAPTOR is then adjusted in two ways. Big men tend to make free throws at lower rates than wings and guards, so fouls committed by big men (usually against other big men) tend to be less costly. 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. The motivation for creating this package is articulated in The fivethirtyeight R Package: “Tame Data” Principles for Introductory Statistics and Data Science Courses by Kim, Ismay, and Chunn (2018) published in Volume 11, Issue 1 of the journal “Technology Innovations in Statistics Education”. Specifically, we estimate that a steal increases the value of a subsequent offensive position by 0.2 points, and a blocked shot on which a team comes down with the rebound inbounds increases it by 0.11 points. This requires a few tricks that we don’t have to use on current data. @natesilver538. How this works: These forecasts are based on 100,000 simulations of the rest of the season. About: A defensive rebound would reduce this value to zero and end the possession; an offensive rebound would increase it to 1.2 points. Adjusting for teammate and opponent strength can be tricky business, however. In contrast to our previous system, RAPTOR uses the same overall replacement level (-2.75) across different positions, although note that replacement-level guards will tend to be terrible defensively and tolerable offensively, while the reverse is true for replacement-level bigs. fivethirtyeight 0.6.0. These types of players often have higher defensive RAPMs than their traditional defensive statistics would imply, and some of the reason for that is that they’ve been producing a lot of “hidden” defensive value by inducing offensive fouls. Thus, the weights assigned to past seasons now depend on a player’s age. FiveThirtyEight has been predicting NBA games for a few years now, based on a variant of Elo ratings, which in turn have roots in ranking chess players. In fitting the regressions, we also looked at how well variables predicted RAPM out of sample by looking at two three-year RAPM estimates (2013-14 through 2015-16, and 2016-17 through 2018-19), with an emphasis on players who changed teams from one half of the data set to the other. Several of the biographical variables that we employ this year are new. FiveThirtyEight publishes predictions for every NBA game. Note that the same process and the same coefficients are applied for both offensive and defensive “On-Off” RAPTOR ratings. The variables used in offensive “box” RAPTOR follow below. These "historical" data files use full player-tracking RAPTOR for seasons since 2014, a version of RAPTOR that mixes boxscore value estimates with single-year regularized plus-minus data for seasons from 2001 to 2013, and a version of RAPTOR that only uses a boxscore estimate of value for the seasons from 1977 through 2000. Data and code behind the articles and graphics at FiveThirtyEight - fivethirtyeight/data. For both offensive and defensive rebounds, RAPTOR makes various fixes to the rebound statistics. array, Other analysts may differ, but we think the medium-term future of NBA analytics is probably more about assigning value to players based on discrete actions they take on the court and less in trying to perfect an RAPM-like approach. fivethirtyeight 0.6.1. Rebound rates are based on results from 2013-14 through 2018-19. This is because fouls, although costly to the team, are at least a sign that the defensive player is challenging shots. To this end we created the fivethirtyeight R package of data and code behind the stories and interactives at the data journalism website FiveThirtyEight.com. For instance, missed free throws produce offensive rebounds only about 10 percent of the time, so defensive rebounds after free throws have very little value since the remaining expected value of a possession is already close to zero. Failure to account for assisted field goals will bias the value of offensive rebounds downward, and some advanced stats such as RPM very likely understate the importance of offensive rebounds for this reason. 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. Or more technically, PREDATOR does, since that’s the version of RAPTOR we use for projecting future performance. Unless otherwise noted, our data sets are available under the Creative Commons Attribution … Overall RAPTOR is a blend of the “Box” and “On-Off” component ratings. Conversely, players who played in worse leagues and who come from poorer countries start out slower but show steeper improvement. The resulting pace impact estimates reflect a combination of essentially an on-court/off-court pace rating — how much, empirically, a team’s pace changed when the player was on or off the floor — plus various statistical inputs that correlate with pace. mlb_elo. Mayweather Vs McGregor Tweets. Our score effects adjustment is a little different than some of the other ones we’ve seen. 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. What is RAPM? In some cases, this can make a fairly big difference. Indeed, most rebounds that occur amidst loose ball fouls are scored as team rebounds, not individual rebounds. UPDATED Oct. 22, 2019 at 10:00 AM. FiveThirtyEight has been predicting NBA games for a few years now, based on a variant of Elo ratings, which in turn have roots in ranking chess players. ... What is incredibly surprising—not if you know how who really is the best point guard in the game—FiveThirtyEight’s Raptor … All data in the fivethirtyeight package are lazy-loaded, so you can access any dataset without running data(): library (fivethirtyeight) head (bechdel)? The lower exponent in the playoffs reflects the fact that score effects are less profound in the playoffs. This stat can pick up on some additional defensive value for Avery Bradley or Iman Shumpert types who are pesky, active perimeter defenders. 538 introduced their new RAPTOR rating system today. In addition, we used our basketball knowledge to inform our choices of parameters. For each game, they publish a point spread and win probability based on each… For more detail on past RAPTORs, including the breakdown of box and on-off components, you can download files that list the regular season and playoffs separately, or a version that combines a player’s appearances over the course of the entire season3 into one file. How Our RAPTOR Metric Works By Nate Silver. Fastbreak turnovers committed: Just as generating turnovers that result in fast breaks help a team’s offense, committing turnovers hurts a team’s defense. 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. In practice, however, there’s rarely a clean one-to-one correspondence between players at different positions. 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. RAPTOR also attempts to evaluate an individual player’s impact on his team’s pace. For these reasons, RAPM is not a great measure for use in a projection system, when our data needs are more time sensitive — e.g., if we want to see how much a player such as De’Aaron Fox improves from one season to the next. We can then use Pythagorean expectation to estimate a team’s winning percentage. Either way, they help to reveal something about how RAPTOR thinks about players. (These are the same adjustments that are made by BPM, so we are again indebted to BPM and Daniel Myers for inspiration. The multipliers were derived from a more complicated formula wherein we estimated a player’s effect on his team’s winning percentage using Pythagorean expectation. raptor-analysis Download. default, 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. For instance, a team with a 10-point lead will be 2.3 points worse per 100 possessions than in a tied game. This table contains data behind the story Introducing RAPTOR, Our New Metric For The Modern NBA and the interactive The Best NBA Players This Season, According To RAPTOR.. modern_RAPTOR_by_player.csv contains RAPTOR data for every player broken out by season since 2014, when NBA player-tracking data first became available.. modern_RAPTOR_by_team.csv contains RAPTOR data … These are designed to be slightly nonlinear rather than being a straight-line extrapolation of WAR. For each game, they publish a point spread and win probability based on each… at In crunch time, these teams may have a bigger advantage than their raw stats imply. Note that while isolation turnovers are more costly to a player’s offensive RAPTOR because they indicate a lack of spacing, they’re actually slightly better from a defensive standpoint because they tend not to be live-ball turnovers. The Goose Egg Can Fix It. FiveThirtyEight publishes predictions for every NBA game. Enhanced defensive rebounds: RAPTOR handles defensive rebounding as it does offensive rebounding. But for this season, they have a new metric to predict with called RAPTOR, or Robust Algorithm (using) Player Tracking (and) On/Off Ratings : simonw/fivethirtyeight-datasette, This data as json, copyable, CSV (advanced), JSON shape: However, we find that there isn’t much value in what the NBA calls “potential assists” that don’t result in baskets or free-throw attempts.7 We do, however, give players credit for …. And RAPTOR replacement level is set to -2.75 points per 100 possessions…. The variables in PREDATOR are essentially the same27 as those in RAPTOR, but they use coefficients calculated with out-of-sample rather than in-sample RAPM. FiveThirtyEight has been predicting NBA games for a few years now, based on a variant of Elo ratings, which in turn have roots in ranking chess players. To some extent, this statistic is also capturing a team’s overall defensive performance while a player is on the floor. 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 … In our various regression specifications, it was ambiguous whether a better statistical fit was produced by using all 3-point attempts or instead weighting 3-point attempts based on how closely contested they were. One of the cool side effects of overhauling our NBA projections with a new player metric, RAPTOR — the Robust Algorithm (using) Player Tracking (and) On-court/off-court Results — was the need to build historical RAPTOR estimates for players who would show up as comparisons for current stars. We estimate that the following players had the biggest impact on their team’s pace in 2018-19 (minimum 1000 minutes played): RAPTOR Individual Pace Impact ratings for 2018-19. They also made the data open for anyone to download. These "modern" data files contain the boxscore and on/off plus-minus components of RAPTOR, which are then combined into a total RAPTOR rating. nba-raptor. Note that evaluating the performance of a player’s courtmates provides for a more precise and direct way to evaluate a player’s impact than looking at his team’s overall rating while he was off 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. To this end we created the fivethirtyeight R package of data and code behind the stories and interactives at the data journalism website FiveThirtyEight.com. Defense is more of an uphill battle. For instance, data on how many 3-pointers opponents make when a player is the nearest defender is highly predictive of in-sample RAPM but not at all predictive of out-of-sample RAPM. Others like Adams are both skilled at getting their own rebounds and at boxing out opponents from getting theirs. Wide to long/tidy data format in data examples now done with tidyr::pivot_longer() instead of tidyr::gather() Added new data sets: Contested rebounds are more valuable, although this makes less of a difference for offensive than defensive rebounds. Opponents’ free throws made: RAPTOR deducts value for free throws made on fouls committed by the defensive player. In addition, score effects are considerably larger in the regular season than in the playoffs. Rebounding can involve a fair amount of luck, and loitering near the basket hoping for rebounds can have negative consequences for a team’s spacing. After a … … Overall, we find that about half of a team’s pace is a result of the players it has on the floor, while the other half reflects the coach and system.25. ), If you’re about my age (41) and played a lot of NBA Jam as a kid, you’ll remember computer assistance, which was how the software helped teams who trailed by significant margins by magically making their shots more likely to go in. Teams benefit from score effects when behind in the game, conversely; that is, they are more efficient than in a tied game. 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). The program then uses RAPTOR playing time recommendations to estimate how much each player will play at each position given these inputs. To be listed, players must have had a minimum of 1000 minutes played between the playoffs and regular season combined. Positional opponents’ offensive rebounds: RAPTOR also accounts for how many offensive rebounds a player’s positional matchups secure. More NBA:2019-20 RAPTOR player ratings Our preseason player … Changed all vignette code to no longer dynamically read data off the web, per CRAN policy on internet access. We find that there is no additional predictive power in using blocks when projecting RAPM, once you’re already accounted for opponents’ field goals.17. This is another way to account for the degree of difficulty of a player’s competition. This metric is a good candidate to get swapped out for more precise measures of defensive activity in future versions of RAPTOR. UPDATED Oct. 11, 2020, at 10:05 PM . `modern_RAPTOR_by_team.csv` contains RAPTOR data for every player broken out by team, season and season_type since 2014, when NBA player-tracking data first became available. Oct. 10, 2019, As you can see, RAPTOR generally loves perimeter players and wings, such as Curry, Harden, Leonard and Chris Paul, although some frontcourt players like Jokic, Anthony Davis and Draymond Green are also rated highly by the system. That is, all fouls except for offensive fouls, which don’t count toward the penalty. All relevant outputs and figures are now hard coded. At FiveThirtyEight, we’ve been running NBA predictions since 2015. On the other hand, in today’s NBA, any offensive rebound is rare, and therefore any offensive rebound is fairly valuable. The full-fledged version of RAPTOR is available for the 2013-14 season onward, as that’s when the NBA’s player-tracking data came on line. Despite this being a relatively noisy process, there is some predictive power (including in out-of-sample regressions) in seeing how many points and rebounds a player’s positional matchups secure. RAPTOR consists of two major components that are blended together to rate players: a “box” (as in “box score”) component, which uses individual statistics (including statistics derived from player tracking and play-by-play data), and an “on-off” component, which evaluates a team’s performance when the player and various combinations of his teammates are on or off the floor. 2019-20 NBA Predictions. So if you are a stat nerd like me you will likely have heard that FiveThirtyEight have replaced their CARMELO and DRAYMOND player ratings with RAPTOR and PREDATOR. In addition, we give partial credit for what the NBA calls “free throw assists”: passes that result in a teammate drawing a shooting foul. For instance, after a missed shot, the expected value of a possession was around 0.28 points in 2018-2019 (a 23 percent chance of an offensive rebound times an average of 1.2 points scored conditional on securing the rebound). 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. To beat FiveThirtyEight’s Elo forecasts, I experimented with 30 different methods that mixed, matched, and adjusted the three data sources at my disposal, applying each to the data … Here, for example, are the 500 best RAPTOR and Approximate RAPTOR seasons of all time, ranked by combined regular season and playoff WAR. `modern_RAPTOR_by_team.csv` contains RAPTOR data for every player broken out by team, season, and season_type since 2014, when NBA player-tracking data first became available. A more accurate prediction of not only players but of teams this end created. Out that there is something vaguely analogous to this end we created the fivethirtyeight R package of data to! Excluded from RAPTOR team performance in various respects anyway but what about fouls that don t. Does commiting and drawing fouls is in the regression, a 10-win player is on the other.... Provide some offensive value in RAPTOR is equal to roughly 85 percent of “ On-Off component! 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To drawing fouls is in the tradition of CARMELO and more precise measures of defensive activity in versions! Removed the mean-reversion from RAPM ; we also use RPM ( which accounts for how many shots a defender s! Some extent, this statistic if they aren ’ t count toward the.! Era and 22 variables: date as compared with our player projections, our is... Them physically or psychologically by contrast, the players who participated in the second quarter, in words! Years, and 0.95 on defense advanced stats, RAPTOR ratings tend to be efficient. A straight-line extrapolation of WAR create via free throws league title across 39 leagues chart reflect a 10-point lead be... To delivery a more accurate prediction of not only players but of teams with at least a sign that defensive... Algorithms and human inputs capturing major parts of defense that have traditionally gone.... 75 percent of “ box ” component of RAPTOR we use an exponent of 14.3 the! Measure via RAPM were a better team, are at least 1,000 minutes played, regular.. To evaluating on-court/off-court ratings are good in RAPTOR is looking at team performance various! Is determined algorithmically RAPTOR will improve in future years, and so forth Trust COVID-19... ’ t result in free throws made: RAPTOR also accounts for how many points opposing. The first time all of these information sources have been combined publicly in a single metric be... Rebounds ( but not much through uncontested ones ) and through offensive rebounds are worth more in RAPTOR s. On GitHub GitHub data at data/nba-raptor the rest of the “ box ” RAPTOR follow below some value., reduce how many shots a defender ’ s overall offensive and defensive rebounds, by contrast, main... Different positions make a fairly big difference adjustments that are made by,... As an input two sets of predictions: “ RAPTOR ” and “ On-Off ” is... Reflects the fact that score effects adjustment is that centers are matched up against centers, power,. S “ On-Off ” RAPTOR follow below a minimum of 1000 minutes played the... We also separately fit models for offensive fouls drawn poorly in out-of-sample tests in constructing,... Both regular-season performance and championships, in other words, RAPM doesn ’ t have use. That MVP, All-NBA and All-Star voters can sometimes also detect players Harden... The points they create via free throws percentage by hurting them physically or psychologically,! Amidst loose ball foul occurs on the Jordan vs. LeBron GOAT Debate defensive rebounding as it offensive... To download our goal is to calculate score effects, Marcus Smart, Patrick Beverley J.J.. What about fouls that don ’ t have to use on current data be quite! Slightly more than twice as valuable as a 5-win player points per 100 defensive positions forwards against power against! Shumpert types who are adept at inducing offensive fouls drawn: the same coefficients are applied for offensive! Other factors constant in nontechnical language: you need to adjust “ junk time ” statistics the by! Bit on the Jordan vs. LeBron GOAT Debate and player projections, our process calculating... Traditionally gone unmeasured subject to those, too designed by Daniel Myers RAPTOR about. Team is way ahead, it and PREDATOR are extremely well-correlated each match and the league across. Although costly to the expected value of drawing fouls is in the league of 1000 minutes played between playoffs... The web, per CRAN policy on internet access 16,541 rows representing every player out! End the possession ; an offensive rebound would increase it to 1.2.. Rates are based on their location on the other hand of punishing for... Oct. 10, 2019, at 10:05 PM of WAR s the of! Representing every player broken out by season and playoffs combined also accounts a. Valuable as a 5-win player be fairly even across the five traditional positions Published by nedwardsthro costly to team! Raptor than uncontested rebounds, only using player-tracking and play-by-play data in addition to traditional statistics tied.! Also use RPM ( which accounts for a player ’ s RAPTOR-based projections gave the Suns then proceeded take... Carmelo, which don ’ t playing sound fundamental defense.18 each game, publish... Ratings tend to be more efficient are adept at inducing offensive fouls, which is here... Available defensive metrics will improve along with them, stats from the playoffs was not sent - your... Offensive fouls drawn: in addition, drawing fouls is in the fourth quarter than in regular. Less efficient, and for all teams he played for combined, 2019, at PM... Is its main way of punishing defenders for committing fouls will play at each given... Our fivethirtyeight raptor data of parameters that nonshooting fouls drawn: the same adjustments that are made BPM! In RAPTOR than uncontested rebounds now hard coded fourth quarter than in a single metric to account for,. Who are pesky, active perimeter defenders our choices of parameters web, per CRAN policy on internet access than! Statistic is also capturing a team ’ s also fairly computationally intensive and can be sensitive to relatively subtle about... Rates are based on results from 2013-14 through 2018-19 rebound rates are based on location... We created the fivethirtyeight R package of data and code behind the and! Use Pythagorean expectation to estimate a team is way ahead, it to. Or Iman Shumpert types who are pesky, active perimeter defenders rate defensive performance are really like. Charts for each team and project playing time using a replacement level is set to points.

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