Career Opportunities. Using the continuity of the entire roster would mask whether their player churn was from peripheral parts or the main engines themselves.

On the opposite end of the spectrum is the dummy statistic, iSRS, which is incredibly sensitive to new team changes.

All rights reserved. Advertise on NBA.com | 2015-16 Player Stats: Advanced 2017-18 Player Stats: Advanced League Champion : Golden State Warriors Most Valuable Player : Russell Westbrook (31.6/10.7/10.4) It uses 2015 to predict 2016, 2016 to predict 2017, and so on. And what should we expect if he changes teams? If a metric predicts a team will finish with an SRS of -5 based on its player values from the previous year, and they actually finish with an SRS of -3, then the metric is off by 2 points. PER may be consistent from year-to-year, but it’s consistently misallocating credit. Now look at our dummy metric, iSRS, which uses only minutes and the team’s result to evaluate players. Our reasoning for presenting offensive logos. In other words, if a metric cannot reshuffle its players and accurately predict new player combinations, then it’s likely misallocating credit in the first place. (If you’re wondering about sample size, there were 225 teams in the under-72 percent continuity group.). Privacy Policy / Copyright © NBA Media Ventures, LLC. I divided teams into different groups based on how much of their “core” lineup returned from the previous season. Notice how much better this group does handling new player combinations: Another major takeaway here is how relatively close all these stats are, especially compared to some of the Old Guard metrics from the previous group. All else being equal, that’s pretty good; it means that, for cores that stay together, we can take the PER for an entire team, assume each player will perform exactly the same in the following season, and that team will be within 3 points of its outcome, on average. Your privacy is safe with us. It’s the only metric I tested that looks better when the lineups are shuffled because it’s incredibly uninformative when lineups remain intact. Bryant, who is 19 and bypassed college basketball to play in the NBA, scored a team-high 33 points off the bench, and Jordan scored a team-high 36 points. In other words, if LeBron James averaged 27 points per game last year, should we expect him to average 27 per game this year? Unlike the previous metrics, APM doesn’t completely fall apart when lineups are shuffled, exhibiting a much softer decline in prediction error as lineup continuity is lowered. For these tests, I also converted all metric-values to the same margin of victory (SRS) scale via a regression. Wins Produced (WP) and Win Shares (WS) have a nearly 2:1 ratio, whereas stats like PIPM and APM are fairly similar in variability, regardless of new teammate circumstance. Logos were compiled by the amazing SportsLogos.net. That, and maybe we can permanently retire PER now. Need game-by-game current season team stats & odds in Excel? I’ve plotted the stronger performing set of composites on the same scale below, where “BP” is my Backpicks BPM model and “BBR” is Basketball-Reference’s version. NBA.com Help | These were the two stats that were most sensitive to new teammates when we examined year-to-year stability, yet it appears their volatility is based more on teammate performance than accurately evaluating players.

The majority of those high-continuity teams are actually good; four in every five teams with a core continuity above 88 percent posted positive SRS’s, and points per game is borderline useless for predicting good teams. GP Games Played W Wins L Losses MIN Minutes Played OffRtg Offensive Rating DefRtg Bryant, who is 19 and bypassed college basketball to play in the NBA, scored a team-high 33 points off the bench, and Jordan scored a team-high 36 points. Imagine a metric that thinks Kevin Love was much better than LeBron James while they were in Cleveland together. Or write about sports?

To investigate this, I grabbed the following metrics for every player-season since 1997 (unless otherwise noted) in attempt to glean value and a deeper understanding of these numbers: I started by looking at a metric’s stability from year-to-year. a big man on a team without any backups is more valuable than if he joined the Tim Duncan–David Robinson Spurs).

if Cleveland fell apart with Love but Los Angeles thrived with LeBron). Instead, I hope that the future of composite metrics will honor the distinctions between valuable and good, allowing us to say “with two great shooters and a dominant interior defender, LeBron James’s situational value is worth X points.” For as much as all-time rankers and talking heads want to argue about overall goodness, the coaches, general managers, and certainly many fans crave stats that answer the question “how will this player help this team?”. Many of these stats are picking up signals that clearly reflect player performance, and when they disagree, they provide fodder for discussion and more granular analysis. This could be accurately capturing how differing circumstances or roles dictate value, or it might be inaccurately tied to his teammate’s performance, much like iSRS. Most Valuable Player: Giannis Antetokounmpo (27.7/12.5/5.9), Rookie of the Year: Luka Dončić (21.2/7.8/6.0), Every Sports Reference Social Media Account, Site Last Updated: Tuesday, October 20, 4:30AM. Updates will be available within 2 to 4 hours following the completion of the last game. Scores from any date in BAA/NBA or ABA history. The sample isn’t too large, and there’s no reason to put too much stock in predicting only good teams, but clearly APM is capturing something worthwhile, without any box score information. We can see this clearly when looking at the results since 1978, long before the plus-minus era (the previous graphs spanned 1998-2018): These are all upgrades over the best of the Old Guard metrics, Win Shares. PER, which is heavily influenced by volume scoring, clocks in as the second-most change-immune metric. the official stats partner of the NBA.

• Ad Choices | While this method accounts for injuries, it doesn’t control for aging or other similar confounders, but every metric in the test is susceptible to these flaws. Do you have a blog? These are strong indicators that the plus-minus family is measuring something quite important, even if it can be difficult to tease out the noise at times. But “goodness” is about a player’s average impact from all relevant team scenarios. Since 1997, there have been 41 teams with an SRS of at least 4 and a lineup continuity of at least 88 percent. DraftKings daily picks: Fantasy basketball lineup – January 8, 2019, The Whiteboard: Derrick Jones Jr. has potential as big as his wingspan, Basketball-Reference’s roster continuity calculator, Nylon Calculus: James Harden and True Shooting Charts, The Balance of the Spurs' Season Shifts with Its Defense, Nylon Calculus: The NBA players with the weakest supporting casts, Nylon Calculus: The shooting efficiency of the San Antonio Spurs. Like PER, it’s good at dividing credit when the same core returns. So unlike prior versions of this test, I focused on new teammate combinations, such as James to the Lakers. The Bulls defeated the Lakers 104-83. To figure out what’s going on here, I extended an old Neil Paine study (who himself expanded on similar studies) by using prior season values to predict teams in the following year. iSRS arguably outperforms points per game here, so it might be wiser to cite minutes-on-a-good-team instead of raw points as an indicator of player quality. 2017-18 Player Stats: Advanced 2019-20 Player Stats: Advanced.

Question, Comment, Feedback, or Correction? (The error is actually RMSE, for the technically inclined.) Ben Taylor is the author of Thinking Basketball. Yet it still outperforms PER here! AFP PHOTO VINCENT LAFORET (Photo credit should read VINCENT LAFORET/AFP/Getty Images). He runs a podcast and YouTube channel by the same name, and once ranked the 40-best careers in NBA history. Watch our How-To Videos to Become a Stathead, Subscribe to Stathead and get access to more data than you can imagine. The Bulls defeated the Lakers 104-83.

Winning teams returning the same core do not compile volume scorers, but instead differentiate with their playmaking, defense and role-player interactions. By accessing any information beyond this page, Let’s start with the right side of the chart, when teams essentially return the same core.

and Terms of Use. Since different metrics are on different scales, I’ve charted variability in standard deviations, ordered by the most stable metrics when playing with similar teammates: Unsurprisingly, points per game is the most consistent of these numbers from year-to-year when teams remain largely unchanged. Fan Relations FAQ |

2019-2020 2019-2020 NBA Advanced Team Stats. PER and Win Shares peg those teams, on average, within 3 points of their following year performance. you agree to abide by the On the other hand, a metric that is insensitive to team change might be accurately measuring a player’s overall “goodness” (irrespective of circumstantial value), or it might be rigidly measuring something else that is consistent, but inaccurate. For instance, imagine a volatile metric that says Isaiah Thomas was incredibly valuable in Boston but not so valuable in Phoenix. It’s only in 2019, when the rosters were shuffled significantly, that its claim about Love and James could be exposed (e.g. 2018-19 NBA Player Stats: Advanced. 2019-2020 NBA Advanced Team Stats. Over the past two decades, single-value basketball metrics have been popping up like weeds. — but there’s something revealing here. Perhaps most interestingly, my own Box Plus-Minus model (BP) was designed to be more team-independent, and it “wins” this test when comparing lower continuity teams, despite lacking plus-minus data for players. Data Provided By All rights reserved. CHICAGO, UNITED STATES: Los Angeles Lakers guard Kobe Bryant(L) and Chicago Bulls guard Michael Jordan(R) talk during a free-throw attempt during the fourth quarter 17 December at the United Center in Chicago.

Add that number to his new Laker teammates’ projected wins (based on each of their 2018 Win Shares) and we can predict the 2019 team performance.

What we have today is still incredibly helpful — we can see this in how much smarter forecasting systems are. PPG: Points per game, the original player ranker, iSRS: individual SRS, a dummy metric that multiplies a player’s minutes by his team’s SRS (adjusted point differential). Core players drive scheme and strategy and are often fulcrums of interactive effects in basketball. Another baseline metric, if you will, is points per game.

This is by design: iSRS treats all starters as roughly the same, regardless of how they actually played. We'll never pass along your email address to spammers, scammers, or the like. We have tools and resources that can help you use sports data. RPM looks about as good as these other top metrics in these tests, but certainly not better based on a few seasons of information. Copyright © 2000-2020 Sports Reference LLC. Our reasoning for presenting offensive logos. “Value” describes the impact a player has in a given circumstance (e.g. Among those teams, APM is well ahead using this testing method, with an average error of only 2.4 points per squad.

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