Andrew Wiggins And The Problem With Scorers

Minnesota Timberwolves swingman Andrew Wiggins was named the NBA’s 2014-15 Rookie of the Year on Thursday. The announcement came as no surprise: It’s an award he’s essentially been a lock to win since at least February.But there’s a big disconnect between what the eye test (plus basic statistics such as points per game) and the analytics say about Wiggins, both in terms of his current production and his future potential. And because of that discrepancy, Wiggins is emblematic of what’s long been one of the most difficult problems to solve in basketball analysis.According to conventional analysis, Wiggins had a standout rookie campaign. Despite being a callow 19-year-old, he averaged nearly 17 points per game for the season, including 19.1 PPG from New Year’s Day onward, and provided some of the most sharable Vines of any player in the league. On top of his scoring output, he’s also regarded by scouts as a player with elite defensive potential because of his length and athleticism. Viewed in those terms, Wiggins’s Rookie of the Year nod could be seen as a launchpad for a Hall of Fame career.The advanced statistics are far less impressive. As others have noted, according to Value Over Replacement Player (VORP) Wiggins had one of the worst seasons by a Rookie of the Year winner since 1973-74, which is as far back as the statistic can be calculated. Also judging by VORP, 60 other rookies provided more value to their teams this season. And even after a high-scoring spike in performance at midseason, Wiggins’s final 2014-15 Statistical Plus-Minus (SPM) of -2.4 was barely better than the -2.9 mark that could have been expected by simply regressing his stats to the mean back in December.ESPN’s single-season Real Plus-Minus (RPM) for Wiggins’s offense was higher than his SPM, suggesting he makes an impact at that end that can’t be fully detected by the box score. But in his supposed strong suit — defense — RPM ranked Wiggins in the 14th percentile of all NBA players in terms of per-possession performance, even after adjusting for the quality of his teammates (or lack thereof) and the opponents he faced. And Synergy Sports judged his capabilities as an individual defender only marginally better, ranking him in the 32nd percentile of defenders according to its video-scouting metrics.So what gives? Why are the eyes so high on Wiggins, but the numbers so down?Part of it is age. If we give a bonus to Wiggins’s SPM according to an aging curve, setting every Rookie of the Year winner on equal footing at age 22,1The average age of all NBA rookies since the 1976-77 season. Wiggins shoots up the list of winners, from No. 40 (out of 41) in rookie wins above replacement (WAR) to No. 27. Kyrie Irving201219- Chuck Person198722- Chris Paul200620-8.513.216.4+3.2 There was also the matter of Wiggins’s awful teammates. According to SPM,2Specifically, a calculation estimating how poor the team’s efficiency differential would be if we removed the player from the roster and gave his minutes to a replacement-level player. Wiggins was saddled with the ninth-worst teammates of any Rookie of the Year winner since the ABA-NBA merger. Teammate Zach LaVine posted the worst WAR of any player in the league, Anthony Bennett ranked 17th-worst, and Adreian Payne was sixth-worst in the league based on his time in Minnesota alone, despite not joining the team until February. Simply put, Wiggins had to carry more of the Timberwolves’ load because he played with a truly terrible supporting cast.But that doesn’t explain all of the disparity between Wiggins’s conventional accolades and his feeble advanced metrics. After all, the quality of a player’s teammates is barely correlated3Since the merger, there’s only a correlation of 0.098 between a player’s “teammate rating” and his own SPM; there’s also a correlation of 0.117 between the year-to-year change in a player’s teammate quality and the change in his (age-adjusted) SPM. with his own performance. A bigger reason might relate to a question APBRmetricians have grappled with for years: How exactly should we deal with high-volume scorers?Former ESPN Director of Production Analytics (and current Sacramento Kings Director of Analytics and Player Personnel) Dean Oliver devoted an entire chapter (titled The Problem With Scorers) in his seminal book “Basketball on Paper” to the issues involved in statistically evaluating players who perform what seems the most essential of on-court acts: putting the ball in the basket. Although he determined that per-possession efficiency was the best measure of a team’s offensive prowess and developed equivalent efficiency metrics for individual players, Oliver also posited that a player’s offensive efficiency was prone to changes based on how much of a scoring workload he took on.That theory, which has largely been borne out by subsequent studies, implies that a player’s efficiency numbers aren’t even close to being all his own — and that, crucially, high scorers such as Wiggins represent the group most centrally affected by such interplay between teammates. Furthermore, raw scoring ability may suggest heightened potential even after controlling for a player’s actual rookie production. If you run a regression attempting to predict a rookie’s remaining career WAR from his first-year statistics, the second-most important predictor (though dwarfed by the effect of his age-adjusted rookie WAR itself) is usage rate, a measure of how frequently a player was called on for scoring attempts within his team’s offense, regardless of their success.The idea that Wiggins’s scoring and athleticism speak volumes about his potential in a way that can’t be captured by his rookie-season value metrics goes a long way toward explaining the gulf between his subjective reputation and the numbers. Only time will tell which is right, but that differential could position Wiggins as his generation’s Allen Iverson or Antoine Walker — players who served as early battlegrounds in the war between analytics and conventional wisdom. Tim Duncan199821-0.412.213.8+1.6 Larry Bird198023+2.612.211.1-1.1 PLAYERYEARAGETEAMMATE QUALITYRAW WARAGE-22 EQUIV. WARDIFF Andrew Wiggins201519-9.0-0.75.1+5.8 Blake Griffin201121-7.510.311.9+1.6 Kevin Durant200819- Derrick Coleman199123- Brandon Roy200722- Mark Jackson198822- Phil Ford197922+ Patrick Ewing198623- Pau Gasol200221- LeBron James200419-5.46.312.4+6.1 Shaquille O’Neal199320-2.910.614.0+3.5 Walter Davis197823+ Allen Iverson199721- Mitch Richmond198923- Adrian Dantley197720- Michael Jordan198521-7.616.918.5+1.6 Emeka Okafor200522- Steve Francis200022- Chris Webber199420-2.09.312.0+2.8 Derrick Rose200920- Grant Hill199522- Ralph Sampson198423- Vince Carter199922- Amar’e Stoudemire200320+ Terry Cummings198321- Mike Miller200120+ Darrell Griffith198122-5.0-2.7-2.70.0 David Robinson199024-2.515.113.2-1.9 Damon Stoudamire199622- Elton Brand200020- Michael Carter-Williams201422- Larry Johnson199222- Damian Lillard201322- Jason Kidd199521- Buck Williams198221- Tyreke Evans201020-

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