Michael Ray Richardson and Kobe

Posted on August 21, 2009 by

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In response to the last post, reader Matt Dalton asked for more information on Michael Ray Richardson. 

Here are Richardson’s career numbers (WP48 = Wins Produced per 48 minutes).

1978-79: 2.0 Wins Produced, 0.078 WP48

1979-80: 21.4 Wins Produced, 0.336 WP48

1980-81: 19.7 Wins Produced, 0.298 WP48

1981-82: 14.0 Wins Produced, 0.221 WP48

1982-83: 6.5 Wins Produced, 0.151 WP48

1983-84: 3.2 Wins Produced, 0.121 WP48

1984-85: 14.6 Wins Produced, 0.225 WP48

1985-86: 7.0 Wins Produced, 0.210 WP48

Totals: 88.6 Wins Produced, 0.229 WP48

Richardson was suspended (for taking drugs) by the league in 1986, so his career ended when he was 30 years old.  Prior to that suspension, though, Richardson was one of the better guards in the NBA.  His teammates, though, were generally lousy.  For his career his teammates posted a 0.076 WP48 [average is 0.100].  To put that in perspective, Kobe Bryant’s teammates have posted 0.113 WP48; and in only one season were Bryant’s teammates as bad as the average we see for Richardson.  

The perceptions of a player’s value are influenced by scoring and winning.  Richardson averaged only 14.8 points per game in his career and he generally played for losers.  So people probably would not think he was as effective as Kobe.  But the data – at least the Wins Produced data – suggests otherwise.  

Update: After the 2008-09 season, Kobe’s Wins Produced stood at 149.0.  His WP48 was 0.207.

– DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.

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