A while back, I got pretty interested in something called “Player Efficiency Rating” (PER). Being a fan of the NBA – and in particular the Lakers – I’m interested in the recent shift across some clubs to a more stats-based approach. It turns out that the teams that use “advanced statistics” to make personnel decisions and to inform their players before each game do significantly better than those that do not. “Advanced Statistics” are things like PER that use an algorithm to bring together multiple individual metrics into a single number. There are plenty of criticisms to this approach, many of which focus on the way the algorithm is built.
Just a couple of weeks ago, I looked at teams that have stats people integrated into the decision process. (Boston, Cleveland, Dallas, Denver, Houston, Oklahoma City, Portland and I may have included Orlando — I’m not certain what they do exactly.) It was seven or eight teams. They had won 60% of their games, and that’s counting Houston, which has only won half their games because they’re missing Yao Ming and Tracy McGrady wasn’t playing.
The teams that don’t have quants won 40-some percent. And it was pretty linear … the more or less they had someone integrated into their decision making, the more or less they were at the extremes of winning and losing. [Emphasis mine]
TrueHoop – The State of Basketball Analysis
I’ll reiterate the main point for emphasis: NBA teams that use a stats-based approach win 60% of their games, while those that don’t win 40%.
But I guess *my* point is not that stats-based approaches are always the way to go, but rather that if you’re going to take a stats-based approach, it’s important to really think hard about how (and why) you’re using data.
Which leads me to a quick dissection of the state of nerdery in basketball today:
That, friends, is the formula for PER. It takes all the valuable individual metrics for a player (which have been recorded since around 1950) and rolls them up into one number that represents the total contribution of a single player per minute of each game. There are plenty of other ways to judge players using advanced metrics, including Adjusted +/- (how the team does when a player is on the floor versus off), Rebound Rate (just what it sounds like) and Wins Added (also what it sounds like).
And while I won’t bore you with an explanation of every portion of the algorithm, you can see that it takes into account good things (points scored and how they’re scored, blocks, steals, rebounds, assists) and bad things (turnovers, shots missed, fouls), and includes the team’s pace-of-play in comparison to the overall league. Each of the “contributions” is weighted to essentially create an index where the “average” player in the NBA has a PER of 15.
When you anecdotally compare players’ performances to their PER numbers, things start to make sense:
Only 14 times has a player posted a season efficiency rating over 30.0. All of them are between 30.23 and 31.84. Michael Jordan leads with four 30+ seasons, with Shaquille O’Neal and Wilt Chamberlain having accomplished three each, and LeBron James, David Robinson, Dwyane Wade and Tracy McGrady having accomplished one each. The 2008-2009 season was unique in that it was the only season in which more than one player (LeBron James and Dwyane Wade, with Chris Paul just missing the cut with a PER of 29.96) posted efficiency ratings of over 30.0.
Wikipedia – PER
I bring this up now because there’s a lot of talk lately of the value of a “fan” on Facebook (or rather, the value of a “liker”), and the analysis seems pretty shallow. Compare PER (judging the value of an NBA player per minute of play) to the formula proposed by Vitrue and Edelman for the value of a “fan”/”liker”:
Don’t get me wrong: there is absolutely value in a fan relationship that can be measured by looking at the free impressions that relationship creates. And while it’s nice to have a low-level algorithm to determine that component of a fan’s “value”, I think we can do a whole heck of a lot better.
To me, judging fan value by how many free impressions they can create seems like judging an NBA player only by their free-throw shooting ability. Or even by how fast they can run end-to-end on a court. Or in a pretty good case by their PER. In all cases, there’s a much bigger picture to take into account.
Take into account this bit from a fascinating article in the Times Magazine from last year, about analyzing the performance of players like Shane Battier, the “No Stats All-Star”:
There are other things Morey has noticed too, but declines to discuss as there is right now in pro basketball real value to new information, and the Rockets feel they have some. What he will say, however, is that the big challenge on any basketball court is to measure the right things. The five players on any basketball team are far more than the sum of their parts; the Rockets devote a lot of energy to untangling subtle interactions among the team’s elements. To get at this they need something that basketball hasn’t historically supplied: meaningful statistics. For most of its history basketball has measured not so much what is important as what is easy to measure — points, rebounds, assists, steals, blocked shots — and these measurements have warped perceptions of the game. (“Someone created the box score,” Morey says, “and he should be shot.”) How many points a player scores, for example, is no true indication of how much he has helped his team. Another example: if you want to know a player’s value as a rebounder, you need to know not whether he got a rebound but the likelihood of the team getting the rebound when a missed shot enters that player’s zone. [Emphasis mine]
Times Magazine – The No-Stats All-Star
I’m not arguing that the creators of the “Fan Value” metric should be shot, but none of us should feel good with an impressions-based valuation of fan relationships. Instead, I’d argue that each business needs to figure out (as basketball nerds already have):
- What constitutes a “win”
- Who/what contributes to those wins
- How those contributions are made
- and Who else competes for those contributions
Only then can you figure out the value of a fan.