Mike Wilbon’s look at place of sports analytics in black sporting discourse is much more interesting than the sneer of derision he usually applies to the topic on PTI. It’s a good reminder that data-driven commentary is one mode of sports discourse, but far from the only one. If statistical writing on sports seems ubiquitous, it is in part because the subset of fans who read obsessively provide the clicks to keep sites who can offer that rather than access reporting. But it is not present in, say, television broadcasts, where the emphasis remains on narrative.
The last third of the column starts to address the way analytics and power are intertwined, but it scratches the surface and you have to work to get there.
The old school/new school framing at the beginning obscures the way this debate is about power (and mirrors discussions occurring in workplaces everywhere). Wilbon’s familiar curmudgeon schtick on analytics is best typified here:
The greater the dependence on the numbers, the more challenged people are to tell (or understand) the narrative without them. Makes you wonder how people ever enjoyed or understood the dominance of baseball king Babe Ruth or boxing champ Joe Louis or Masters Tournament co-founder Bobby Jones. Imagine something as pedestrian as home runs and runs batted in adequately explaining Ruth’s overall impact.
This pining for the good old days leaves aside that home run and RBI totals in ARE analytics. They may be simple by today’s standards; you just have to count stuff, what fun is that? But they are performance measurements. We keep those totals because we think they provide meaningful information about baseball players. The first newspaper sportswriter, Henry Chadwick, invented a statistical language to understand baseball so he and his ilk (PTI word!) could describe it to people back in the 1860s.
Statistics and analytics are one very common way of knowing a sport. There are other ways of course, through narrative for instance. But a story about a guy breaking out of a slump is rooted in a hybrid approach. That data tells you in he was not hitting and the personal interview tells you how he managed it. Wilbon was trying to draw line between traditional stats and modern analytics, but that is not a meaningful distinction.
More importantly, those traditional stats were a regime of knowledge about sports. The statistics invented by Chadwick around the Civil War still persist to this day in baseball (batting average, runs, home runs, RBIs). They structured how we actually knew and made sense of the game. Fans, executives, managers, players and sportswriters measured players’ value through these numbers. The rise of analytics challenged this authority over knowledge of the game. Suddenly the strategies long espoused by managers and writers were challenged and could not stand up to scrutiny. The stats I grew up reading in the in Detroit Free Press sorted hitters by batting average because that was the obvious way to measure the worth of a hitter in the 1980s. In hindsight, how did that ever make sense? Why were we ever so picky about how a batter gets on base? It was just tradition.
To hear Michael Lewis tell it, analytics liberated baseball from the hands of the sport’s lifers who were trapped by groupthink. That’s one way to think about it. Another way is that baseball front offices recalibrated how they valued data in relation to experience. Suddenly, 40 years of experience in the game was not enough to justify a sacrifice bunt in the fifth inning. Needing a regression analysis to justify stealing a base redistributed power in a baseball organization. It determines who gets to be a general manager and who never advances past pitching coach. Sportswriters were part of this group who saw their control over sports knowledge
But this comes back to Wilbon’s best point. This is a gross oversimplification, but the racial politics in baseball were less clear because it was white Ivy League graduates replacing white people with high school educations. Basketball’s racial makeup means the sport’s lifers are more likely to be black. They too are being replaced by Ivy League hotshots building models that I have a hard time understanding. Wilbon is right that the embrace of analytics is a way of keeping people not rooted in a specific way of knowing basketball out of power hierarchies, or preventing them from advancing. And in basketball the racial divides are easier to see.
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