Last week Charles Barkley was openly critical about so-called sports experts over-relying on “analytics” rather than simply watching and evaluating talent. Barkley called Houston Rockets general manager Daryl Morey “one of those idiots who believe in analytics,” prompting a wider discussion around the use of statistics in sports, and whether stats can be relied upon as heavily (and exclusively) as some organizations in sports use them.
Stats in sports today
Sabermetrics are commonly used in baseball, making it seem that building a baseball team is as simple as constructing a Lego set (see Moneyball for more on this subject). In fact, not only do we have an abundance of established statistics to cull from when analyzing baseball players, but there are seemingly new statistics coming out all the time. The guess here is that Barkley would assert that baseball guys who rely on statistics are idiots, too.
Statistics can be very useful and lend objectivity to analysis, so from that perspective data collection and analysis can be a good thing. Still, Barkley may have a point when he argues that overly relying on statistics can be misleading, and not the best way to evaluate talent. In other words, do statistics accurately tell us information about a player’s motivation, “heart,” or the ways in which he interacts with teammates? The answer to that is no.
Finding a balancing point
Players are human beings and subjected to all the emotions in life that the rest of us experience, including insecurities, frustration, fear, and anger. It is often these mood states that interrupt otherwise fairly reliable and valid statistics, rendering them useless at times. Statistics work very well in some settings, and not as well in others (like when you are measuring a player’s motivation). The key, it seems, is finding the right balancing point by using some statistical analysis, but also making sure to include the “eyeball test” when making comprehensive judgements about players. You may not be a big fan of Charles Barkley, but in this case his argument of over-reliance on statistics may be right on the money.
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