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Saturday, Nov. 30, 2024
The Emory Wheel

A Statistical Analysis of the Overuse of Statistical Analysis in Sports | Callahan’s Corner

Need to know how many wins a player contributes to a team in comparison to an undefined “replacement” player? How about what the average-at-best Chicago Bulls forward Thaddeus Young has in common with NBA legends Michael Jordan, Larry Bird, Magic Johnson and LeBron James? Well, there’s a stat for that, and for just about anything else. But are they reliable?

After the success of Moneyball (the Oakland Athletics’ data-driven approach to decision-making, not the 2011 Oscar-nominated movie), the use of sabermetrics to measure a player’s value exploded. Since about 2002, when Oakland implemented their famous statistical strategy, analytics has taken over the sports world. In most, if not all professional front offices, analytics experts in the field dictate the path a team should take when making transactions or changing the offense. Advanced numbers are everywhere and have changed the way people approach sports.

Numbers have defined a generation of analytically-inclined executives and fans alike. They have also created a generational divide between those who think the three-point line is a distraction from the much safer mid-range shot and those who think that threes and layups are the only shots worth taking. This specific argument is yet to be settled, but we’ll see the consequences of swearing by the calculated value of shot types later.

The rise of sabermetrics in sports has had its benefits and its consequences. Statistics provide an objective analysis of the effectiveness of a player, a certain type of shot or play and can highlight the strengths and shortcomings of a player or a team. The Houston Rockets transformed their offense into one of historic proportions that shoots most of their shots from behind the three-point arc or in the painted area because those two shots are, statistically, the most valuable.

The Rockets are arguably the most data-driven organization in sports, but they haven’t won anything. They last made an NBA Finals appearance in 1995. And they’re not alone. Many other organizations that have adopted radical statistical approaches lack the requisite success to back up their strategies. 

The Philadelphia Eagles under Head Coach Chip Kelly also relied heavily on numbers, but won just one NFC East division title in his three years in Philadelphia. The Athletics, who “Moneyball” was based on, have not made a World Series since then-General Manager Billy Beane instituted his statistical philosophy in 2002. The Atlanta Falcons have player-specific recovery and sleeping programs but have nothing to show for it besides a historic Super Bowl collapse in 2017. 

Analytics are important, but they are not to be used exclusively to make personnel decisions. They provide an objective interpretation of what is happening on the field, court or in the rink. But they lack context. What good is the goals-against average when the calculations don’t consider the quantity or quality of shots a goalie faces in a game? Why avoid the mid-range shot when, in the middle of 27 consecutive three-point misses, you could use any sort of basket to get the offense back on track (talking to you, Houston)? Statistics are just one ingredient for success, but not the whole recipe.  

While all teams use some sort of analytics, it’s the teams riding mostly traditional approaches to their respective sports that are winning championships: the New England Patriots, 2018 Eagles and 2019 Toronto Raptors are recent championship teams who relied on adept player evaluations, timely rest schedules and great team chemistry to win championships in their respective leagues.

These teams understood the importance of analytics, but they didn’t let numbers and graphs make decisions for them.