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Has Analytics In Sports Gone Too Far?

Moneyball is one of the best sports movies ever made. It dives into how former Athletics general manager Billy Beane (played by Brad Pitt) used “Moneyball” to build a roster that set the American League record for most consecutive wins in 2002.


At the time, Beane’s use of analytics was groundbreaking. However, the point and the purpose of “Moneyball” might have been missed, as Beane said himself nearly 20 years later. The A’s didn’t get out of the first round of the MLB playoffs. The point was probably that small-market teams like Oakland must innovate like Beane did to compete with franchises like the Yankees and Dodgers. Analytics was his way of doing that.


Analytics has now gone way too far in professional sports. It’s prevalent in major sports leagues, most notably the MLB and NFL. There are massive analytics departments, and decision-making—from roster construction to in-game choices—has been largely driven by the numbers for some organizations.


Widely accepted groupthink stemming from analytics has become mainstream. One of the most common arguments from analytics proponents is that “running backs don’t matter.” Recently, Giants running back Saquon Barkley and Raiders running back Josh Jacobs did not receive long-term deals from their teams and will have to play the 2023 season on the franchise tag. This led to running backs banding together to voice their displeasure online.



There’s no question that “analytics” and the franchise tag have allowed NFL teams to easily devalue the running back position. You often hear, “well Super Bowl teams don’t pay running backs a lot,” ignoring the difficulty of winning it all and the fact that one team (typically with an elite quarterback) wins every season.


Another example of how analytics has arguably gone too far is the belief that having a quarterback on a rookie contract is the best shot to win a championship. While having a superb young quarterback at a lower salary can help with cap allocation, just two quarterbacks on their rookie contract since the 2011 collective bargaining agreement implementing the rookie wage scale have won it all: Russell Wilson and Patrick Mahomes.


Part of the issue is a lack of independent thinking, which leads to these types of thoughts spreading and catching on. The bottom line is you need a great team to win a Super Bowl. Players like Barkley and Jacobs can be part of that, even at a higher salary. Additionally, analytics cannot measure the heart and leadership of players like Barkley and Jacobs, but their value is evident if you watch them play.


In baseball, you have this new school of thought that “swinging up at the baseball” being the best path to success as a hitter. Walk around Little League fields and schools across America and you’ll probably see uppercut swings being taught. It’s based in analytics. Listen to all-time greats like Mike Schmidt talk about it, and you’ll find that they think it’s laughable.


As another example, analytics also typically frowns upon the art of base stealing. Non-aggressive baserunning puts less pressure on the pitcher and defense, though, which the numbers arguably cannot capture. It brings me to this meme I came up with from the Quentin Tarantino film Inglourious Basterds, hitting on the risk/reward that comes with aggressiveness on the basepaths:



However, this is not to say that analytics has no value or benefit in sports. Sports science uses analytics to help players stay healthier and at peak performance levels.


But I can’t find a compelling argument that “the numbers” can replace the feel of a coach on the field during a game or of a talented evaluator on player personnel decisions. For scouting specifically, you must put in the work and actually watch and evaluate players—it’s unfathomable that some analytics people believe you can make a proper evaluation without watching film.


I think legendary 49ers head coach Bill Walsh had it right when he discussed analytics in his must-read book Finding the Winning Edge:


When decisions go wrong, information is used to rationalize an explanation (e.g., “I know we lost that one, but all the data indicated we couldn’t miss”).


This book was from before the turn of the millennium, but it’s insane how prescient Walsh was throughout the book—including about analytics before it was close to established in sports. Walsh believed that it should be a tool, but it shouldn’t go too far and become a philosophy.


In my humble opinion, the Hall of Fame coach is exactly right. Analytics in sports should be a tool in the utility belt. It shouldn’t be the entire Batsuit, Batmobile, and Batcave.