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Analytics Didn’t Help The Tampa Bay Rays, But Can It Help The Legal Profession?

Last night, the Los Angeles Dodgers beat the Tampa Bay Rays to win the 2020 World Series. It was the Dodgers’ first title in 32 years. One fateful decision changed the momentum of the game.

For the first six innings, Tampa Bay had a 1-0 lead. This was because their starting pitcher, Cy Young Award-winning Blake Snell was doing very well. He struck out nine and gave up only two hits. His performance was compared to Hall of Famer Sandy Koufax.

But on the sixth inning, right after Snell gave up a base hit, Rays manager Kevin Cash replaced him with Nick Anderson. This decision backfired as Anderson gave up two runs on that inning including one due to a wild pitch. Unfortunately for Tampa Bay, they were unable to recover from this.

I don’t follow baseball so I was confused by Cash’s decision. I didn’t think a pitcher would be substituted out after giving away only two hits. I thought substitutions happened when a player was losing his edge and giving up numerous hits and runs.

I was told that the manager replaced Snell likely because he relied on analytics. There is a massive trove of data on baseball statistics, such as games played, the outcomes, and player attributes. All of this information is analyzed and synthesized to give teams advice and determine who is likely to win a certain game and when a pitcher should be relieved. There is even a term for it: Sabremetrics. I suppose it’s not much different than watching two computer AIs play each other on a baseball video game.

The problem is that analytics isn’t foolproof, as Tampa Bay learned the painful way last night. In fact, if every team used analytics to plan their season, only one team will benefit while the rest will either have to get different players or a more powerful AI that can synthesize the data better.

This made me wonder about how much the legal profession relies on their own analytics when making decisions.

We rely on precedent to predict how a similar case will be decided. We analyze a judge’s past decisions to prepare briefs and oral arguments that will persuade the judge to rule in our favor. We vet a juror based on race, education, social and economic standing, and a host of other factors to see if they will be sympathetic to our client. The opposing counsel’s attorney’s reputation and accomplishments could also play a role on how to proceed with the case.

With developing AI and machine learning technologies, the analysis will be more detailed. They will look at court decisions, law review articles, judges’ speeches, an attorney’s Yelp reviews and any other information they can find on the web.

Another problem is access. The richer law firms will likely be the early adopters of this technology and will use it to their clients’ advantage. While smaller firms with more modest or indigent clients will have to wait until the technology meets their price point. This unfairness is nothing new. The richer can buy more resources because they have the money to do it.

So let’s say a lawyer has a strong case, and he thinks he is likely to win at trial. But what if the “analytics” say that the judge will likely rule against his motions? Or the AI program thinks the jury will likely rule against his client? Of course, no one can say. Just as no one can tell whether Tampa Bay would have won last night if Blake Snell had stayed in the game.

Relying on analytics might not get you the result you want. Whether it is litigation or transactional work, there are a lot of moving parts at play. Some parts we can predict with great accuracy while others are a crapshoot. Judges and jurors are human beings and can change. Attorneys can lose their edge or become better as time passes. Economies and laws can change.

In the future, people and professionals will rely more on analytic data to help guide their decisions. But analytics is still at best an educated guess. In a changing and unpredictable world, it might still be better to rely on your intuition, especially if it has served you well in the past.


Steven Chung is a tax attorney in Los Angeles, California. He helps people with basic tax planning and resolve tax disputes. He is also sympathetic to people with large student loans. He can be reached via email at sachimalbe@excite.com. Or you can connect with him on Twitter (@stevenchung) and connect with him on LinkedIn.