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Litigation Moneyball: Data Mining Litigators

Updated: Jun 9, 2023

attorney ready to play litigation moneyball

If you’ve read anything by Michael Lewis over the years, it’s impossible not to notice a recurring theme. And it’s this: data—obtained by people dispositionally prepared to wield it—is regularly used to gain serious advantages in highly competitive enterprises. As explored in Lewis’s books, some of those enterprises include:

  • Baseball (Moneyball);

  • High-frequency trading and dark pools (Flash Boys); and

  • Mortgage-backed securities (The Big Short), among others.

There is another enterprise in which data is regularly leveraged to obtain monetary advantages (sometimes huge ones). That enterprise, of course, is litigation.

There exists an interesting body of literature that addresses how litigants leverage “asymmetric access to information” (i.e., salient data to which only one party has access) to achieve better results for their clients.[i] Most often, this asymmetry has to do with temporarily cloistered facts impacting the merits of the case itself. But not always. A second type of asymmetry also exists that has less to do with hidden facts of the case and more to do with the lawyers that litigate them.

Litigators, as a species, are generally eager to tell you about themselves. But looking past the war stories, data can tell you so much more about their efficacy. Data can render clear a whole host of things that ineffective attorneys would prefer remained hidden. What kind of data? Well, for starters, data that helps you assess efficiency. It’s no secret that some bad attorneys pursue their cases without diligence. Still others milk their cases for billable hours (a hungry outside counsel being a dangerous outside counsel). The good news? Hints of these practices show up in the data. And that data can be a boon for you — and a nightmare, fully realized, for inefficient attorneys. You just need to know where to look.

Want to know the average time it takes an attorney or firm to take a product liability case to a dismissal, summary judgment, termination, or trial? Want to examine that data while controlling for variables such as matter types, courts, and judges? Want to compare those statistics to any other firm or attorney you’re considering hiring? For that matter, do you want to see how often a party’s motions on a specific topic succeed or fail? Done, done, and done. Sophisticated tools, such as those offered by Docket Alarm, can unearth a borderline scary amount of data on these topics. And if you want to see what hyper-granular data can do in the hands of someone that knows how to use it, just ask my friend @DamienRiehl over at Fastcase.

Consider: Your company is being pitched by two attorneys. One gets to trial, in product liability cases, in District X, in an average of 841 days; the other: 1,106 days (real data, by the way). Obviously, one of those firms is working those cases for an additional 265 days, on average. Does that mean they’re the worst choice? Nope. Is that nevertheless a useful data point that requires additional digging? Yep.

Data can also be, at first blush, deceiving. In the above case, the firm that gets to trial faster may actually be less efficient. They may have expensive partners doing associate level work. They may be filing motions that data could have shown were doomed. There are lots of good explanations for why it may take firms longer to reach the same goals. But there are lots of bad reasons, too. Data requires interpretation. As Billy Bean of Moneyball fame noted when interpreting data: “We’re blending what we see but we’re not allowing ourselves to be victimized by what we see.”

If you’re interested in mining data to obtain insights, feel free to drop me or someone at Cloud Court a note. Until then: litigate like you mean it.

[i] See, e.g., Cédric Argenton, Xiaoyu Wang, Litigation and Settlement Under Loss Aversion, Tilburg University Jan.30, 2020 (“In a typical tort litigation setting, the plaintiff may indeed have private information about the damages she has suffered while the defendant may have private information about his liability for the accident. Ramseyer and Nakazato (1989), Farber and White (1991), Osborne(1999), Waldfogel (1998) and Sieg (2000) all provide empirical evidence for the existence and the importance of asymmetric information in various litigation environments.”).

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