Trellis article published with the National Law Review –
On June 27, 2013, Marriott Resorts Hospitality Corporation filed an action to foreclose liens on multiple residents of separate timeshare estates at Cypress Harbour Condominium in Orlando. Six months later, in January, the Hon. Eric J. Netcher of the 9th Judicial Circuit Court of Florida ruled in favor of the lodging company, ordering the clerk of the court to sell the properties at public auction. Then, on January 8, 2014, the properties were individually purchased by Marriott Ownership Resorts for $100.00 each.
This case is entirely unremarkable. There are thousands of others just like it. Still, there is something interesting about the way these timeshare matters have moved through the 9th Judicial Circuit. The attorney assigned to represent the plaintiff in this case, a litigation associate at Holland & Knight, had maintained a long string of unbroken wins before this particular judge, outperforming the average win rate for this type of case in Orange County.
According to Toby Unwin, a co-founder of Premonition, this could only mean one thing—that the most important metric for predicting the outcome of a case is an attorney’s prior win rate, preferably when holding constant the case type and the judge. This is because “every judge has their favorites,” explains Guy Kurlandski, another co-founder of Premonition.
What I like most about this conclusion is the question it leaves lingering in the air. Many have taken this insight to study how law firms can identify the favorites, putting the right attorney before the right judge. But I want to do something different. I want to know how judicial analytics has equipped—not identified—attorneys. That is to say, I want to know how attorneys are using judicial analytics to become the right attorney.
Scaling Judicial Analytics
“If I’m heading to trial, the judge is the person I need to know best,” confides one attorney. “I need to get inside the judge’s head to figure out what will work and what won’t.” The desire to read the mind of a judge is as strong as ever. “It used to be that personal experience and word-of-mouth were the primary vehicles through which you obtained information about the players in a given case,” writes Nicole Black, an attorney based in Rochester. “For local cases, those reference points were often sufficient. But the further removed a case was from your local jurisdiction, the more difficult it was to obtain actionable data points to make litigation decisions.”
This is where the largest law firms have excelled. Those tasked with representing a large number of large corporations have an inherent advantage when it comes to judicial analytics, as they are positioned to directly acquire large quantities of data about the litigation landscape. Consider, for a moment, a large insurance company. Repeatedly faced with the same types of cases over and over again, the outside counsel of this company can curate its own archive of insurance litigation, incorporating information about judges, parties, settlements, and jury verdicts. This firm will know, perhaps better than anyone else, how different types of cases are likely to be resolved in different courtrooms. It can see it all because it is involved in all of it.
Judicial analytics started because attorneys like Kirk Jenkins, former chair of the appellate task force at Sedgwick, took matters into their own hands, literally collating and “hand-coding [their] own databases of thousands of [state trial court] decisions.” Now, at law firms like Orrick, homegrown legal analytics is built into the very fabric of the organization. According to Kate Orr, judicial analytics are automatically fed through the firm’s case management system, providing, at the start of every case, “a snapshot of the judge and her history, the breakdown of the kinds of cases she works on, her propensity to dismiss cases, the time it takes to resolve cases, and typical outcomes.”
Sunshine on Strategy
Let’s return to Orlando, where timeshare estates continue to move in and out of the 9th Judicial Circuit. According to Trellis, the average case length in Orange County is 502 days. Knowing where a judge sits in relation to this average, as well as the number of cases (s)he has on deck, could help an attorney anticipate the likely pace of their case. Netcher, for example, has 2,325 active cases in his docket; twice as many as the average judge in the county. With this number in hand, an attorney can begin drawing conclusions about his availability—about the attention he might be able to devote to each individual case. A heavy caseload may push a judge to make quick decisions, suggesting that an attorney may want to be as concise as possible when writing petitions. Another attorney might look at these same numbers and see something completely different, gleaning insights about the (dis)advantages of filing in Orange County as opposed to Seminole County.
“It’s not so much that it’s telling us how to win the case, but it helps us strategize,” says Martin Korn, present co-founder at Golden Arrow Publishing. An attorney can dig as deep as they want into the data, learning even more about the tendencies of a judge like Netcher. I can see, for example, that Netcher has tended to favor defendants in their motions to dismiss, sustaining a grant rate that is 30 percent higher whenever they are the moving party. As one attorney from Locke Lord explains, this type of information not only helps attorneys predict how a judge may rule on a motion, but it also gives them “a sense of who has leverage during settlement negotiations.”
The Nuances Behind the Numbers
The problem, however, is that quantitative data may not say much at all. “[I]f a lawyer knows that 70 percent of the time a single judge denied motions to dismiss,” begins Wendy Butler Curtis, the chief innovation officer at Orrick, “that percentage does not capture the complexity or difficulty of the case.” It’s often necessary to get behind the numbers, to look at the raw data that informs any particular metric. Here, then, is the second component of judicial analytics, where attorneys systematically perform close textual readings of the individual cases underlying each number.
The transparency into the litigation landscape afforded by legal analytics platforms means attorneys can easily sift through the thousands of rulings issued by individual judges. By doing so, attorneys are gaining invaluable insights into how a judge writes, how a judge thinks—how a judge decides. They are identifying the cases a judge tends to cite and the language (s)he finds persuasive. As Daniel Lewis, a former litigation attorney in California, explains, we can now see the extent to which “certain judges are re-using the same language over and over again, according themselves to patterns, like focusing on the third factor in a four-factor test.” Jeff Dailey, a former partner at Akin Gump, echoes these sentiments, intimating that “the more you can rely on [a judge’s] decisions, whether it’s in your briefing or in framing your arguments, the better off you’re going to be.”
Take, as an example, two separate commercial landlord-tenant cases in Florida, both of which test the force majeure provisions of a commercial lease. On December 18, 2020, Fitness International filed an action against its landlord, Vereit Real Estate, in the 11th Judicial Circuit Court. Shortly after, the tenant moved for summary judgment, arguing that the force majeure provision of its lease negated its obligation to pay rent for the three-month period during which state and local governments ordered the closure of all gyms and health clubs. The Hon. William L. Thomas, the judge assigned to the case, agreed with Fitness International. Adopting a purposive interpretation of the lease, Thomas rejected Vereit Real Estate’s defense, which sought to differentiate the tenant’s ability to pay rent from its ability to maintain operations. That is to say, according to Thomas, the landlord’s defense ignored “the bargain at the heart of the lease: the payment of rent in exchange for the right to operate a health club.”
Meanwhile, in the 12th Judicial Circuit Court, a similar case appeared before the Hon. Charles P. Sniffen. Just like before, Fitness International issued a motion for summary judgment against its landlord, 93 FLRPT. In this case, the tenant referenced the force majeure provision within its lease to seek repayment of the rent it had paid during the closure period. This time, Sniffen ruled in favor of the landlord, highlighting the fact that the tenant’s ability to pay rent was neither impossible nor impracticable; the tenant had, in fact, paid its rent. Lurking beneath this ruling, however, was the very same legal reasoning that Thomas found wanting—the bifurcation of the ability to pay rent from the ability to maintain operations.
Do commercial tenants have to continue paying rent if a pandemic forces them to shut down? It really just depends on whom you ask. That’s what’s special about a qualitative approach to judicial analytics. It lets an attorney know the answers to the legal questions they haven’t yet posed. It also helps them get a feel for the types of arguments that will resonate with different judges, whether that be a narrow interpretation of a contract provision or a purposive approach to the law. Everything changes as soon as an attorney knows why a particular motion failed before a particular judge. It’s the moment an attorney can begin formulating actionable solutions, whether that means building the right evidentiary record or formulating the right legal argument.
Concluding Thoughts
In the United States, our legal system relies on precedents, which assures us that the outcome of any single case will be fairly predictable. The problem is that judicial rulings so often surprise us. And, in a way, this makes sense. State trial court judges aren’t computers. They are people filled with their own beliefs and experiences, all of which shape how they interpret laws, apply facts, and consider arguments. These same judges are also given broad discretionary powers. An attorney can’t simply feed competing arguments into the bench and expect the same outcome.
Who your judge is matters. But, as we have seen, the reason it matters isn’t because every judge has their favorites. By synthesizing millions of unique data points, judicial analytics helps enact a world where favorites matter less and less. It’s a world where litigation becomes less about finding the right attorney for each judge and more about becoming the right attorney. With judicial analytics, the focus is on preparation, on using the power of big data to craft compelling arguments and effective tactics. It’s a world where strategy—not personality—matters most.
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