Nik Reed, before Ravel Law’s purchase by LexisNexis. (Courtesy photo: Eric Millette)

U.S. District Judge William Alsup has ruled on 864 motions to dismiss in his career on the bench in the Northern District of California. He has granted 52 percent of them, tossed 25 percent and split the baby on 23 percent.

The case he is most likely to cite when deciding on those motions? Cited 425 times, Bell Atl. Corp. v. Twombly is a watershed 2007 U.S. Supreme Court Case that raised the bar a plaintiff must plead in order to proceed.

This kind of data—for every federal judge and for 100 different types of motions—is now available to litigators at the click of a mouse through a launch on Thursday of LexisNexis Context, the result of the legal giant’s purchase of Ravel Law in mid-2017. Context will be available as an added purchase in the Lexis Advance suite.

In addition to judges’ favored citations and motion outcomes, Context tool has sortable data on 380,000 expert witnesses that have appeared in federal court. Want to know for sure if your expert has the goods? Check how many times they’ve had their testimony thrown out, and for what reasons.

“You can very literally take the judge’s own language and insert it into your own motion,” said Nik Reed, co-founder of Ravel Law and now a senior director of product and strategy at LexisNexis. “So you are speaking directly to the judge.”

The launch represents a next step for legal analytics, which have not been used to detail the specific language and cases judges are most likely to cite or the reasons why expert testimony gets tossed.

LexisNexis is not alone in its pursuit of legal analytics.

Companies such as Gavelytics, Premonition and others have focused on analyzing judges’ behavior and lawyers’ success rates in state courts. LexisNexis’ Lex Machina tool, which it acquired in 2017, has analyzed case types and judge’s broader behavior, such as how long they typically take to issue rulings and how likely they are to rule on certain matters.

LexisNexis for the past 1½ years has been integrating Ravel Law’s technology into its Lexis Advance platform. That will lead to other products, Reed said, such as an analysis of how often cases that lawyers cite in their briefs are used in a judge’s opinions. The company also plans to incorporate data from its Shepherd tool to determine how often judges are following or departing from certain case citations.

“It’s only recently that technology has caught up to textual-based documents to be able to do this,” Reed said. “It used to be search and retrieval. Enter a keyword and try and find the best document you can from that keyword search. But now you can go beyond that and say what is the meaning behind these different sentences that judges and attorneys are writing. And you can classify that to create powerful insights.”

Litigators with access to Ravel Law have already been using some of the power of the new Context tool to change their behavior when litigating cases, Reed said. In one instance, he said a New York-based lawyer was told by a California judge that a certain motion the lawyer filed was never granted in California. Using analytics, the lawyer showed the judge that he had approved the motion four times in previous years, leading the judge to “begrudgingly” approve the motion, Reed said.

“When you rationally walk through what happens from people having this technology, you hopefully will start to get judges starting to rule more consistently, and maybe the application of the law gets a better service out of this kind of tool,” Reed said. “We need a lot of people to use it and study it before that can happen, but given the sheer amount of data that attorneys have to wrangle these days, having tools that can directionally help you is super helpful.”

Still, there is a question of how welcoming lawyers will be to incorporate data that contradicts their own personal experiences or beliefs about certain judges.

Rick Merrill, a former Greenberg Traurig litigator who launched Gavelytics in 2015 to give insights into California state court rulings, said there is still some resistance to data among lawyers. But he said success stories have helped the cause.

In one instance, he said a partner at a major law firm asked colleagues about a certain judge’s tendencies in a California state court. The partner’s colleagues responded with a suggestion to use a local rule to request a new judge. But, using Gavelytics, the lawyer found that the judge was statistically more likely than most to agree to a motion to compel arbitration. The lawyer shared that data with opposing counsel, and both sides agreed to arbitration without ever filing the motion, Merrill said.

“Fast-forward a couple of years, and it will be absolutely unthinkable to not study your judge or to not study the lawyer you’re going to hire in a statistical fashion,” Merrill said. “People will look back and laugh and say, ‘Can you believe we used to not do this stuff?’ There is so much change coming in litigation.”