From War Stories to Judge Analytics
When we were in law school, we were always taught one piece of timeless advice: know your audience. It was sage advice then, and it proved even more valuable once I started practicing. Before a hearing on a motion, the first question was always the same: Who is the judge? We wanted to know if they preferred short, direct argument or a deep dive into precedent. Whether they were sticklers for procedure or more concerned with substance. We wanted to know their temperament, their tendencies, and their quirks. But back then, there were no platforms or dashboards to give us this information. Instead, we did what lawyers have always done. We picked up the phone and called our friends, or we sent out a firm-wide email to get the “low down.” That was our version of judge analytics.
We live in a different world now. The launch of NetDocuments’ new Judge Analytics App is another sign of how quickly things are changing. Instead of relying on stories and war tales, firms can now feed thousands of judicial orders into an AI-powered system that classifies outcomes, motion types, and reasoning patterns. And out comes a structured profile of how a judge tends to rule. The shift reflects a broader transformation in the legal profession, the move from anecdote to analytics.
I have always been a bit skeptical about judge analytics, especially in the state courts. Federal judges may write detailed orders and opinions in every case that are easily captured and indexed. But state court judges make countless decisions that never appear in a searchable database. Many rulings live only in a minute entry, a scanned PDF, or the collective memory of the local bar. That is why, for years, I assumed that robust analytics in the state system was still a long way off.
But the ground is shifting beneath us. E-filing systems, digital records, and the sheer scale of data being collected are changing the game. What used to be hidden in dusty court files is now stored, searchable, and analyzable at scale. Companies like NetDocuments are betting that with enough volume, they can turn this data into insight, and they may be right. For practitioners, this raises fascinating questions. How reliable is the data set? Does a judge’s record on certain motions really predict future rulings? Will knowing a judge’s analytics profile make us better advocates, or simply overconfident in our assumptions?
In the end, analytics will never replace the human element. Judges are people, not algorithms. They can surprise you. They can change their minds. They can be persuaded by arguments well outside their usual pattern. And while tools like this may offer lawyers a sharper starting point, real preparation still comes from knowing the case, mastering the law, and understanding the arguments that matter. It will be interesting to see where this goes.
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