[rayiner]

As they acknowledge, it is essential to account for case difficulty in comparing success rates. Having been on both sides of the "v." I can say it is easier on the defense side (at least on the civil side). Defense counsel representing Big Cos. will have a better record not only because those companies are often the target of weaker lawsuits, but because various rules intended to filter out those weaker lawsuits stack the deck against plaintiffs. Thus, there are fantastic lawyers working at Sierra Club or NRDC, but they're not going to have the same record of wins as similarly-good lawyers at a big New York firm.

According to the article, their analysis does account for that. They allegedly "calculate the probability of a successful outcome for the applicant" using machine learning. But there is no description of how they do that. If I had an algorithm that produced halfway decent results in an automated fashion, I wouldn't use it to get into the legal technology market. I'd set myself up as a litigation funder and make boatloads of money with accurate valuations of potential investments.

[jamesk_au]

> If I had an algorithm that produced halfway decent results in an automated fashion, I wouldn't use it to get into the legal technology market. I'd set myself up as a litigation funder and make boatloads of money with accurate valuations of potential investments.

Legalist is a recent YC startup aiming to do exactly that:

http://www.newyorker.com/business/currency/what-litigation-f...

[andrewfong]

If I were interested in litigation funding, I wouldn't evaluate the ability of law firms to litigate but rather the ability of lawyers to accurate predict the outcome of cases (regardless of whether they're actually representing the client) -- e.g. associates at law firms frequently write memos to assess the probability of success before a case makes it way to trial. Seems like there's value in actually correlating memos with actual outcomes.

[rayiner]

The article says they have a machine-learning algorithm that can "calculate the probability of a successful outcome" of a case. Then they calculate firms' ability to improve (or not) that outcome. But if I had such an algorithm I'd just use it directly to decide what cases to fund.

My understanding from talking to litigation funders is that lawyers are terrible at valuing cases. There is money to be made for anyone that can use technology to improve those predictions.

[gohrt]

> Thus, there are fantastic lawyers working at Sierra Club or NRDC, but they're not going to have the same record of wins as similarly-good lawyers at a big New York firm.

Not a problem for the analysis of law firms. Sierra Club is a less effective law firm than the big New York firm.

[x1798DE]

> Not a problem for the analysis of law firms. Sierra Club is a less effective law firm than the big New York firm.

Why is this not a problem? The parent comment was saying that the Sierra Club takes harder cases and is often the plaintiff, not the defendant, so they may be more effective as a law firm but have worse numbers because the win/loss numbers don't mean the same things in different contexts.

[harryh]

It's also worth nothing that the Sierra Club isn't a law firm at all. It's an environmental organization that, among many other things, sometimes uses the legal system to advance its goals.