Now Adobe wants to give you a leg up.

For the second year in a row, the company is opening part of its data analytics to anyone who wants to explore it. Using information gathered by sports data company Sportsradar, Adobe has compiled statistics from 56,000 college basketball games so that people can dig into pretty much any detail imaginable while putting together their brackets.

Want to compare how teams match up in three-point shots in the third quarter? It’s in there. Match offensive vs. defensive efficiencies? Sure thing. Check how the teams have done in divisional games vs. opponents in other divisions? Not a problem.

“We’re trying to help people understand that data is not scary and analysis of data isn’t scary,” says Jeff Allen, senior director of product marketing for Adobe Analytics, the division that is making the so-called Hack the Bracket technology available. “You don’t have to have a PhD to get real value out of data. … We wanted to turn people loose in the tool and see what they could figure out.”

Last year, about 1,500 people used Adobe’s tools to help create their brackets. This year, the number will likely be significantly higher, partly due to a more aggressive marketing strategy, but also because the system performed well last year.

The bracket Adobe created, based on probabilities calculated by the Adobe Analytics system, finished among the top 2% nationwide and accurately predicted the NCAA Tournament’s winner. This year, the company is hoping for an even better result, as there’s a lot more information for the system to crunch.

Last year, Hack the Bracket had 50,000 rows of data. This year, there are 3.5 million rows.

That said, warns Allen, no system is perfect, so wager appropriately.

“Part of this whole game is nobody has any success in predicting the tournament perfectly,” he says. “Being in the top 2% means you’re part of 1.8 million people, so you’re not winning Warren Buffett money.”

Casual visitors to the Hack the Bracket site can get a quick look and plainspoken odds of a win for one team over another (i.e. “Purdue will defeat Virginia with 61.9% probability”). Users are also be able to see how Adobe Analytics has configured its bracket in case they just want to copy those picks and cross their fingers.

But fanatical March Madness followers who want to dive into the most obscure details and crunch their own numbers will find a treasure trove of data on the teams, such as the breakdown of freshman players vs. juniors and seniors to determine on-court experience of players to how efficient certain lineups are against other opponents. There’s even a chart plotting where each team shot from on the court throughout the season.

(That last data point is “kind of ‘gee whiz’ data that doesn’t really help in picking a bracket, to be honest,” admits Allen.)

Even if you’re not playing a bracket, Adobe Analytics may still have a tool of interest for you. One of the new features this year is the “watchability score,” a calculation of whether a game is likely to be worth watching.

To do this, it looks at what each team’s most exciting games of the season were (Duke’s, for instance, was the 80-78 victory over Florida State on Jan. 12, which ended with a dramatic three-pointer from Cam Reddish), extrapolates what made them so electrifying, and predicts if the NCAA Tournament match will have those same qualities.

“It’s really just showing what you can do if you combine a few data points,” says Allen.

Of course, some people might complain that having a cloud-based system crunch a season’s worth (or decades’ worth) of data may give someone an unfair advantage in their office pool. Allen acknowledges that might be true, but also notes that since Adobe’s system is open to anyone, it’s really more a matter of taking advantage of tools available to you.

“If everyone can cheat,” he says, “then it’s not cheating.”