A decade ago, when baseball GMs started using statistical analysis to evaluate their teams, it revolutionized the game (see 'Moneyball'). Now, the numbers-based approach is coming to basketball. Muthu Alagappan, a 22-year-old Stanford undergrad, was crunching cancer-related numbers for a data analysis firm when he got the idea to turn his attention to hoops. Last summer, at MIT's Sloan Sports Analytics Conference in Boston, Alagappan presented his potentially groundbreaking model for studying the pro game – a software system that takes traditional stats (rebounds, points, blocks, etc.) and maps them spatially, revealing how seemingly disparate players actually have similar skill sets and styles of play. "I found similarities between players that I hadn't thought of before," Alagappan says, "like [Spurs journeyman point guard] Patty Mills next to [Bulls MVP point guard] Derrick Rose. The software tells me that, analytically, they play in a similar fashion." Word trickled to the NBA and now Ayasdi, the firm where Alagappan works, has been recruited by a handful of teams to analyze their rosters. Alagappan has also started breaking down college hoops data, hoping to find even more surprises. Here, for NCAA and NBA basketball fans, are six counterintuitive ways to look at the game.