Live predicted run vs. pass success metrics in the ESPN mobile app. It could be as simple as “ESPN predicts that Mike Leach should run the ball on 3rd and 1 right now on the 40 of the opposition, with 80% conversion probability”. Of course, Mike Leach might have an assistant look at this data, get real contrarian, and have his quarterback heave a touchdown pass into the end zone. Not only would fans feel more informed by this data, but if it was made accessible to coaches real-time, it could make the game an even more intriguing chess match.
And here’s a bonus. Would love for the app to instantly break down a play after its completion. If the app after a play were to literally say, “We know that Mike Leach just passed the ball on 1st and 10 on his own twenty and got eight yards, but we believe that if he’d run a draw play to the right, he would’ve gotten a first down, based on historical tendencies of the opposition in the nickel defensive formation”. One purpose this would serve: It’d make the fan experience even more fluid and fast. Critique the play analysis while the offensive is huddling back up.
Of course, for any of this to happen, college football would have to widely adopt motion capture technology, like we have in the NBA today through SportVU (SportVU is covered in depth in Betaball, a really readable and intriguing book on the Golden State Warriors). But because there are so many more variables associated with motion capturing a college football game vs. an NBA game, it doesn’t seem like analytics companies have a large, profitable incentive to do so.