Alabama vs. Indiana prediction by ESPN football computer sees surprising result

One of the great blue bloods face off against an insurgent contender in the College Football Playoff, as Alabama and Indiana meet in the Rose Bowl quarterfinal round this week.

Alabama was down by 17 on the road against Oklahoma in the first round game, but stormed back in a comeback for the ages that cemented the Crimson Tide as a national championship contender.

Likewise are the Hoosiers, a historic loser in football that has catapulted into legendary status over the last two years under head coach Curt Cignetti.

Indiana is 13-0, the Big Ten champion outright for the first time since 1945, in the playoff a second-straight year, and boasts the Heisman Trophy winner in quarterback Fernando Mendoza.

Looking ahead to this week’s matchup, let’s check out the latest college football predictions from the Football Power Index computer prediction model.

The model simulates every NCAA college football game 20,000 times and uses key analytics from both teams and picks winners based on a projected scoring margin per game.

Alabama vs. Indiana prediction

In terms of an outright victory, the models are clearly siding with the Big Ten side in this matchup.

Indiana emerged as the projected winner in the overwhelming majority 71.4 percent of the computer simulations of the game.

That leaves Alabama as the presumptive winner in the remaining 28.6 percent of sims.

How does that translate into an expected margin of victory in the game?

Indiana is projected to be 5.9 points better than Alabama on the same field in both teams' current composition, according to the model's latest forecast.

If so, that would not be enough for the Hoosiers to cover the spread, as Indiana is a 7 point favorite against Alabama, according to the latest game lines posted to FanDuel Sportsbook.

College Football Power Index

Football Power Index (FPI) college football rankings and computer prediction model are a measure of team strength that predicts a team’s future performance.

Rankings and scores predictions are based on 20,000 simulations of a team’s season and games, using a combination of key analytics, including scores to date, quality of opponents, team talent, recruiting, and a team’s schedule.

Teams are ranked not in order of talent like in other rankings, but by a projected point margin per game against an average team on a neutral field.

How good is the prediction model?

How accurate was the College Football Power Index computer prediction model last Saturday?

Projecting the games this season, the Power Index models correctly predicted 74 percent of all games and hit 48.1 percent against the spread.

Predicting a total of 799 college football games a year ago, the Power Index computers were correct for 70.964 percent of their final picks, ranking eighth nationally out of 55 other football models.

Over the last decade, the Football Power Index has proven correct on 75 percent of FBS college football game predictions, including in 73 percent of matchups when it favored a team with at least 70 percent likelihood to win.

Game odds refresh periodically and are subject to change.

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