Utah vs. UCLA odds, spread, lines: Week 6 college football picks, predictions by computer model
A battle between ranked teams is set for the Rose Bowl as Utah and UCLA meet up for a conference battle in the surprisingly competitive Pac-12 in college football's Week 6 action on Saturday.
Utah checks in at 4-1 winning four straight since the opening loss at Florida, while UCLA is perfect through five and on an 8-game win streak overall behind an offense good for over 506 yards per game.
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What do the experts think of the matchup? Let's see how the College Football Power Index computer prediction model projects the game.
Utah vs. UCLA odds, spread, predictions
The index is going with the visitors this week, as Utah has a 68.9 percent chance to defeat UCLA on the road on Saturday.
That leaves the streaking Bruins the 31.1 percent shot to take down the Utes and stay undefeated on the year.
The oddsmakers take a slightly different view as Utah comes in the slight 4 point favorites, according to the line at SI Sportsbook, which set the over/under mark at 64 points.
Related: College football point spreads, betting lines for Week 6
Utah comes in at No. 7 on the index's 131 college football rankings, a jump of 3 spots after last week's defeat of Oregon State.
The computer projects the Utes will win 10.0 games this season and will be 17.8 points better on average than the teams on their schedule going forward. Utah has the 12.3 percent chance to make the College Football Playoff, according to the predictions.
UCLA owns the No. 31 position on the index rankings, an improvement of 7 spots after its win over ranked Washington a week ago.
The computer estimates UCLA will be 8.1 points better than the teams on its schedule the rest of the way and will win 9.0 games overall.
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, using a combination of analytics, including scores to date, quality of opponents, and a team’s schedule.
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