College football’s bowl season heads into the new year as a revived UCLA team meets ACC challenger Pittsburgh in this year’s Sun Bowl game.
Pittsburgh finished 8–4 in Pat Narduzzi’s eighth season, second in the division behind UNC, averaging 30.8 points per game and finishing the year with four straight games, but the quarterback of Kedon Slobis to the transfer portal this offseason.
UCLA had a nine-win season, but fell short of the Pac-12’s title hopes by coming out of the skid with two losses at the end of the year, nine points behind Arizona and USC. The Bruins ranked him ninth in the nation with 39.6 points per game, and 246.3 rushing yards per game ranked him fourth overall.
What do the experts think about this matchup? Let’s see how the College Football Power Index’s computer prediction model predicts the game.
Sun Bowl: Pittsburgh vs. UCLA Picks, Predictions
UCLA Prediction: The computer favors the Bruins with a 53.9% chance of winning the game outright.
Pittsburgh Forecast: The Panthers could pull off an upset with a 46.1% advantage, according to the latest index projections.
Point Spread: UCLA will enter the game as the 8-point favorite against Pittsburgh, according to SI Sportsbook quotes.
total: 54 | -118 or more | -110 or less
Moneyline: UCLA-333 | Pittsburgh +240
Diffusion of consensus picks: UCLA -8 (69% of bets are on the Bruins)
UCLA ATS Records: 6-6
Pittsburgh ATS Records: 5-7
UCLA Betting Trends: “The Bruins’ game was overhit at the highest rate in college football (9-3), and the game earned the lowest total points of the entire season. Similar to UCLA, it was a meager gain over the spread. I had a 500 record, and I didn’t cover it in my last three games.” — Kyle Wood, Sports Illustrated
Pittsburgh Betting Trends: “The Panthers have covered three times in their current four-game winning streak, and have been overhit in all but one game. It was -3.”-Thurs
Football Power Index (FPI) College football ranking and computer predictive model is a measure of team strength that predicts a team’s future performance.
Rankings and score predictions are based on 20,000 simulations of the team’s season, using a combination of analysis of historical scores, opponent quality, team schedules, and more.
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