The No. 10 Alabama Crimson Tide and the South Florida Bulls meet in a non-conference tilt on Saturday. Alabama won the only previous matchup between the programs in 2003, and Raymond James Stadium will host the game in Tampa. Alabama is 1-1 this season after a 34-24 loss to Texas a week ago, and the Crimson Tide were 11-2 in 2022. USF is also 1-1 to begin the 2023 season under new head coach Alex Golesh, with a comfortable win over Florida A&M last week. Alabama will reportedly turn to Notre Dame transfer Tyler Buchner at quarterback after Jalen Milroe started the first two games of the season.

SportsLine consensus lists the Crimson Tide as 34-point favorites for this 3:30 p.m. ET kickoff. The total number of points Vegas thinks will be scored, or the over/under, is 61 in the latest Alabama vs. South Florida odds. Before making any USF vs. Alabama picks, you need to see the college football predictions and betting advice from SportsLine’s proven computer model.

The SportsLine Projection Model simulates every FBS college football game 10,000 times. Since its inception, the proprietary computer model has generated a stunning profit of almost $2,500 for $100 players on its top-rated college football picks against the spread. Anyone who has followed the model has seen huge returns.

Now, the model has set its sights on Alabama vs. USF and just revealed its picks and predictions. You can visit SportsLine now to see the model’s CFB picks. Here are several college football odds and trends for USF vs. Alabama:

Alabama vs. South Florida spread: Alabama -34Alabama vs. South Florida over/under: 61 pointsAlabama vs. South Florida money line: Alabama -10000, USF +2500Alabama: The Crimson Tide are 7-7-1 against the spread since the start of 2022USF:…


Source link : https://www.cbssports.com/college-football/news/alabama-vs-usf-odds-spread-time-line-2023-picks-week-3-college-football-predictions-from-proven-model/

Author : CBS Sports Staff

Publish date : 2023-09-16 17:27:08

Copyright for syndicated content belongs to the linked Source.