Machine Learning Magic: Week 10 College Football Predictions
Machine Learning Predictions for College Football: Week 10
The machine learning model is based on a random forest model type that learns from historical data and simulates thousands of possible scenarios for each game. The model then outputs the most likely winner for each game. The model has been tested on past seasons and has achieved an accuracy of about 70% in predicting the winner of each game. Last four weeks we have gone 176-86 for predictions.
NORTHERN-ILL
TOLEDO
BOWLING-GREEN
KENT-ST
TCU
DUKE
SOUTH-ALA
SYRACUSE
COLORADO-ST
CLEMSON
OHIO-ST
KANSAS-ST
OLE-MISS
NEBRASKA
WISCONSIN
SOUTH-CAROLINA
FLORIDA
UTAH
NAVY
GEORGIA-TECH
AIR-FORCE
MEMPHIS
NORTH-TEXAS
ARKANSAS-ST
UAB
FLORIDA-ST
GEORGIA
OKLAHOMA
TULANE
LOUISVILLE
NORTHWESTERN
UCF
JAMES-MADISON
HOUSTON
COASTAL-CARO
MINNESOTA
TULSA
HAWAII
SOUTHERN-MISS
OREGON
LIBERTY
UNLV
KANSAS
WEST-VIRGINIA
UTAH-ST
SOUTHERN-CALIFORNIA
MICHIGAN
KENTUCKY
LSU
SMU
MIAMI-FL
WASHINGTON-ST
WESTERN-KY
OREGON-ST
FRESNO-ST
UCLA
