Machine Learning Magic: Week 7 College Football Predictions
Machine Learning Predictions for College Football: Week 7
My 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 75% in predicting the winner of each game. However, this does not mean that the model is infallible or guarantees a profit. There are always uncertainties and surprises in sports, and you should always do your own research and use your own judgment before placing any bets. Last two weeks we have gone 72-30 for predictions.
SYRACUSE
OHIO-ST
ALABAMA
RUTGERS
KENT-ST
NORTH-TEXAS
GA-SOUTHERN
CINCINNATI
TOLEDO
NAVY
UTAH
OREGON
MARYLAND
TENNESSEE
KANSAS
CENTRAL-MICH
TCU
MIAMI-OH
FLORIDA
WAKE-FOREST
TROY
BUFFALO
SOUTH-FLA
WISCONSIN
OHIO
UNLV
SAN-JOSE-ST
LOUISVILLE
LSU
WASHINGTON-ST
AIR-FORCE
TEXAS-ST
GEORGIA-ST
KANSAS-ST
SOUTHERN-CALIFORNIA
NORTH-CAROLINA
MISSOURI
DUKE
OREGON-ST
UTSA
BOISE-ST
HAWAII
