Machine Learning Magic: Week 9 College Football Predictions
Machine Learning Predictions for College Football: Week 8
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 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 four weeks we have gone 137-71 for predictions.
LIBERTY
NEW-MEXICO-ST
JACKSONVILLE-ST
UTEP
SYRACUSE
GA-SOUTHERN
FLA-ATLANTIC
OKLAHOMA
FLORIDA-ST
PENN-ST
NORTH-CAROLINA
CLEMSON
MARYLAND
MIAMI-FL
MINNESOTA
BOSTON-COLLEGE
KANSAS-ST
MASSACHUSETTS
TEXAS-AM
LOUISVILLE
UCF
PURDUE
ARKANSAS-ST
WESTERN-MICH
FRESNO-ST
MEMPHIS
NEW-MEXICO
TEXAS
GEORGIA
OREGON
NOTRE-DAME
BAYLOR
SMU
APPALACHIAN-ST
UTSA
OHIO
TEXAS-ST
MISSISSIPPI-ST
SOUTHERN-CALIFORNIA
TULANE
SOUTH-ALA
BOISE-ST
COASTAL-CARO
SAN-JOSE-ST
WASHINGTON
TENNESSEE
AIR-FORCE
OHIO-ST
UCLA
OLE-MISS
JAMES-MADISON
WASHINGTON-ST
CINCINNATI
ARIZONA
