College Football Week 6 Picks
Machine Learning Predictions for College Football: Week 6
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.
MIDDLE-TENN
NEW-MEXICO-ST
LIBERTY
WESTERN-KY
KANSAS-ST
NEBRASKA
OHIO-ST
OKLAHOMA
WISCONSIN
LSU
TOLEDO
MISSISSIPPI-ST
ARMY
MARSHALL
UTSA
WASHINGTON-ST
ALABAMA
NORTH-CAROLINA
FLORIDA-ST
WAKE-FOREST
OHIO
PURDUE
MIAMI-OH
TEXAS-ST
NORTH-TEXAS
NORTHERN-ILL
EASTERN-MICH
VANDERBILT
MIDDLE-TENN
NEW-MEXICO-ST
LIBERTY
WESTERN-KY
KANSAS-ST
NEBRASKA
UCF
TROY
SOUTH-FLA
RICE
TULSA
COLORADO
GEORGIA
SOUTH-ALA
OLD-DOMINION
LOUISVILLE
OLE-MISS
GEORGIA-TECH
FRESNO-ST
BOISE-ST
TCU
TEXAS-TECH
UTAH-ST
OREGON-ST
