Predicting Sport ResultsBY HANNES JOHANSSON & JAMES HALL

Our Project Idea

Available Data

Artificial Neural Networks• Inspired by biology • Human brains have

~85,000,000,000 neurons

Neural Net Model

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Input Layer Hidden Layer Output Layer

Gradient Descent

Neural Net Model

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Input Layer Hidden Layer Output Layer

Trained Neural Net

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Input Layer Hidden Layer Output Layer

Programming Environment• Neuroph framework • MySQL database • Java 1.8 • 15 classes across 3 packages

What We’re Predicting

• Parallel neural nets • Number of goals • Outputs are combined

Our Neural Nets

Neural Net Goals??

?

Evaluation

• Number of incorrect goals • Exact predictions • Winner/loser • Threshold

Inconclusive

Team A Team B

Our Results

• Accuracy goes from 55% to 60%

• Inconclusive goes from 25% to 80%

• Last-Game-Difference input

%

0

25

50

75

100

Threshold0.5 1.0 2.0

Max Accuracy Inconclusive

Possible Improvements

• More inputs • More data • Multiple passes • Other learning methods