NFL Game SimulatorOliver Reimer

Matthew CritesBrian Jones

Determine the winner of a NFL game between two teams.

How?◦ What aspects of a team are most important in a

game’s outcome?◦ How to represent match-up exploitations?

(i.e. a top-tier defensive team vs. a mediocre offensive ball club)

The Problem

Given 2 teams, teamH and teamA based upon the comparison between offensive and

defensive factors, O and H◦ OH , DH 

◦ OA , DA

Each team’s “edge” in the matchup will be computed as

The team with the larger edge value is the predicted winner

The Solution

A

H

H

D

OE

H

A

A

D

OE

Given a set of n team normalized, offensive attributes, P= {0, 1, … n-1}

And a set of n team normalized, defensive attributes Q= {0, 1, … n-1}

And a set of n weights W = {0, 1, … n-1} The offensive factor is calculated

The defensive factor is calculated

The Factors

ii WPn

i

1

0

ii WQn

i

1

0

Statistics were taken as a per game average over the 16 games of the 2014 NFL season.

Offensive statistics were normalized

Defensive statistics were normalized

Normalization

avgleague

statteam

_

_

statteam

avgleague

_

_

Passing Yards per game Rushing Yards per game Points per game First Downs per game Fumbles (lost and recovered) Interceptions

Statistics Considered

What set of weights will give optimal results?

What team attributes are more important in the game outcome?

The nature of these questions support a genetic approach

Weights

Four step process◦ Determine fitness of the members of the

population◦ Generate offspring◦ Mutate◦ Update the population

Genetic

Start with a population of n randomly generated solutions◦ Weights had values ranging from 0 – 1 exclusive

Determine Fitness Generate Offspring from the most fit Mutate Update Population Repeat for m generations

Genetic

Four Solution Fitness categories ◦ Edge differences ascending◦ Edge differences descending

◦ Simulation ascending◦ Simulation descending

The four categories produce vastly different results

Fitness

|| AEEH

Comparison

PPG

FLPG

FDPG

PASS_YPG

INTPG

RUSH_YPG

PAPG

FRPG

FDAPG

PASS_YAPG

INTPG_D

RUSH_YAPG

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

SIMADESASCSIMD

Accuracy in predicting the 2014 NFL Season◦ Edge Difference Ascending

50.4 %◦ Edge Difference Descending

70.7 %◦ Simulation Ascending

70.7 %◦ Simulation Descending

48.8 %

Results

Most Important◦ Forcing Turnovers

Fumbles Interceptions

Least Important◦ Yardage Allowed

Rushing Passing

◦ First Downs Allowed

Results

Hot Streaks Past Match-up Experience Injuries Home-field/Weather advantage

Future Work

Questions?