KICKIN’ BACK Predictive Analytics and Fantasy Football Kicking GEORGE GREEN DSS680: PREDICTIVE ANALYTICS

INTRODUCTION Recent popularity of fantasy football Use of kickers in real life Fantasy scoring Only thirty-two kickers, usually ten to sixteen team fantasy leagues Not a position considered important enough to risk using a draft pick

ASSUMPTIONS Kickers don’t tend to move around the league a lot The lone exception being if they become inconsistent, they can be replaced relatively easily and very cheaply Another play after a TD not involving the kicker was ignored. It has low usage and is usually only successful half the time Missed extra point attempts, worth 1 in both real life and fantasy scoring, were not considered due to the extreme rarity.

Consistent|Unemployed -180 points total FGs -High 21 points -Low 2 points AVG -Tied for most points with consensus #1 preseason kicker ‘11 – 120 points ‘12 – 106 ‘13 – 116 points ‘14 – Out of the league. Also missed an extra point attempt. Will never be forgiven for it.

Variables Used Target Variable: Fantasy Points per Game Points Per Game Defensive Points Per Game Yards Per Game Plays Per Game Field Goal % Dome (Binary)

Cleaning the Data Rows Data for entirety of game in one row for both teams Had to combine into Offensive Yards Copy and Paste after Splitting Creation of fantasy point statistic

Stat Explore Input Correlation FG_ PPG YPDS PlaysPG DPG

Variable Selection

Dome Rejected! Kind of surprising!

Model Comparison Model Model Node Model Description VASE TASE Y AutoNeural AutoNeural Boost Gradient Boosting Neural Neural Network Ensmbl Ensemble Neural2 NeuralVar Reg Regression Reg2 Stepwise Reg3 StepwiseVar Tree Decision Tree

Importance of Variables Variable Importance Obs NAMELABEL NRULES IMPORTANCE VIMPORTANCE RATIO H 1 FG_ PPG YPDS PlaysPG DPG

Future Research Other data in the set such as wind speed and direction Other positions The significance of the insignificance of the dome

Questions? No? Awesome, next victim!