A Simple Linear Regression Analysis of Fantasy Football Kickers

Today I am testing the adage that kickers score more fantasy points when their teams score more points. Some people tend to think the opposite could be true since worse football teams kick more field goals and field goals make up a majority of a kicker’s fantasy points. I decided to test these theories out myself by doing a simple linear regression analysis in excel using data from the 2019 football season.

For the 2019 fantasy football season, a kicker’s team scoring more points was statistically significant in predicting the amount of points a kicker would score.
Regression Statistics
Multiple R0.46930652
R Square0.22024861
Adjusted R Square0.19425689
Standard Error21.2289205
Observations32
 CoefficientsStandard Errort StatP-value
Intercept57.757135120.96918232.7543818460.00989409
Team Points0.164535250.0565222982.9109794070.006733778

As we can see, there is a positive correlation between the amount of points a team scores and the amount of fantasy points that team’s kicker scores. The small p-value (of below .05) tells us that this information is statistically significant and can help us accurately predict how many points a kicker will score. R Squared measures how closely the data is to the fitted regression line. Our R Squared is a bit lower than I had hoped for, but this information alone can’t disqualify this as a good model. If you would like me to test other variables, feel free to reach out to me on social media, and I will investigate for you!

I use vegas lines to help me in my analysis of picking my kicker in both season long and daily fantasy sports. I had great success on my Twitter account predicting kicker streamers last year in the few weeks I posted content. Feel free to check me out @SportsConfidant. A lot of my content will be posted to my Instagram this upcoming season.

-Cody, Founder of Sports Confidant

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Published by Sports Confidant

Sports Analytics and Fantasy Sports Enthusiast

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