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Predictive model and code used to determine the relationship between variables collected from each game and the number of wins for a given team in 2020.

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mtroian1/Insights-For-NFL-Draft-2021

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NFL-Draft-2021

Description

This project contains a linear regression model, simulations, and code to determine the relationship between variables collected from each NFL game and the number of wins for a given team in 2020. This was created to analyze the 2020 season and determine which areas need improvement as well as provide recommendations for the 2021 draft.

Technologies

R version 4.0.4 (2021-02-15) was used for this project.

Libraries include: RMySQL DBI Magrittr Tidyverse GridironaiR GGally Dplyr

General Process

  • Analyze a lot of NFL data from 1970-2020
  • Try to figure out some relationships between full-season stats (like total yards, total rushing yards, yards per play, etc)
  • Build a linear regression to get the relationships between these variables and total wins
  • Run some simulations for 2020 based on different scenarios that could have played out if those full-season stats were different (like if the Eagles had more receiving yards)

Acknowledgment

Thank you to Andy Troiano for your support with this project and the valuable feedback provided along the way! I am so gratful and appreciative!

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Predictive model and code used to determine the relationship between variables collected from each game and the number of wins for a given team in 2020.

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