Premium Project

Scout Your Athletics Fantasy Team

Analyze athletics data to find new ways to scout and assess jumpers and throwers.

  • 10 tasks
  • 884 participants
  • 1,500 XP

Project Description

If you were scouting out an athletics team, you would need to know more than just how far each person has jumped or thrown once. You want to know who is the most consistent, who fouls the least and who comes through in the clutch. And you will need to decide which aspects are most important to you so you can find the right balance.

In this R project, you will use data frames and the dplyr package to find out who you should put on your team. You will use the six functions of dplyr to show why you should be the next "Moneyball" star manager of an athletics team.

You will use performance data collated from jumps and throws events in the US from 2013-2017.

It is recommended that you have completed Data Manipulation in R with dplyr, Cleaning Data in R, and Introduction to the Tidyverse prior to starting this project.

Project Tasks

  • 1 Athletics needs a new breed of scouts and managers
  • 2 Managers love tidy data
  • 3 Every throw matters
  • 4 Find the clutch performers
  • 5 Pull the pieces together for a new look at the athletes
  • 6 Normalize the data to compare across stats
  • 7 What matters most when building your squad?
  • 8 Get to know your players
  • 9 Make your case to the front office
  • 10 Time to throw down
George Perry
George Perry

Sports Scientist and Entrepreneur

George Perry is a sports scientist and entrepreneur. Whether he is coaching his athletes, managing a team or writing about soccer, he lives to find the balance between heart-pounding passion for the game and data-driven insight. Before wandering into data science George was a Submarine Warfare Officer in the United States Navy, and earned degrees from Boston University and the University of Texas.

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