2018 ESSI Summer Camp

The University of Michigan Exercise & Sport Science Initiative (ESSI) will host a data science summer camp for high-school students who are interested in sport analytics.

During this camp, which will be held June 25-29 (9-4 p.m.) in Ann Arbor, high-school students will learn the basic mathematics behind data science, with a sports analytics emphasis. They will experience real-life applications pertaining to U-M Athletics. High-school students with an interest in mathematics and sports are encouraged to apply.

In competitive athletics and elite performance, “analytics” aim to achieve wins and peak performance. For individuals across the lifespan, it provides a personalized strategy for achieving exercise, fitness and health/wellness goals. The challenge for individuals is to translate a myriad of data from multiple types of devices or sources on an individual’s training, nutrition, biomechanics, physiology and psychology into useable approaches to prevent injury and achieve fitness or performance goals.

For teams, an additional challenge is to analyze each individual’s actions in relation to those of everyone else on the team, and to analyze the team’s action as whole. With the masses of data, there is a critical need for “analytics” to separate correlation from causality in the design of algorithms to predict individual and team performance successes.

Tentative Topics and Activities

    • Data science overview and classroom activities
    • Python programming introduction
    • Life as an undergraduate student and extracurricular opportunities
    • Introduction to Catapult Sport Technology
    • Sports predictions and fantasy sports
    • Football stadium tour
    • Correlation vs. causation discussion
    • Augmented reality/virtual reality in sports
    • Stadium design — where the future is headed
    • Detroit Tigers and data analytics
    • Sports Performance Center Tour
    • Michigan Performance Research Laboratory tour and data collection activity
    • Discussion of R programming