Tyler Richardett

Tyler Richardett

Data Scientist, ComponentWise Solutions

Tyler Richardett is a data scientist at ComponentWise Solutions, where he oversees the development of deep learning- and computer vision-based solutions for clients at the Department of Homeland Security. On occasion, he contributes to American Soccer Analysis.

He holds an M.S. in Data Analytics Engineering from George Mason University.

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Recent Posts

Using Optical Tracking Data from Second Spectrum to Visualize Long Goal-scoring Build-ups
Just by plotting each frame of these special goal-scoring sequences, it’s enlightening to see how these attacking teams move and exploit space to ultimately unlock the opposing defense.
Aug 26, 2021 Soccer AnalyticsAmerican Soccer AnalysisR
Using Optical Tracking Data from Second Spectrum to Visualize Long Goal-scoring Build-ups
Building a New In-Game Win Probability Model for American Soccer Analysis
More on how we built this model, how we plan to use it, and how deconstructing it can teach us more about the conditions under which goal-scoring events occur.
Jul 19, 2021 Soccer AnalyticsAmerican Soccer AnalysisR
Building a New In-Game Win Probability Model for American Soccer Analysis
Proposing a Decision Support System for Scouting Talent and Weighing Competing Objectives
This decision support system intends to pair professional soccer players’ event-level data with multi-criteria decision analysis methods—resulting in a system which assists clubs with the identification, scouting, and acquisition of world-class talent.
Mar 31, 2019 Soccer Analytics
Proposing a Decision Support System for Scouting Talent and Weighing Competing Objectives
Valuing Defensive Actions Using Offensive Possession Models
Among other examples, we can determine when pressure scenarios are forcing the ball into less dangerous areas, which players are consistently turning the ball over at inopportune moments, and which players are shutting plays down in the most crucial moments.
Mar 6, 2019 Soccer Analytics
Valuing Defensive Actions Using Offensive Possession Models
U.S. Soccer Can't Afford to Continue Ignoring Children from Traditionally Underserved Communities
Without paving the way for children from traditionally underserved populations, our soccer system will never enter the next stage of growth.
Oct 11, 2018 Access in Youth Soccer
U.S. Soccer Can't Afford to Continue Ignoring Children from Traditionally Underserved Communities
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