• Contact Info

Pruitt, Kristopher

Senior Instructor

Positions

Research Areas research areas

Research

research overview

  • Primary areas of research are mathematical modeling and statistical learning with applications to human performance and sports. Partnering with faculty and students alike to explore problems such as: 1) Pacing and nutrition strategies for long-distance racing; 2) Route selection for traversing highly variable terrain; 3) Kinematic characteristics of human running stride; 4) Spatial analysis of player positioning and scoring in team sports; 5) Live in-play win probabilities for team sports; 6) Key numbers in sports scoring and their relation to sports betting odds; 7) Hedging in sports trading markets; 8) Data visualization and analysis for grand prix car racing; 9) Individual and team strategy for multi-stage bike racing.

keywords

  • sports analytics, human performance

Teaching

courses taught

  • STAT 2600 - Introduction to Data Science
    Primary Instructor - Spring 2023 / Fall 2023 / Spring 2024
    Introduces students to importing, tidying, exploring, visualizing, summarizing, and modeling data and then communicating the results of these analyses to answer relevant questions and make decisions. Students will learn how to program in R using reproducible workflows. During weekly lab sessions students will collaborate with their teammates to pose and answer questions using real-world datasets.
  • STAT 3400 - Applied Regression
    Primary Instructor - Fall 2022 / Spring 2023 / Fall 2023 / Spring 2024
    Introduces methods, theory, and applications of linear statistical models, covering topics such as estimation, residual diagnostics, goodness of fit, transformations, and various strategies for variable selection and model comparison. Examples will be demonstrated using statistical programming language R.
  • STAT 4680 - Statistical Collaboration
    Primary Instructor - Spring 2023 / Fall 2023 / Spring 2024
    Educates and trains students to become effective interdisciplinary collaborators by developing the communication and collaboration skills necessary to apply technical statistics and data science skills to help domain experts answer research questions. Topics include structuring effective meetings and projects; communicating statistics to non-statisticians; using peer feedback, self-reflection and video analysis to improve collaboration skills; creating reproducible statistical workflows; working ethically. Same as STAT 5680.
  • STAT 5680 - Statistical Collaboration
    Primary Instructor - Spring 2023 / Fall 2023 / Spring 2024
    Educates and trains students to become effective interdisciplinary collaborators by developing the communication and collaboration skills necessary to apply technical statistics and data science skills to help domain experts answer research questions. Topics include structuring effective meetings and projects; communicating statistics to non-statisticians; using peer feedback, self-reflection and video analysis to improve collaboration skills; creating reproducible statistical workflows; working ethically. Same as STAT 4680.

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