Hello, I am Parker Booth! I have an analytical background in Quantitative Analysis, Business Analytics, and Econometrics. Currently, I am studying in the Master of Statistics program at the University of Utah, with plans to graduate in the Spring of 2025. I am passionate about using my acquired data analysis skills in the sports industry to help athletes reach their highest potential.
Throughout my studies, I have honed my analytical skills using economic data through various projects with federal economic data. My primary tools for these projects were R programming and Stata.
I also have significant experience in a sports setting as a Sports Science Intern in the Applied Health & Performance Science department at the University of Utah. This opportunity has given me experience with data analysis in a sports setting using R programming and Power BI to analyze athlete data to improve performance.
This repository showcases my data analysis skills and relevant Data Analysis / Sports Science projects.
Duration: 4 months
Program: R
Description: This project focused on finding the statistics and movements essential to winning volleyball games. The data used was two seasons of historical catapult data and matching game data from those two seasons. By collecting and analyzing this data, the goal was to provide answers to the questions about what movements within a game and practice drove wins for the volleyball team.
Two types of Bayesian models were run in this analysis using STAN: General Linear Regression Models and Logistic Models. These models were run using the stan package in R, allowing for a deep Bayesian analysis of how movements influenced match outcomes and statistics. This project deepened my experience with advanced statistical modeling and reinforced the value of data analysis in optimizing athlete performance.
Duration: 3 months
Program: R
Description: This project aimed to build a consistent API that runs every five minutes to automatically update ForceDeck data files utilized by an entire athletics department. The API was implemented in R-Studio and was designed to check for new data and then update the sports-specific data frames to keep all data current.
I worked with the Vald API documentation and resource files. A substantial portion of time was spent on researching how to code an API and how to validate API credentials within R. The other portion of time was spent formatting and specifying the incoming data so the formatting was consistent with the existing data formats.
Duration: 7 months
Program: R
Description: This project aimed to explore the relationship between ForceDecks data and injury report data to identify connections or correlations that could help predict or flag injuries. This project was completed over two semesters with a small break between the two periods.
The first stage focused on exploratory and descriptive statistics, mainly utilizing z-score and data summarization techniques. The project's second stage continued this exploratory analysis and focused on sports with higher observation counts to slim down the data set and ensure robust results. Statistical methods such as a Cox proportional hazards model were introduced to look for predictive results.
Multiple angles of analysis were attempted in both stages and while results were not fully conclusive, information that was valuable to the department was still gained.
- Poster Presentation
- 1st Stage Presentation
- 1st Stage Exploratory Code
- 1st Stage Analysis Code
- 2nd Stage Presentation
- 2nd Stage Analysis Code
Duration: 2 months
Program: Power BI
Description: This project aimed to provide a printable dashboard of pitching statistics for coaches to use easily. This dashboard was my first experience using Power BI in a professional setting.
The dashboard's capabilities allow coaches to easily select different pitchers and specific game dates to review individual performance metrics. The second tab of the dashboard has a slider that allows for the ability to specify a time frame for summarizing pitching statistics. Coaches can print this dashboard to show players at practice about their performance in the previous games or their overall season-long performances.
Duration: 3 months
Program: R
Description: The project investigated the differences between the Track and Cross Country (XC) teams, who do not train together but will compete in similar or even the same events. This analysis focused on ForceDeck data and race times to see which metrics predicted performance for each team's best runners and how those differed.
To answer this question, I implemented a hierarchical statistical model to better understand team differences. The project included exploratory analysis, distance comparisons, and team comparisons to uncover key insights into performance metrics.
Duration: 1 month
Program: R
Description: This project aimed to provide an end-of-season analysis of the basketball team. This analysis used Strive in-season data. The main goals of this project were to provide meaningful visualizations that could be aggregated and report on season-long trends. Trends were analyzed by position and individually by player. This project showcases my visualization skills using the ggplot2 package in R.
Duration: 1 week
Program: R
Description: This project was an impromptu question from the Head Coach of the football team. The main question was how much athletes in the football program have grown over the years. This included growth in height, wingspan, and hand size. This project was a quick look at a small data set showcasing my dplyr manipulation skills and an understanding of R programming. A quick turnaround gave the coach an insightful answer to his question.
University of Utah: Master of Science - MS, Statistics, Econometrics Specialization Jan 2024 - Dec 2025
University of Utah: Bachelor's degree, Quantitative Analysis of Markets & Organizations, Finance Emphasis Aug 2021 - Dec 2023
- LinkedIn: @ParkerBooth
- Email: [email protected]
- Phone: (435) 776-6640