A set of simple analyses looking at various facets of no-hitters
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Updated
Jan 9, 2023 - Python
A set of simple analyses looking at various facets of no-hitters
Scraping historic MLB data then estimating each team's probability of reaching the 2020 postseason
These data frames were mined from data at baseballsavant.com and were used to conduct analysis for Peter L'Oiseau's 2018 Carleton University Undergraduate Mathematics Honours Project
Predictive Modeling in Baseball: a Logistic Regression analysis for my bachelor's Thesis
Data engineering exercise on baseball data
An inferential test of the predictive ability of fWAR after making an array of changes to the equation
This project focuses on designing, building, and evaluating a model to predict a player's on-base percentage (OBP) based on other performance indicators. We then train a tuned model and evaluate performance.
Sabermetrics materials and research
Web app designed to predict a pitcher's pitch selection in various scenarios. Intended for use with MLB the Show's Diamond Dynasty, but can be used IRL too.
Displays current lineup for the Atlanta Braves including some other basic stats for each player.
A Python program that uses Scrapy to scrape baseball statistics from https://baseballsavant.mlb.com to use to calculate players that should start improving or getting worse.
Website that displays my daily predictions for baseball players, specifically hitters. It shows my top five picks for hitters that I think will do well, and my top five hitters that I think will do poorly.
An API to use Baseball Stats to pick the best fantasy roster
Lahman databases through the years
Modeling of winning percentages as compared to those provided by Vegas
STAT406: Statistical Learning
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