Sports data scientist focused on basketball and baseball.
py_ball. Python API for stats.nba.com with a focus on NBA and WNBA applications
123basketball_data_science. Working through Basketball Data Science
25shot_probability. Building a shot probability model from NBA shot chart data
12location_data. Generating shot, foul, and assist charts
12draft_combine. NBA Draft Combine Analysis
6challenges. Exploratory data analysis of the new NBA challenge rule
5assist_networks. Visualizing team assists as a network of player nodes
4scoreboard. Using Jupyter to build a dashboard displaying a basketball scoreboard
3synergy. NBA Synergy data exploration
3l2m. NBA Last Two Minute Report exploration
3ETM. Basketball Metric Development
2franchise_history. WNBA and NBA franchise history visualization
2nba_lottery. Tool to simulate the NBA lottery as teams are revealed
2team_additions. Visualizing team and player statistics in the context of transactions
2win_probability. Developing NBA and WNBA in-game win probability models
2team_travel. Visualizing and quantifying NBA team travel
2rebounding. Visualizing and quantifying rebounding
2approach. Modeling expected strokes as a function of distance from the hole and lie type
1wnba_elo. WNBA ELO Ratings
1nyc_bb. Visualization of New York City Public Basketball Courts
1nba_official_evaluation. Leveraging Last Two Minute report and Coach's Challenge data to evaluate NBA officials
1bball-analytics. Jupyter Notebook
1nba_lottery_site. Site to host live NBA Draft Lottery Odds
1basketballrelativity.github.io. HTML
1playing_time_viz. Visualizing playing time throughout WNBA and NBA games
1personal. Personal website
1wnba_lottery. Tool to provide updated odds by team for the WNBA lottery as teams are revealed
1defense. Visualizing and quantifying defensive impact
1salaries. Exploratory Analysis of NBA Salary Data
1video. Accessing play-by-play video
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