Welcome
103rd issue.
The Open Championship is underway, and the Women's World Cup just started yesterday. A great sports weekend ahead! Short and sweet intro today.
I am interested in sports-related data science opportunities within the betting or DFS space. Know someone I should chat with? I'll buy you a coffee.
Self Promotion
I recently created SP K Prediction, which identifies positive expected value in MLB starting pitcher strikeout bets and automatically updates each morning. Additionally, it creates market odds for which pitcher will have the most strikeouts that day based on 10k simulations. Check it out, I think it's rad.
This Week's Lineup
Has the Tour de France Gotten Easier Over Time?
Analyzes changes in the race over the years. Good stuff!
Predicting Ticket Sale Prices: A Deep Learning Approach.
Explores the use of deep learning algorithms to predict NFL ticket sale prices and identify profitable ticket-flipping opportunities
FIFA Women's World Cup Predictions
FIFA Women’s World Cup predictions for the 2023 finals, provided by Opta.
Analysis of Europe’s Top Women’s Leagues
Using Wyscout data, Hudl analyze's what insights can be gained from benchmarking the top women’s leagues in Europe.
Women's World Cup Player Similarity Scores
Using recent data, they calculated the cosine similarity between players. It measures how similar two things are, like soccer players' playing styles, by calculating the angle between their "skill vectors."
Please Forward
Was this email forwarded to you? Sign up here >>
Unexpected Points Added is curated and maintained by Patrick Hayes.
In August, I am graduating with a Master of Applied Data Science from the University of Michigan, let's connect.
Send me an email with your feedback or question. I respond to every single one.