the (data) science of sports
Hello world! Introducing the spread.
Building a win probability model, part 3: What's a good model?
Building a win probability model, part 2
Probabilities, models, and reality
Building a win probability model part 1
Football analytics on Twitter
Win probability, uncertainty, and overfitting
New code up on Github
Building a win probability model part 4: Feature engineering and model evaluation
Full model vs. model moel
Selecting features vs. selecting samples: Making smart decisions
Guest post: How’d Those Football Forecasts Turn Out?
Forecasting QB performance using multilevel regression
Reproducible research and sports
Learning about football fandom using social media
Following up on usability and prediction: Downs don't matter?
Thinking about statistical decision-making vs. prediction
How consistent are these ratings?
Points are great, but what about win percentage? (Ranking, part 2)
Ranking algorithms and the NFL (Part 1 of a series)
Massey Least Squares Simple Ratings
Power ratings (Ranking, part 3)
Crowdsourced Team Strength Rankings and Ratings
Elo ratings (part 4)
Want to work in sports?
The sorry state of football analytics
How to ask for (and receive) help from strangers on the internet
Why is it so hard to know if changing coaches has any effect?
Blueprint for an Analytical NFL Franchise, version 0.1
Situational thinking in football - How can data help?
Using k-means clustering to find similar players
Using Continuous-Time Markov Chains to Rank College Football Teams
Counterintuitive findings are not (necessarily) better findings
Building more accurate predictive models with cross-validation
Expected Points Part 1: Building a Model and Estimating Uncertainty
Expected Points Part 2: Why Does Uncertainty Matter?
A new season, a new (lean) design
Win probability plots -- useful tool?
What we talk about when we talk about win probability