Each case study retells a piece of research that Pascal Institute has published, and explains what it shows about building a forecast, validating a model, or framing a decision. They are our own work, not client engagements, and every number in them comes from the published articles they link to, including the results that did not favor our models.
Forecasting · Model validation
How we built a 2026 World Series forecast from the Pascal Rating and probable starters, validated it on ten past postseasons, and found that the futures market already knew what it knew.
Decision analysis · Measurement
Five studies of MLB's Automated Ball-Strike challenge: how we framed a two-second decision, measured how often players act on a missed call, and put a price on a challenge.
Decision analysis · Expected value
How we evaluated an NFL fourth-and-one decision before knowing the result, by asking what success was worth and where the preferred choice would change.
If your organization has a forecast to build or test, or a decision to frame, tell us about it. We will reply by email and say plainly whether we are the right fit.
