The MCP Sessions Vol. 1: Sports Analytics

Natural Language Prompting

The analyst simply describes what they want to analyze in plain English, and Claude automatically:

1. Lists tables in both databases
2. Identifies 6 new games added
3. Calculates Super Bowl odds changes
4. Attributes probability shifts to specific game outcomes

Key Findings

• Seahawks dropped from 27% → 25% Super Bowl odds (bracket got harder as favorites won)
• Texans gained odds after beating the Steelers
• When a team loses, their Super Bowl odds "go back to the pool" for redistribution

SQL Self-Correction

When Claude writes incorrect SQL and gets an error, it automatically checks the schema, identifies the issue, and rewrites the query correctly.

Finding Correlations to Earnings

Asking "Which stat categories correlate most to money list rankings?" reveals that Shots Gained Tee-to-Green vastly outweighs Shots Gained Putting for predicting earnings.

Identifying Dark Horse Players

Asking "Who played well statistically in 2025 but underperformed on money list?" surfaces players like Pearson Cudi and Pureborn Olison:

• Ranked 124th and 107th in earnings
• But ranked 28th and 20th in Shots Gained
• Watch list candidates for breakout seasons

Validating Historic Dominance

Comparing Scheffler's 2025 to the best seasons from 2017-2022 shows his season was statistically better than Rory's 2019 and Morikawa's 2021. Even accounting for the weaker field post-LIV, his gap to #2 was unprecedented.