About MLBAnalytic

I’m an independent analyst who got tired of arguing about baseball with stats I couldn’t verify. MLBAnalytic is where I pull the data myself, build the charts from scratch, and write up what I find. There’s no newsroom and no agenda here — just public data, open code, and a long-standing habit of asking “where did that number come from?”

Every data-driven article on this site ships with the Python script that produced its numbers, so you can re-run it, check it, or adapt it for your own questions. If a statistic appears here, it came from a real data pull on a specific date — not from memory and not from a screenshot.

Methodology & data sources

The analysis here leans on a small set of trustworthy, public sources:

• Baseball Savant (Statcast) — pitch- and batted-ball-level tracking data: exit velocity, barrels, expected stats (xBA/xSLG/xwOBA), pitch types and spray coordinates.
• The MLB Stats API — the same public feed that powers MLB’s scoreboards: standings, season totals back to the 1900s, schedules, and play-by-play win probability.
• Baseball-Reference (via pybaseball) — the historical record, OPS+, and Baseball-Reference WAR.
• Retrosheet and the Lahman database — deep historical play-by-play and season data for long-run questions.

My rules are simple. Historical facts, formulas, and rule changes I’ll state directly. But anything presented as a current or recent-season statistic comes from an actual pull, captioned with its source and retrieval date. When a source is unreachable, I leave a visible note and the working script rather than guess. Charts are computed with Python and matplotlib from the fetched data — never mocked up.

How to read the data notes

Tables and charts carry a caption like “Source: Baseball Savant, retrieved June 2026.” That date matters: leaderboards change. If you want fresher numbers, grab the script named in the article from the /scripts folder and run it again.