LA Angels Tuesday News Crash

Subject: Broken Defensive Metrics (OAA, DRS, dWAR) — Anyone want to see the real clubhouse numbers?

I’ve been talking with some high-level baseball minds and front-office folks recently, and the consensus is clear: public defensive data is completely failing the eye test.
Every major metric out there has a massive structural blind spot:

• OAA ignores positioning entirely, meaning it actively punishes a player for a bench coach’s terrible shift card.

• DRS punishes elite pre-pitch execution, handing out massive spikes to players who make diving catches simply because they were caught out of position.

• Double-Play Pivot IQ is completely ignored. A middle infielder can lazily take the “easy out” at first base when a double play was highly viable, and public metrics don’t blink. They actively reward passivity.

• dWAR is a complete disaster. It’s a system of lazy positional welfare and arbitrary taxes. Keith Hernandez has a fantastic 60.4 overall career WAR, but his traditional career dWAR is a measly 1.3. The old math claims 17 years of absolute defensive mastery were worth just 0.07 wins per year because of a flat positional tax of -1.25 per year. It completely fails to reward how dominant a player he actually was at his position.

To bridge this gap, I’ve been building a new dual-stat clubhouse framework that strips out positioning luck, applies strategic immunity for bad shifts, and actively grades double-play situational IQ. Under this model, Keith Hernandez scales to 24.8 true wins saved defensively. Applying this sensible math fixes his entire ledger, launching his career total from 60.4 WAR up to a staggering 83.9 overall WAR—vaulting him straight into what should have been HOF numbers.

We are also currently working to get our hands on proprietary, MLB-level spatial throwing accuracy data. Right now, public stats only track raw velocity (how hard a guy throws). We are targeting the raw camera tracking data that measures the exact sub-inch coordinate where a throw intersects the first baseman’s frame. This lets us calculate “True Flight Efficiency” (how quickly the ball actually gets there based on release and trajectory) and finally docks shortstops for erratic throws while properly crediting first basemen for saving errors with elite scoops.

Once this data is fully reviewed by their team, this framework might soon be deployed in the near future in a well-respected clubhouse—not ours.

While the entire body of work we’re putting together is going to be incredibly comprehensive, I would shorten it down significantly into a highly digestible, punchy summary for a post here on the forum. Right now, I’m just feeling out the appetite for this kind of data.

So here’s my question:

Would anyone here actually be interested in checking out a condensed breakdown if I put it together? Let me know.