Does the sim match real-life extremes for contact hitters in extreme parks? And is “building for your park” by hitter type exploitable?
Our park effects work established that in Diamond Mind Baseball, park effects are additive: the same park adds or subtracts a fixed number of 1B, 2B, 3B, and HR per 600 AB for every batter. Baker Bowl adds about +10.5 HR per 600 AB; the Astrodome subtracts about −6 to −7. That model is evidence-based (Tom Tippett’s 2004 SABR presentation; see Imagine Sports Downloads) and fits DMB exports: the additive diff is roughly constant across high-power and low-power hitters, while the percentage impact varies wildly.
On message boards, a researcher (Lemayripper) cited external work suggesting that hitter type—not just raw power—drives how park affects HR totals. One often-quoted result: move a 5 HR/600 hitter and a 40 HR/600 hitter to a park 10% more HR-friendly; the weak hitter increases by about 50% (in percentage terms), the slugger by only about 1 additional HR. So the effect is not uniform; it works in the opposite direction of what many assume (weak hitters get the bigger percentage bump). Batted-ball data that would nail this down weren’t available until Statcast—so for historical seasons we rely on archival park × player splits and sim output.
Ashburn anecdote (Lemayripper). In around 25,000 archived ABs in both Baker Bowl and the Astrodome, Ashburn hits a HR every 70 AB in Baker and has never hit a single HR in the Astrodome—0 in 25,000. In a classic coded league he had a 14 HR season in Guaranteed Rate Park. That real-life vs. sim gap is the core of this research idea.
We propose to test the following:
Conventional wisdom says “don’t build for your park.” A reported plan to exploit park × hitter-type effects in round two of the Open suggests that at least some players believe the opposite. We want to see what the data say.
Compare real-life park-specific HR rates (and, where available, 2B/3B/1B) for a small set of well-defined contact types and power types to sim output for the same players in the same parks. Focus on extreme parks (Astrodome, Baker Bowl, and a HR-friendly modern park such as Guaranteed Rate). If the sim systematically credits contact hitters with more HR in HR-friendly or neutral parks than real life did, that supports the “over-credit” hypothesis and frames the exploit question. We would then test whether roster construction by hitter type and home park beats additive-only valuation in controlled comparisons.
| Deliverable | Description |
|---|---|
| Validation note | One-pager comparing Ashburn (and 1–2 others) real park HR rates vs. sim, with caveats (sample size, era, park definitions). |
| Exploit memo | If building for park by hitter type appears to beat additive-only expectation, document when it matters and how (e.g. contact types in Baker/GRF; avoid contact-only in Astrodome). |
| Thread follow-up | If we find material gaps, optional board post citing the research and linking to Tippett and hitter-type literature. |
Our valuation and MVP tools use additive park adjustment: the same delta per 600 AB for every batter. If the engine in practice rewards or penalizes certain hitter types more than that model predicts, then (a) our valuations could be off for those types in those parks, and (b) league play could have an exploitable angle that “don’t build for your park” understates. This research idea is the first step to testing both.
strategy/BOARD_THREAD_SUMMARY.md.strategy/PARK_DELTA_MATH.md; Baker Bowl and Astrodome deltas in our reference table.strategy/PARK_HITTER_TYPE_RESEARCH_IDEA.md.