Rosternomics
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July 22, 2022

NYMPIT

unsettledToo soon to call — players still accruing.
NYMNYM Billy Eppler net +$4.0M net +1.1
received +$0.0M+$0.0M ± $18M expected surplus · +$4.0M realized received 0.5 ± 2 expected · 1.1 realized WAR
Playoff odds: this deal moved NYM's 2022 odds 92% → 93% (+1.5 pts) — how trade timing is graded ↗
receives — most valuable first
Dan Vogelbach1B/DH·30y·L/R
+$0.0M+$0.0M± $18M exp surplusrealized +$4.0M 0.5± 2 exp WARrealized 1.1
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 0.3/yr over 1.3 season
Talent
0.27/yr blended
Horizon
3.0 control yrs × 0.59 age decline
PITPIT Ben Cherington net −$4.0M net -1.1
received +$0.0M+$0.0M ± $0M expected surplus · +$0.0M realized received 0.0 ± 0 expected · 0.0 realized WAR
Playoff odds: this deal moved PIT's 2022 odds 0% → 0% (-0.1 pts) — how trade timing is graded ↗
receives — most valuable first
cash / PTBNL
+$0.0M+$0.0M± $0M exp surplusrealized +$0.0M 0.0± 0 exp WARrealized 0.0
Cash or player to be named — no projection

Each player is valued on what he was expected to produce at the time of the trade, versus what he actually produced for his new team.

Expected WAR blends a player's pedigree (Baseball America rank / draft slot, or a baseline) with his recent track record, projected over the years of team control acquired. The ± band is the uncertainty — wide for unproven prospects, tight for established veterans. Surplus values that production at the FA market price of a win (~$8M/WAR) minus salary — so cost-controlled players carry large surplus and expensive ones little, even at the same WAR. Who won is descriptive, not a skill claim: ~99% of a trade's outcome is unforeseeable at the time.

Historically these expected values are unbiased and land within ±2 WAR of reality 75% of the time — yet the side the model favors actually comes out ahead only 53% of the time. The grade is a calibrated bet, not a prediction. Why trades are an efficient market →