Rosternomics
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December 14, 2022

MILCLE

unsettledToo soon to call — players still accruing.
MILMIL David Stearns net +$2.4M net +0.6
received +$0.8M+$0.8M ± $38M expected surplus · +$2.4M realized received 0.9 ± 5 expected · 0.6 realized WAR
Playoff odds: this deal moved MIL's 2023 odds 14% → 17% (+2.8 pts) — how trade timing is graded ↗
receives — most valuable first
Owen Miller1B/2B·27y·R/R
+$0.8M+$0.8M± $38M exp surplusrealized +$2.4M 0.9± 5 exp WARrealized 0.6
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 0.2/yr over 1.1 season
Talent
0.20/yr blended
Horizon
5.0 control yrs × 0.90 age decline
CLECLE Chris Antonetti net −$2.4M net -0.6
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 CLE's 2023 odds 6% → 5% (-1.2 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 →