Rosternomics
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May 13, 2007

CLESEA

CLE won this trade +$3.2M surplus CLE won this trade +0.4 WAR
CLECLE Mark Shapiro net +$3.2M net +0.4
received +$0.0M+$0.0M ± $12M expected surplus · +$0.0M realized received 0.2 ± 2 expected · 0.0 realized WAR
Playoff odds: this deal moved CLE's 2007 odds 52% → 54% (+2.1 pts) — how trade timing is graded ↗
receives — most valuable first
Gregorio Rosario
+$0.0M+$0.0M± $12M exp surplusrealized +$0.0M 0.2± 2 exp WARrealized 0.0
Unidentified minor-league throw-in — valued at the ~0.2 WAR base rate (most produce nothing)
SEASEA Bill Bavasi net −$3.2M net -0.4
received +$4.0M+$4.0M ± $18M expected surplus · −$3.2M realized received 1.3 ± 2 expected · -0.4 realized WAR
Playoff odds: this deal moved SEA's 2007 odds 6% → 6% (-0.5 pts) — how trade timing is graded ↗
receives — most valuable first
Jason DavisP·27y·R/R
+$4.0M+$4.0M± $18M exp surplusrealized −$3.2M 1.3± 2 exp WARrealized -0.4
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 0.9/yr over 2.2 seasons
Talent
0.65/yr blended
Horizon
2.0 control yrs

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 →