OAK⇄SEA

OAKOAK David Forst net +$0.8M net +0.1

received +$3.2M+$3.2M ± $14M expected surplus · +$0.8M realized received 0.8 ± 2 expected · 0.1 realized WAR

Playoff odds: this deal moved OAK's 2026 odds 0.0% → 0.0% (+0 pts) — how trade timing is graded ↗

receives — most valuable first

José SuarezP·28y·L/L

+$3.3M+$3.3M± $14M exp surplusrealized +$0.8M 0.8± 2 exp WARrealized 0.1

Prior

no pedigree — league baseline → 0.21/yr

Evidence

recent form 0.3/yr over 2.0 seasons

Talent

0.53/yr blended

Horizon

2.0 control yrs × 0.66 age decline

why ▾hide ▴

SEASEA Jerry Dipoto net −$0.8M net -0.1

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 SEA's 2026 odds 44.9% → 44.4% (-0.5 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

why ▾hide ▴

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 →