WSN⇄HOU

WSNWSN Paul Toboni net +$0.0M net +0.2

received −$0.8M−$0.8M ± $9M expected surplus · +$0.0M realized received 0.2 ± 1 expected · 0.2 realized WAR

Playoff odds: this deal moved WSN's 2026 odds 1.7% → 1.8% (+0.1 pts) — how trade timing is graded ↗

receives — most valuable first

Tom CosgroveP·30y·L/L

−$0.5M−$0.5M± $9M exp surplusrealized +$0.0M 0.2± 1 exp WARrealized 0.2

Prior

league baseline (track record outweighs draft pedigree) → 0.21/yr

Evidence

recent form 0.2/yr over 1.2 season

Talent

0.42/yr blended

Horizon

3.0 control yrs × 0.19 age decline

why ▾hide ▴

HOUHOU Dana Brown net +$0.0M net -0.2

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 HOU's 2026 odds 52.0% → 51.6% (-0.4 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 →