Rosternomics
← Trade Database
Share on 𝕏
January 17, 2025

TORCLE

unsettledToo soon to call — players still accruing.
TORTOR Ross Atkins net −$4.0M net +1.9
received −$20.8M−$20.8M ± $24M expected surplus · −$4.0M realized received 1.9 ± 3 expected · 1.9 realized WAR
Playoff odds: this deal moved TOR's 2025 odds 56% → 66% (+9.8 pts) — how trade timing is graded ↗
receives — most valuable first
Myles StrawOF·31y·R/R
−$20.8M−$20.8M± $24M exp surplusrealized −$4.0M 1.9± 3 exp WARrealized 1.9
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 1.1/yr over 1.5 season
Talent
0.73/yr blended
Horizon
4.0 control yrs × 0.66 age decline
CLECLE Chris Antonetti net +$4.0M net -1.9
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 2025 odds 9% → 6% (-2.9 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 →