Rosternomics
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April 17, 2025

SDPPIT

unsettledToo soon to call — players still accruing.
SDPSDP AJ Preller net +$2.4M net +0.7
received −$2.4M−$2.4M ± $13M expected surplus · +$2.4M realized received 0.1 ± 2 expected · 0.7 realized WAR
Playoff odds: this deal moved SDP's 2025 odds 23% → 26% (+2.8 pts) — how trade timing is graded ↗
receives — most valuable first
Bryce JohnsonOF·30y·B/R
−$2.4M−$2.4M± $13M exp surplusrealized +$2.4M 0.1± 2 exp WARrealized 0.7
Prior
#186 overall draft pick — at the league baseline → 0.21/yr
Evidence
recent form -0.3/yr over 0.5 season
Talent
0.05/yr blended
Horizon
4.4 control yrs × 0.23 age decline
PITPIT Ben Cherington net −$2.4M net -0.7
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 PIT's 2025 odds 3% → 3% (-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

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 →