Rosternomics
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February 21, 2017

BALNYY

BAL won this trade +$7.2M surplus BAL won this trade +1.7 WAR
BALBAL Dan Duquette net +$7.2M net +1.7
received −$0.8M−$0.8M ± $17M expected surplus · +$7.2M realized received 0.4 ± 2 expected · 1.7 realized WAR
Playoff odds: this deal moved BAL's 2017 odds 1% → 1% (+0 pts) — how trade timing is graded ↗
receives — most valuable first
Richard BleierP·30y·L/L
−$0.8M−$0.8M± $17M exp surplusrealized +$7.2M 0.4± 2 exp WARrealized 1.7
Prior
#183 overall draft pick — at the league baseline → 0.21/yr
Evidence
recent form 0.3/yr over 1.0 season
Talent
0.26/yr blended
Horizon
4.4 control yrs × 0.34 age decline
NYYNYY Brian Cashman net −$7.2M net -1.7
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 NYY's 2017 odds 93% → 93% (-0.3 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 →