Rosternomics
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April 17, 2017

ANABAL

ANA won this trade +$2.4M surplus ANA won this trade +0.5 WAR
ANAANA Billy Eppler net +$2.4M net +0.5
received −$1.6M−$1.6M ± $51M expected surplus · +$2.4M realized received 0.5 ± 6 expected · 0.5 realized WAR
Playoff odds: this deal moved ANA's 2017 odds 3% → 4% (+0.8 pts) — how trade timing is graded ↗
receives — most valuable first
Parker BridwellP·26y·R/R
−$1.6M−$1.6M± $51M exp surplusrealized +$2.4M 0.5± 6 exp WARrealized 0.5
Prior
#268 overall draft pick — at the league baseline → 0.21/yr
Evidence
recent form -0.9/yr over 0.1 season
Talent
0.10/yr blended
Horizon
5.5 control yrs × 0.91 age decline
BALBAL Dan Duquette net −$2.4M net -0.5
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 BAL's 2017 odds 1% → 1% (-0.2 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 →