Rosternomics
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February 1, 2017

CHCCOL

CHC won this trade +$3.2M surplus CHC won this trade +0.7 WAR
CHCCHC Jed Hoyer net +$3.2M net +0.7
received −$4.0M−$4.0M ± $38M expected surplus · +$3.2M realized received 0.0 ± 5 expected · 0.7 realized WAR
Playoff odds: this deal moved CHC's 2017 odds 61% → 64% (+2.9 pts) — how trade timing is graded ↗
receives — most valuable first
Eddie ButlerP·26y·R/R
−$4.0M−$4.0M± $38M exp surplusrealized +$3.2M 0.0± 5 exp WARrealized 0.7
Prior
BA #77 pedigree (2015) → 0.35/yr
Evidence
recent form -0.4/yr over 1.7 season
Talent
-0.09/yr blended
Horizon
5.0 control yrs
COLCOL Jeff Bridich net −$3.2M net -0.7
received +$0.0M+$0.0M ± $12M expected surplus · +$0.0M realized received 0.2 ± 2 expected · 0.0 realized WAR
Playoff odds: this deal moved COL's 2017 odds 15% → 13% (-1.5 pts) — how trade timing is graded ↗
receives — most valuable first
James Farris
+$0.0M+$0.0M± $12M exp surplusrealized +$0.0M 0.2± 2 exp WARrealized 0.0
Unidentified minor-league throw-in — valued at the ~0.2 WAR base rate (most produce nothing)

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 →