Rosternomics
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November 4, 2016

PHIHOU

HOU won this trade +$11.2M surplus PHI won this trade +1.6 WAR
PHIPHI Matt Klentak net −$11.2M net +1.6
received −$4.8M−$4.8M ± $8M expected surplus · −$11.2M realized received 0.2 ± 1 expected · 1.6 realized WAR
Playoff odds: this deal moved PHI's 2017 odds 2% → 2% (+0.7 pts) — how trade timing is graded ↗
receives — most valuable first
Pat NeshekP·37y·B/R
−$4.8M−$4.8M± $8M exp surplusrealized −$11.2M 0.2± 1 exp WARrealized 1.6
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 0.5/yr over 2.8 seasons
Talent
0.39/yr blended
Horizon
0.6 control yr
HOUHOU Jeff Luhnow net +$11.2M net -1.6
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 HOU's 2017 odds 98% → 97% (-1 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 →