Rosternomics
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August 31, 2015

LADSEA

LAD won this trade +$0.0M surplus LAD won this trade +0.6 WAR
LADLAD Andrew Friedman net +$0.0M net +0.6
received +$6.4M+$6.4M ± $18M expected surplus · +$0.0M realized received 1.9 ± 2 expected · 0.6 realized WAR
Playoff odds: this deal moved LAD's 2015 odds 82% → 84% (+2 pts) — how trade timing is graded ↗
receives — most valuable first
Justin RuggianoOF·33y·R/R
+$6.4M+$6.4M± $18M exp surplusrealized +$0.0M 1.9± 2 exp WARrealized 0.6
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 1.8/yr over 1.5 season
Talent
1.06/yr blended
Horizon
2.0 control yrs × 0.90 age decline
SEASEA Jeff Kingston net +$0.0M net -0.6
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 SEA's 2015 odds 4% → 3% (-0.5 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 →