Rosternomics
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November 22, 2021

ATLSFG

SFG won this trade +$0.8M surplus ATL won this trade +0.0 WAR
ATLATL Alex Anthopoulos net −$0.8M net +0.0
received −$0.8M−$0.8M ± $12M expected surplus · −$0.8M realized received 0.1 ± 2 expected · 0.0 realized WAR
receives — most valuable first
Jay JacksonP·35y·R/R
−$0.8M−$0.8M± $12M exp surplusrealized −$0.8M 0.1± 2 exp WARrealized 0.0
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 0.0/yr over 1.5 season
Talent
0.11/yr blended
Horizon
1.7 control yr × 0.61 age decline
SFGSFG Farhan Zaidi net +$0.8M net +0.0
received +$0.0M+$0.0M ± $0M expected surplus · +$0.0M realized received 0.0 ± 0 expected · 0.0 realized WAR
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 →