Rosternomics
← Trade Database
Share on 𝕏
November 20, 2014

ANATEX

ANA won this trade +$0.0M surplus ANA won this trade +0.2 WAR
ANAANA Jerry Dipoto net +$0.0M net +0.2
received −$0.8M−$0.8M ± $19M expected surplus · +$0.0M realized received 0.4 ± 2 expected · 0.2 realized WAR
Playoff odds: this deal moved ANA's 2015 odds 5% → 6% (+0.3 pts) — how trade timing is graded ↗
receives — most valuable first
Dan RobertsonOF·30y·R/R
−$0.8M−$0.8M± $19M exp surplusrealized +$0.0M 0.4± 2 exp WARrealized 0.2
Prior
#1005 overall draft pick — at the league baseline → 0.21/yr
Evidence
recent form 0.4/yr over 0.5 season
Talent
0.25/yr blended
Horizon
4.4 control yrs × 0.38 age decline
TEXTEX Jon Daniels net +$0.0M net -0.2
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 TEX's 2015 odds 12% → 12% (-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 →