Rosternomics
← Trade Database
Share on 𝕏
December 14, 2017

PITPHI

PIT won this trade +$0.0M surplus PIT won this trade +0.3 WAR
PITPIT Neal Huntington net +$0.0M net +0.3
received +$1.6M+$1.6M ± $58M expected surplus · +$0.0M realized received 1.2 ± 7 expected · 0.3 realized WAR
Playoff odds: this deal moved PIT's 2018 odds 15% → 14% (-0.2 pts) — how trade timing is graded ↗
receives — most valuable first
Nick BurdiP·25y·R/R
+$1.6M+$1.6M± $58M exp surplusrealized +$0.0M 1.2± 7 exp WARrealized 0.3
Prior
#46 overall draft pick — at the league baseline → 0.21/yr
Evidence
no MLB track record — leans on pedigree
Talent
0.21/yr blended
Horizon
5.5 control yrs
PHIPHI Matt Klentak net +$0.0M net -0.3
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 PHI's 2018 odds 9% → 10% (+0.2 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 →