Rosternomics
← Trade Database
May 10, 2016

WSNANA

WSN won this trade +$0.8M surplus WSN won this trade +0.2 WAR
WSNWSN Michael Rizzo net +$0.8M 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 WSN's 2016 odds 70% → 71% (+0.9 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
ANAANA Billy Eppler net −$0.8M net -0.2
received +$0.8M+$0.8M ± $7M expected surplus · −$0.8M realized received 0.3 ± 1 expected · -0.2 realized WAR
Playoff odds: this deal moved ANA's 2016 odds 2% → 2% (-0.1 pts) — how trade timing is graded ↗
receives — most valuable first
Brendan RyanSS·34y·R/R
+$1.2M+$1.2M± $7M exp surplusrealized −$0.8M 0.3± 1 exp WARrealized -0.2
Prior
league baseline (track record outweighs draft pedigree) → 0.21/yr
Evidence
recent form 0.5/yr over 1.4 season
Talent
0.34/yr blended
Horizon
1.0 control yr

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 (composite top-100 rank / draft slot, or a baseline) with his recent track record, projected over the years of team control acquired. The ± figure is a historically calibrated predictive standard deviation, measuring how widely comparable forecasts have missed around their expected value. 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.