Rosternomics

2022 MLB Draft

Every MLB amateur draft, 1985–2025. Real = career WAR so far. Expected = the model's full-career projection for this slot × position × age-at-draft (HS vs college), ± a predictive band. DVOS = Real minus what the same cohort has produced by the same number of years post-draft (apples-to-apples — so we don't punish a 2024 pick for not yet being a 10-yr veteran). Example: Bazzana (2024 #1, college IF) has Real 0.8; the typical #1 college IF has produced 1.6 WAR by year 2 post-draft, so his DVOS = −0.8 (0.8 behind cohort); long-run Expected ≈ 40 WAR. Model: empirical-Bayes hierarchical, fit on 41 years of realized outcomes. SD leaderboard →

Unsettled: selected year(s) include a class with <5 seasons to play out — realized WAR is partial and vs-Pace is preliminary. Most picks take ~5 years to surface; the back of the draft can take a decade. The Expected column is the right "asset value" read for fresh picks.
Round:
Year Pick Rd Team Player Pos Age B/T Ht Wt Bonus Bonus% Scouting Dir GM / POBO Real DVOS Expected
2022 1 1.1 BAL Jackson Holliday IF 2B 19 HS L/R 5'11" 200 $8.19M 46% Mike Elias 1.1 -2.9 49.9±4.0
2022 2 1.2 ARI Druw Jones OF OF 19 HS R/R 6'2" 180 $8.19M 53% Ian Rebhan Mike Hazen 0.0 -1.7 14.3±4.2
2022 3 1.3 TEX Kumar Rocker P P 23 COLL R/R 6'5" 245 $5.2M 49% Kip Fagg Jon Daniels 1.0 -1.5 9.8±3.9
2022 4 1.4 PIT Termarr Johnson IF SS 18 HS L/R 5'7" 201 $7.22M 50% Joe Dellicarri Ben Cherington 0.0 -3.6 18.9±3.9
2022 5 1.5 WSN Elijah Green OF OF 19 HS R/R 6'3" 225 $6.5M 51% Michael Rizzo 0.0 -0.6 8.0±4.1
2022 6 1.6 MIA Jacob Berry IF 3B 21 COLL S/R 5'11" 212 $6.0M 53% D J Svihlik Kim Ng 0.0 -2.4 14.8±4.0
2022 7 1.7 CHC Cade Horton P P 21 COLL R/R 6'1" 211 $4.45M 38% Dan Kantrovitz Jed Hoyer 2.2 -0.4 7.9±3.8
2022 8 1.8 MIN Brooks Lee IF SS 21 COLL S/R 6'0" 205 $5.67M 51% Sean Johnson Derek Falvey 0.4 -2.0 14.8±3.8
2022 9 1.9 KCR Gavin Cross OF OF 21 COLL L/L 6'2" 210 $5.2M 47% Dan Ontiveros J.J. Picollo 0.0 -2.2 8.5±3.9
2022 10 1.10 COL Gabriel Hughes P P 21 COLL R/R 6'4" 238 $4.0M 28% Bill Schmidt 0.0 -2.6 7.9±3.7
2022 11 1.11 NYM Kevin Parada C C 21 COLL R/R 5'11" 197 $5.02M 34% Marc Tramuta Billy Eppler 0.0 -1.7 17.0±4.1
2022 12 1.12 DET Jace Jung IF 3B 22 COLL L/R 5'11" 205 $4.59M 50% Scott Pleis Sam Menzin -0.3 -2.4 10.8±3.7
2022 13 1.13 ANA Zach Neto IF SS 21 COLL R/R 5'11" 185 $3.5M 42% Matt Swanson Perry Minasian 8.8 +6.6 10.8±3.7
2022 14 1.14 NYM Jett Williams IF SS 19 HS R/R 5'7" 179 $3.9M 27% Marc Tramuta Billy Eppler 0.0 -0.4 7.8±3.8
2022 15 1.15 SDP Dylan Lesko P P 19 HS R/R 6'2" 195 $3.9M 33% AJ Preller 0.0 -0.6 5.5±3.7
2022 16 1.16 CLE Chase DeLauter OF RF 21 COLL L/L 6'3" 235 $3.75M 32% Paul Gillispie Chris Antonetti 1.2 +0.5 4.4±3.7
2022 17 1.17 PHI Justin Crawford OF CF 18 HS L/R 6'2" 188 $3.89M 52% Brian Barber Dave Dombrowski 0.3 -0.2 8.0±3.7
2022 18 1.18 CIN Cam Collier IF 3B 18 HS L/R 6'1" 210 $5.0M 41% Joe Katuska Nick Krall 0.0 -0.4 2.8±3.7
2022 19 1.19 OAK Daniel Susac C C 21 COLL R/R 6'5" 210 $3.53M 37% Eric Kubota David Forst 0.5 +0.2 2.0±3.9
2022 20 1.20 ATL Owen Murphy P P 19 HS R/R 6'1" 190 $2.56M 22% Dana Brown Alex Anthopoulos 0.0 -0.4 5.5±3.7
2022 21 1.21 SEA Cole Young IF 2B 19 HS L/R 5'10" 180 $3.3M 39% Scott Hunter Jerry Dipoto 0.6 +0.2 2.8±3.7
2022 22 1.22 STL Cooper Hjerpe P P 21 COLL L/L 6'3" 200 $3.18M 41% Jamal Strong John Mozeliak 0.0 -1.3 5.5±3.7
2022 23 1.23 TOR Brandon Barriera P P 18 HS L/L 6'2" 180 $3.6M 38% Shane Farrell Ross Atkins 0.0 -0.4 5.5±3.7
2022 24 1.24 BOS Mikey Romero IF SS 18 HS L/R 5'11" 175 $2.3M 24% Paul Toboni Chaim Bloom 0.0 -0.4 2.8±3.7
2022 25 1.25 NYY Spencer Jones OF RF 21 COLL L/L 6'7" 240 $2.88M 36% Brian Cashman -0.2 -0.9 4.4±3.7
2022 26 1.26 CHW Noah Schultz P P 19 HS L/L 6'10" 240 $2.8M 37% Mike Shirley Kenny Williams 0.4 +0.3 2.7±3.7
2022 27 1.27 MIL Eric Brown Jr. IF SS 22 COLL R/R 5'10" 190 $2.05M 27% David Stearns 0.0 -0.4 3.8±3.7
2022 28 1.28 HOU Drew Gilbert OF CF 22 COLL L/L 5'9" 195 $2.5M 31% Evan Brannon James Click -0.1 -0.7 3.8±3.7
2022 29 1.29 TBR Xavier Isaac IF 1B 19 HS L/L 6'3" 240 $2.55M 30% Rob Metzler Erik Neander 0.0 -0.3 2.8±3.7
2022 30 1.30 SFG Reggie Crawford IF 1B 22 COLL L/L 6'4" 255 $2.3M 33% Michael Holmes Farhan Zaidi 0.0 -0.4 3.8±3.7

Model: empirical-Bayes hierarchical — smooth monotone slot curve × position group (P/IF/OF/C/DH) × age bin (HS <20 vs COLL 20+) × maturity. The slot curve is forced monotone-decreasing within each position+age cell, so pick N can't have lower expected than pick N+1 by construction. Predictive ± band = √(σ²·(1 + 1/n_cell)) — pooled within-cell residual SD plus the cell-mean uncertainty for a new pick at that cell. Fallback chain when a (slot, pos, age) cell is too sparse: → (slot, pos) → (slot). Position × age effects: pitchers debut earlier (high realized at 2 yrs, lower career due to attrition); college catchers ~2× HS catchers career WAR at top slots; HS slot-1 IF/OF carry premium upside (Harper/Correa/A-Rod pattern). Coverage: position 100% (1985–2025), bio (born/ht/wt) ~97%, age 97%, signing bonus only ~11% (sparse pre-2008 — MLB Stats API hasn't backfilled). SD attribution follows SABR (single unambiguous name per team-year), GM uses our hire/POBO records. Team/GM development effects intentionally NOT in the model — that signal belongs on the DVOS-attribution side (per-SD on /sds, per-GM in this table), or it would collapse to zero by construction.