Rosternomics

2018 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 →

Round:
Year Pick Rd Team Player Pos Age B/T Ht Wt Bonus Bonus% Scouting Dir GM / POBO Real DVOS Expected
2018 1 1.1 DET Casey Mize P P 21 COLL R/R 6'3" 212 $7.5M 51% Scott Pleis Al Avila 6.1 -7.0 19.6±3.8
2018 2 1.2 SFG Joey Bart C C 22 COLL R/R 6'2" 242 $7.03M 51% Bobby Evans 3.3 -16.1 24.4±3.7
2018 3 1.3 PHI Alec Bohm IF 3B 22 COLL R/R 6'4" 218 $5.85M 52% Johnny Almaraz Matt Klentak 9.3 -3.8 21.5±3.9
2018 4 1.4 CHW Nick Madrigal IF 3B 21 COLL R/R 5'7" 175 $6.41M 54% Kenny Williams 2.6 -10.5 21.5±4.1
2018 5 1.5 CIN Jonathan India IF 2B 22 COLL R/R 5'10" 200 $5.3M 42% Chris Buckley Nick Krall 7.8 -2.9 18.9±3.7
2018 6 1.6 NYM Jarred Kelenic OF RF 19 HS L/L 5'11" 206 $4.5M 41% Marc Tramuta Sandy Alderson 0.8 -2.6 8.0±3.9
2018 7 1.7 SDP Ryan Weathers P P 19 HS R/L 6'1" 230 $5.23M 42% Kurt Kemp AJ Preller 2.1 -2.1 9.9±3.8
2018 8 1.8 ATL Carter Stewart P P 19 HS R/R 6'6" 225 Brian Bridges Alex Anthopoulos 0.0 -3.2 5.8±3.8
2018 9 1.9 OAK Kyler Murray OF OF 21 COLL R/R 5'11" 195 $4.66M 43% Eric Kubota David Forst 0.0 -7.1 8.5±3.9
2018 10 1.10 PIT Travis Swaggerty OF LF 21 COLL L/L 5'11" 200 $4.4M 44% Joe Dellicarri Neal Huntington -0.2 -7.2 8.5±3.9
2018 11 1.11 BAL Grayson Rodriguez P P 19 HS L/R 6'5" 230 $4.3M 41% Gary Rajsich Dan Duquette 4.0 +1.1 5.5±3.7
2018 12 1.12 TOR Jordan Groshans IF SS 19 HS R/R 6'2" 200 Steve Sanders Ross Atkins -0.1 -3.3 7.8±3.8
2018 13 1.13 MIA Connor Scott OF LF 19 HS L/L 6'3" 208 $4.04M 39% Michael Hill 0.0 -3.1 8.0±3.7
2018 14 1.14 SEA Logan Gilbert P P 21 COLL R/R 6'6" 215 $3.88M 46% Jerry Dipoto 15.3 +9.9 7.9±3.7
2018 15 1.15 TEX Cole Winn P P 19 HS R/R 6'2" 190 $3.15M 35% Kip Fagg Jon Daniels 0.3 -2.5 5.5±3.7
2018 16 1.16 TBR Matthew Liberatore P P 19 HS L/L 6'4" 215 $3.5M 25% Rob Metzler Erik Neander 3.0 +0.7 5.5±3.7
2018 17 1.17 ANA Jordyn Adams OF CF 19 HS R/R 6'1" 181 $4.1M 47% Matt Swanson Billy Eppler -0.9 -4.0 8.0±3.7
2018 18 1.18 KCR Brady Singer P P 22 COLL R/R 6'5" 215 $4.25M 30% Dayton Moore 12.9 +9.3 5.5±3.7
2018 19 1.19 STL Nolan Gorman IF 3B 18 HS L/R 6'0" 225 $3.23M 34% Randy Flores John Mozeliak 3.1 +1.0 2.8±3.7
2018 20 1.20 MIN Trevor Larnach OF LF 21 COLL L/R 6'3" 223 $2.55M 37% Sean Johnson Derek Falvey 3.6 +0.8 4.4±3.7
2018 21 1.21 MIL Brice Turang IF 2B 19 HS L/R 6'0" 190 $3.41M 44% David Stearns 9.0 +6.9 2.8±3.7
2018 22 1.22 COL Ryan Rolison P P 21 COLL R/L 6'2" 213 $2.91M 34% Jeff Bridich -0.8 -4.5 5.5±3.7
2018 23 1.23 NYY Anthony Seigler IF 2B 19 HS L/S 5'9" 192 $2.82M 35% Brian Cashman -0.2 -2.3 2.8±3.7
2018 24 1.24 CHC Nico Hoerner IF 2B 21 COLL R/R 5'11" 200 $2.72M 30% Matt Dorey Jed Hoyer 21.7 +15.4 10.8±3.7
2018 25 1.25 ARI Matt McLain IF 2B 19 HS R/R 5'8" 180 Deric Ladnier Mike Hazen 0.0 -2.1 2.8±3.7
2018 26 1.26 BOS Triston Casas IF 1B 18 HS L/R 6'4" 244 $2.55M 35% Dave Dombrowski 2.2 +0.5 2.8±3.7
2018 27 1.27 WSN Mason Denaburg P P 19 HS R/R 6'4" 195 $3.0M 44% Michael Rizzo 0.0 -1.4 2.7±3.7
2018 28 1.28 HOU Seth Beer IF 1B 22 COLL L/R 6'2" 225 Jeff Luhnow -0.7 -2.9 3.8±3.7
2018 29 1.29 CLE Bo Naylor C C 18 HS L/R 5'9" 205 $2.58M 24% Scott Barnsby Chris Antonetti 4.4 +3.3 3.1±3.8
2018 30 1.30 LAD J.T. Ginn P P 19 HS R/R 6'2" 200 Billy Gasparino Andrew Friedman 0.0 -1.4 2.7±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.