David BecklesLF FCL Blue Jays
Age 22 R/R 6'3" / 215 lbs ROK HR +12%BB +4% Svc 0.0 · Ctrl thru 2037 peak 0.5 · 2030
wRC+†75
AVG/OBP/SLG.212 / .283 / .341
PA305
HR7
K%30
BB%8
MLB%0%
BAT: -8.7 runs (wOBA-derived runs vs avg)-9BATRUN: +0.4 runs (SB/CS + UBR baserunning)+0RUNFLD: +0.0 runs (Defensive runs vs avg)+0FLDPOS: -3.3 runs (Positional adjustment)-3POSREP: +8.6 runs (Replacement-level credit)+9REPTotal WAR: -0.30-0.3WAR
Scouting · nowfuture
HIT
4545
PWR
4040
SPD
4040
EYE
4835
trajectory · 10 yrs
0.5peak
2030

Contract

ESTIMATED  ·  service-time + WAR-based estimator (needs verification)
Status   MiLB
MLB Debut   2032
Service   0 yrs (est)
Team Control Through   2037
First FA Year   2038
YearStatusSalary Proj WAR Value Surplus
2026MiLBstill in minors · estimated debut 2032
2027MiLBstill in minors · estimated debut 2032
2028MiLBstill in minors · estimated debut 2032
2029MiLBstill in minors · estimated debut 2032
2030MiLBstill in minors · estimated debut 2032
2031MiLBstill in minors · estimated debut 2032
2032Ext / FA-deal$0.9M+0.4$2M+$1.0M
2033Ext / FA-deal$1.0M+0.2$1.0M+$0.0M
2034Ext / FA-deal$1.0M+0.1$0.5M-$0.5M
2035Ext / FA-deal$0.2M
2036Ext / FA-deal$0.4M
2037Ext / FA-deal$0.6M
Totals $4M $-4M -$8M
Why some years run red
On long-term deals the salary is locked in regardless of how the player ages. Late years are red whenever projected production drops below the AAV — that's expected, not a sign the deal is bad. The honest scorecard is the Net Surplus over the whole contract, not any single year.

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

YearAge LvlTeam PAAB H2B3BHR BBSOHBP SBCS AVGOBPSLGOPS ISOBABIP K%BB% wOBAwRC+ BATRUNFLDPOSREP WAR
202218 ROKDSL NYY Yankees 209185 34303 20862 102 .184.271.249.519 .065.316 4110 .234 37 -15 +1 +0 -2 +6 -1.0
202319 ROKDSL NYY Bombers 144118 23601 19415 42 .195.331.271.602 .076.282 2813 .285 76 -4 +0 +0 -2 +4 -0.1
202420 ROKDSL Blue Jays 11299 16301 11192 00 .162.259.222.481 .061.190 1710 .224 30 -9 +0 +0 -1 +3 -0.7
202521 ROK2 teams 311283 541106 221215 21 .191.261.293.555 .102.306 397 .244 45 -19 +0 +0 -3 +9 -1.4
▸ 2026 Season
202622 MLBTOR 305275 581117 24913 41 .211.281.335.616 .124.289 308 .283 75 -9 +0 +0 -3 +9 -0.3
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
202723 MLB 11%TOR 345309 681329 29994 51 .220.295.362.658 .142.289 298 .293 82 -7 +1 +0 -4 +10 -0.0
202824 MLB 26%TOR 416372 8316211 361165 61 .223.300.366.666 .142.290 289 .299 87 -6 +1 +0 -4 +12 0.2
202925 MLB 43%TOR 454406 9218213 401255 61 .227.304.377.681 .150.291 289 .304 91 -5 +1 +0 -5 +13 0.4
203026 MLB 58%TOR 477426 9719214 431315 71 .228.306.380.686 .153.292 279 .306 92 -4 +1 +0 -5 +14 0.5
203127 MLB 76%TOR 486433 9819214 441336 61 .226.306.376.683 .150.292 279 .306 92 -4 +1 +0 -5 +14 0.5
203228 MLB 84%TOR 487434 9819214 451355 61 .226.306.376.681 .150.291 289 .305 91 -5 +1 -1 -5 +14 0.4
203329 MLB 90%TOR 481429 9518213 441345 51 .221.301.364.665 .142.290 289 .303 90 -6 +1 -1 -5 +14 0.2
203430 MLBTOR 473421 9318213 441345 50 .221.302.366.668 .145.289 289 .300 87 -7 +1 -2 -5 +13 0.1
203531 MLBTOR 460410 8917212 421325 40 .217.298.356.654 .139.287 299 .296 85 -8 +1 -3 -5 +13 -0.2
203632 MLBTOR 442393 8516211 411295 30 .216.298.351.650 .135.286 299 .291 81 -10 +1 -4 -5 +13 -0.5
203733 MLBTOR 413368 7815210 381234 30 .212.293.345.638 .133.284 309 .286 77 -11 +1 -4 -4 +12 -0.7
203834 MLBTOR 368328 671318 331134 20 .204.285.323.608 .119.282 319 .279 72 -12 +0 -5 -4 +10 -1.0
▸ Career Totals (MLE all levels + projections)
Career 63835689 122823524160 575186275 7813 .216.296.350.646 .134.289 299 .291 81 -139 +10 -20 -68 +181 -3.6
/ 162G 650579 12424216 591908 81 .214.296.345.641 .131.287 299 .291 81 -14 +1 -2 -7 +18 -0.4

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

YearAge LvlTeam PAAB H2B3BHR BBSOHBP SBCS AVGOBPSLGOPS ISOBABIP K%BB% wOBAwRC+ BATRUNFLDPOSREP WAR
202218 ROKDSL NYY Yankees 209174 48605 31582 102 .276.391.397.788 .121.381 2815 .357 132 +7 +1 +6 1.5
202319 ROKDSL NYY Bombers 144105 28802 32285 42 .267.458.400.858 .133.338 1922 .394 160 +10 +0 +4 1.4
202420 ROKDSL Blue Jays 11292 18401 18132 00 .196.339.272.611 .076.218 1216 .295 84 -2 +0 +3 0.1
202521 ADunedin Blue Jays 7465 14401 9210 00 .215.311.323.634 .108.302 2812 .292 82 -2 +0 +2 0.1
202521 ROKFCL Blue Jays 237207 631118 24635 21 .304.390.483.873 .179.401 2710 .387 154 +15 +0 +7 2.2

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

Scouting At Match Age Next 3 Yrs Peak 3 Yrs
Comp Age HIT PWR SPD EYE AVG/OBP/SLG ISOBABIP HRSB K%BB% wRC+WAR AVG/OBP/SLG ISOBABIP HRSB K%BB% wRC+WAR AVG/OBP/SLG ISOBABIP HRSB K%BB% wRC+WAR
David Beckles (OGILVIE) 22 45 40 40 35 .212/.283/.341 .129.289 74 30% 8% 75 -0.0
Rainel Rosario
2011 · A
22 42→51 45→50 46→50 44 .207/.283/.342 .135.296 119 32% 8% 74 -0.1 .210/.267/.310 .100.310 89 33% 7% 59 -1.1 .253/.308/.402.150.28519618%7%96+1.1
Brock Peterson
2006 · A
22 45→52 44→55 41→40 43 .222/.287/.343 .122.300 124 29% 7% 76 +0.1 .239/.299/.388 .149.310 164 27% 6% 93 +1.3 .240/.300/.399.159.30918227%6%93+1.0
Clint Coulter
2015 · A
22 43 48→50 42→40 46 .217/.297/.357 .140.276 155 27% 8% 85 +0.7 .209/.276/.336 .127.266 134 26% 6% 70 -0.3 .205/.273/.359.153.24919425%5%71-0.1
Robbie Tenerowicz
2017 · A
22 44→51 43→50 38→45 38 .216/.265/.328 .111.296 104 30% 5% 63 -0.9 .227/.280/.338 .111.289 106 24% 6% 71 -0.3 .232/.320/.392.161.28820225%7%102+1.2
Zelous Wheeler
2009 · A
22 44→52 43→50 43→45 43 .219/.274/.329 .109.278 107 25% 6% 66 -0.6 .233/.304/.346 .113.289 108 22% 8% 84 +0.6 .242/.315/.375.133.28514719%8%93+1.0
Kody Hinze
2009 · A
22 42→46 45→50 45→30 46 .213/.281/.336 .124.281 134 28% 8% 72 -0.2 .208/.278/.341 .133.286 152 31% 8% 72 -0.2 .216/.290/.370.154.28520130%9%82+0.4
Anderson Gomes
2008 · A
23 45→38 43→45 44→50 42 .224/.271/.336 .112.289 117 26% 6% 66 -0.6 .215/.267/.329 .114.297 118 30% 6% 63 -0.8 .160/.218/.266.106.229131035%6%24-0.9
Chris Gittens
2016 · A
22 48→45 46→55 45→30 41 .231/.295/.365 .134.326 145 32% 7% 85 +0.7 .210/.280/.369 .159.308 214 37% 8% 81 +0.4 .210/.302/.377.167.30724037%11%89+0.5
Tyler Saladino
2012 · A
23 44→46 46→45 45→55 42 .217/.280/.356 .139.292 137 29% 7% 76 +0.1 .216/.285/.317 .101.284 820 25% 8% 68 -0.5 .253/.299/.369.116.300112519%5%84+0.4
Matt Vierling
2019 · A
22 46→55 47→50 44→50 39 .231/.274/.365 .134.292 149 26% 4% 76 +0.1 .206/.259/.305 .099.275 914 27% 5% 54 -1.4 .252/.313/.388.135.304131021%7%95+1.2
Jimmy Herron
2019 · A
23 45 44→45 42→55 46 .224/.288/.336 .112.272 126 22% 7% 75 -0.0 .194/.268/.288 .094.254 814 25% 8% 53 -1.5 .218/.294/.351.132.264152423%8%78+0.2
Johermyn Chavez
2011 · A
22 44→47 49→50 43→45 37 .224/.274/.373 .148.302 186 31% 5% 79 +0.3 .209/.271/.345 .136.279 165 30% 6% 70 -0.3 .187/.257/.303.117.24914430%6%52-0.9
Dustin Geiger
2014 · A
22 44→47 47→50 40 41 .223/.276/.360 .137.284 154 27% 6% 76 +0.0 .208/.267/.335 .127.283 145 30% 7% 66 -0.6 .176/.239/.297.121.25214235%7%41-1.3
Jonathan Rodríguez
2013 · A
23 41→51 49→50 40→50 44 .211/.287/.363 .152.286 175 32% 8% 82 +0.5 .224/.290/.358 .134.302 1410 29% 8% 82 +0.5 .225/.301/.376.151.30919332%9%88+0.7
Torin Montgomery
2023 · A
22 47 45→40 48→45 38 .220/.283/.342 .122.338 126 37% 6% 74 -0.1 .226/.311/.324 .098.344 85 33% 9% 82 +0.5 .220/.314/.307.086.3437334%10%75+0.0
Cory Vaughn
2012 · A
23 43→40 44→45 44→50 42 .211/.283/.325 .114.290 127 30% 7% 70 -0.3 .201/.277/.328 .127.279 1413 31% 8% 69 -0.4 .187/.266/.311.124.260141632%8%57-0.9
Koby Clemens
2009 · A
22 41→51 43→55 43→45 43 .205/.268/.319 .114.278 114 29% 7% 62 -0.9 .221/.289/.389 .168.303 195 32% 8% 89 +1.0 .210/.283/.393.182.28522533%8%86+0.7
Deibinson Romero
2009 · A
22 46 43→50 46→40 41 .227/.280/.341 .113.296 117 26% 6% 72 -0.2 .204/.270/.299 .095.282 83 29% 7% 57 -1.2 .226/.295/.367.141.27217223%8%84+0.5
Samuel Hiciano
2016 · A
22 41 45 43→50 37 .210/.250/.333 .124.282 138 30% 5% 57 -1.2 .210/.267/.337 .127.300 127 32% 7% 66 -0.6 .163/.236/.314.152.23111033%8%43-0.4
Matthew Whitney
2006 · A
22 41→49 41→50 40→30 43 .205/.264/.296 .090.268 104 27% 6% 54 -1.4 .203/.258/.332 .129.290 162 34% 6% 61 -1.0 .237/.296/.387.150.29618125%7%89+0.8