Vincent PerozoC Brooklyn Cyclones
Age 23 L/R 5'11" / 170 lbs A+ H +5%HR +3% Svc 0.0 · Ctrl thru 2035 peak 0.8 · 2030
wRC+†49
AVG/OBP/SLG.177 / .266 / .265
PA281
HR3
K%37
BB%8
MLB%0%
BAT: -16.1 runs (wOBA-derived runs vs avg)-16BATRUN: +0.1 runs (SB/CS + UBR baserunning)+0RUNFLD: +0.0 runs (Defensive runs vs avg)+0FLDPOS: +5.0 runs (Positional adjustment)+5POSREP: +8.0 runs (Replacement-level credit)+8REPTotal WAR: -0.30-0.3WAR
Scouting · nowfuture
HIT
4545
PWR
3030
SPD
4040
EYE
4845
trajectory · 10 yrs
0.8peak
2030

Contract

ESTIMATED  ·  service-time + WAR-based estimator (needs verification)
Status   MiLB
MLB Debut   2030
Service   0 yrs (est)
Team Control Through   2035
First FA Year   2036
YearStatusSalary Proj WAR Value Surplus
2026MiLBstill in minors · estimated debut 2030
2027MiLBstill in minors · estimated debut 2030
2028MiLBstill in minors · estimated debut 2030
2029MiLBstill in minors · estimated debut 2030
2030Arb-2$0.9M+0.8$4M+$3M
2031Arb-3$0.9M+0.7$3M+$2M
2032Ext / FA-deal$0.9M+0.5$2M+$1M
2033Ext / FA-deal$0.4M+0.3$1M+$1M
2034Ext / FA-deal$5M+0.1$0.5M-$5M
2035Ext / FA-deal$0.6M
Totals $9M $10M +$1M
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
202118 ROKFCL Mets 6655 6101 7304 02 .109.258.182.439 .073.208 4511 .199 11 -7 -1 +0 +1 +2 -0.5
202219 ROK2 teams 177156 26523 76012 10 .167.257.282.539 .115.242 344 .239 41 -12 +0 +0 +3 +5 -0.4
202320 ASt. Lucie Mets 342304 441314 2515611 11 .145.235.234.469 .089.274 467 .215 23 -30 -0 +0 +6 +10 -1.5
202421 ASt. Lucie Mets 271238 33801 201169 41 .139.232.185.417 .046.256 437 .197 9 -28 +0 +0 +5 +8 -1.5
202522 A2 teams 290253 521113 238013 56 .206.304.292.597 .087.287 288 .270 65 -12 -1 +0 +5 +8 0.0
▸ 2026 Season (actual · ROS · total)
202623 A+Brooklyn Cyclones 3330 7000 2121 10 .233.303.233.536 .000.389 366 .237 40 -2 +0 +0 +1 +1 -0.1
ROS23 MLBNYM 248219 40813 19918 31 .183.272.269.542 .087.293 378 .251 50 -14 +0 +0 +4 +7 -0.2
TOT23 MLBNYM 281249 47813 211039 41 .189.276.265.541 .076.306 377 .250 49 -16 +0 +0 +5 +8 -0.3
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
202724 MLB 10%NYM 320281 551115 2610410 42 .196.287.295.582 .100.286 328 .268 64 -13 +0 +0 +6 +9 0.2
202825 MLB 25%NYM 381335 671317 3212011 52 .200.291.307.598 .107.287 318 .277 70 -13 +0 +0 +7 +11 0.5
202926 MLB 43%NYM 420369 751518 3613012 52 .203.295.314.609 .111.288 319 .281 74 -13 +0 +0 +8 +12 0.7
203027 MLB 58%NYM 437384 791619 3813512 52 .206.297.323.620 .117.289 319 .283 74 -13 +0 +0 +8 +12 0.8
203128 MLB 68%NYM 444390 801619 3913812 52 .205.297.321.618 .115.288 319 .281 74 -13 +0 -1 +8 +13 0.7
203229 MLB 77%NYM 441387 771518 3913912 52 .199.292.305.597 .106.287 329 .279 72 -14 +0 -1 +8 +12 0.5
203330 MLB 84%NYM 436383 761518 3813812 42 .198.291.305.596 .107.286 329 .276 70 -15 +0 -2 +8 +12 0.3
203431 MLBNYM 412362 711417 3613311 31 .196.289.298.587 .102.284 329 .272 67 -16 +0 -3 +7 +12 0.1
203532 MLBNYM 384337 651316 3412610 22 .193.286.291.577 .098.282 339 .268 63 -16 -0 -4 +7 +11 -0.2
203633 MLBNYM 346304 571115 301159 13 .188.280.280.559 .092.281 339 .263 59 -16 -1 -4 +6 +10 -0.5
203734 MLBNYM 296260 48914 261018 17 .185.279.273.552 .088.279 349 .256 54 -15 -3 -5 +5 +8 -0.9
▸ Career Totals (MLE all levels + projections)
Career 57115017 9511941691 4751912176 5438 .190.283.289.572 .099.282 338 .264 60 -258 -4 -20 +102 +162 -1.8
/ 162G 650571 10822210 5421820 64 .189.282.287.569 .098.282 348 .264 60 -29 -0 -2 +12 +18 -0.2

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
202118 ROKFCL Mets 6652 9201 10214 02 .173.348.269.618 .096.267 3215 .303 90 -1 -1 +2 0.0
202219 ASt. Lucie Mets 3531 4111 182 00 .129.206.323.528 .194.130 233 .230 34 -3 +0 +1 -0.2
202219 ROKFCL Mets 142120 34724 113210 10 .283.390.475.865 .192.353 238 .384 152 +8 +0 +4 1.3
202320 ASt. Lucie Mets 342297 671828 3210311 11 .226.324.380.704 .155.314 309 .318 101 +1 -0 +10 1.0
202421 ASt. Lucie Mets 271231 401001 27819 41 .173.285.229.514 .056.255 3010 .246 46 -16 +0 +8 -0.9
202522 A+Brooklyn Cyclones 6860 10200 5193 22 .167.265.200.465 .033.244 287 .228 33 -5 -0 +2 -0.4
202522 ASt. Lucie Mets 222185 48923 254210 34 .259.376.378.754 .119.319 1911 .345 122 +6 -1 +6 1.1

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
Vincent Perozo (OGILVIE) 23 45 30 40 45 .177/.266/.265 .089.283 33 37% 8% 49 -0.8
Micah Schilling
2006 · A
23 45 40 43→50 41 .212/.272/.300 .088.318 86 34% 7% 58 -1.2 .222/.298/.311 .089.308 69 27% 9% 72 -0.2 .226/.314/.313.087.30451124%10%77+0.1
Dan Gamache
2014 · A
23 46→52 39→40 42→45 41 .215/.269/.310 .096.309 56 31% 6% 59 -1.1 .237/.285/.342 .105.322 95 27% 6% 74 -0.1 .259/.303/.363.104.33010324%5%84+0.2
Alberto Mineo
2017 · A
23 43→50 38→40 45→30 41 .203/.260/.282 .079.304 64 33% 7% 48 -1.9 .223/.286/.301 .078.305 43 26% 7% 64 -0.8 .218/.285/.296.077.3034127%7%60-0.6
Anthony Seigler
2022 · A
23 41→39 41→45 44→55 45 .195/.271/.299 .104.290 86 34% 9% 58 -1.2 .192/.292/.304 .112.255 1014 26% 12% 69 -0.4 .200/.299/.321.122.247122723%12%74-0.1
Damon Dues
2022 · A
24 45 36→30 44→60 43 .207/.284/.273 .066.313 37 32% 8% 57 -1.2 .226/.316/.291 .065.330 222 28% 11% 75 -0.0 .237/.336/.296.060.33913727%13%80+0.1
Chris Mariscal
2016 · A
23 42→49 37→40 43→45 39 .198/.258/.266 .067.305 46 34% 7% 43 -2.2 .226/.284/.314 .088.332 66 31% 7% 66 -0.6 .231/.292/.323.092.3317530%7%70-0.3
Shane Matheny
2019 · A
23 37→42 39→45 41→50 35 .184/.237/.261 .077.294 85 39% 6% 33 -2.9 .183/.239/.277 .094.288 104 38% 6% 38 -2.6 .191/.281/.316.125.30014938%10%64-0.5
Dallas Tarleton
2011 · A
23 46 39→45 41→40 37 .201/.266/.284 .083.354 66 42% 8% 52 -1.6 .212/.278/.299 .087.333 75 35% 8% 60 -1.0 .221/.287/.312.091.3228232%8%65-0.3
Mitch Walding
2016 · A
23 41→45 38→50 39→40 40 .192/.254/.269 .077.303 54 36% 7% 43 -2.2 .202/.275/.330 .128.322 144 38% 8% 68 -0.5 .198/.281/.352.154.31019239%9%74-0.0
Cody Milligan
2022 · A
23 44→54 36→40 46→60 43 .200/.272/.265 .065.308 313 33% 8% 49 -1.8 .229/.296/.311 .082.322 420 28% 8% 71 -0.3 .233/.297/.326.093.32252827%8%72-0.1
Tim Susnara
2019 · A
23 42 40 43→40 43 .201/.268/.293 .091.291 75 32% 8% 55 -1.4 .179/.243/.261 .082.289 85 38% 8% 36 -2.7 .143/.216/.227.083.23410141%7%14-1.3
Chase Fontaine
2009 · A
23 47→49 38→40 41→45 47 .220/.288/.302 .082.304 56 28% 8% 65 -0.7 .228/.289/.319 .091.318 77 28% 8% 69 -0.4 .248/.306/.338.090.3467628%7%81+0.1
Nick Plummer
2019 · A
23 37→47 40→45 43→50 47 .175/.280/.268 .093.290 88 38% 11% 56 -1.3 .177/.279/.285 .108.305 108 41% 10% 59 -1.1 .182/.281/.306.123.298131039%9%63-0.5
Alex Perez
2016 · A
23 42 35→30 45→40 41 .195/.257/.259 .063.287 24 31% 7% 40 -2.4 .213/.285/.259 .046.301 13 26% 9% 53 -1.5 .215/.287/.249.034.3010226%9%49-1.1
Cole Lankford
2016 · A
23 42 41→40 46→40 35 .202/.248/.296 .094.303 85 35% 5% 46 -2.0 .230/.271/.295 .065.288 45 20% 4% 55 -1.4 .251/.286/.295.044.3012316%3%58-0.6
Oliver Dunn
2021 · A
23 43→47 40→50 43→55 42 .204/.267/.293 .089.301 79 33% 7% 54 -1.4 .205/.288/.344 .139.328 1413 38% 10% 77 +0.1 .207/.297/.363.156.316171637%11%83+0.3
Braulio Vasquez
2021 · A
22 40 39→40 44→65 37 .193/.250/.274 .080.298 77 36% 6% 42 -2.3 .205/.278/.298 .093.301 729 32% 7% 61 -1.0 .200/.277/.293.093.28774230%7%55-0.6
Sergio Burruel
2013 · A
22 44 35→30 44→30 45 .207/.272/.265 .059.284 24 27% 7% 49 -1.8 .226/.276/.294 .068.304 46 25% 6% 57 -1.2 .244/.307/.320.075.2988119%7%75+0.0
Bobby Haney
2012 · A
23 42 37→40 38→40 42 .201/.252/.270 .070.278 44 29% 6% 41 -2.3 .225/.271/.299 .074.306 45 26% 6% 56 -1.3 .235/.279/.305.070.3124425%5%59-0.6
Beau Taylor
2014 · AA
24 45→46 38→45 42→30 45 .215/.277/.291 .076.299 53 29% 8% 57 -1.2 .207/.273/.302 .095.298 93 31% 8% 59 -1.1 .215/.303/.325.110.30710131%11%76+0.0