Armando LaoC DSL Tigers 1
Age 19 R/R 5'10" / 170 lbs ROK HR +5%H +3% Svc 0.0 · Ctrl thru 2037 peak 3.0 · 2033
wRC+†55
AVG/OBP/SLG.202 / .268 / .292
PA50
HR1
K%31
BB%7
MLB%0%
BAT: -2.6 runs (wOBA-derived runs vs avg)-3BATRUN: +0.1 runs (SB/CS + UBR baserunning)+0RUNFLD: +0.0 runs (Defensive runs vs avg)+0FLDPOS: +0.9 runs (Positional adjustment)+1POSREP: +1.4 runs (Replacement-level credit)+1REPTotal WAR: -0.00-0.0WAR
trajectory · 10 yrs
3.0peak
2033

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+2.9$28M+$27M
2033Ext / FA-deal$1.0M+3.0$30M+$29M
2034Ext / FA-deal$1.0M+3.0$30M+$29M
2035Ext / FA-deal$6M+2.9$30M+$25M
2036Ext / FA-deal$9M+2.7$29M+$20M
2037Ext / FA-deal$12M+2.5$28M+$16M
Totals $29M $175M +$145M

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
202417 ROKDSL Tigers 1 7360 6100 5337 31 .100.250.117.367 .017.222 457 .167 -14 -9 +0 +0 +1 +2 -0.6
202518 ROKDSL Tigers 1 4035 8000 3101 11 .229.308.229.536 .000.308 258 .236 39 -3 -0 +0 +1 +1 -0.1
▸ 2026 Season
202619 MLBDET 5045 10201 4151 10 .222.300.333.633 .111.290 308 .257 55 -3 +0 +0 +1 +1 -0.0
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
202720 MLB 11%DET 140126 28513 11412 31 .222.295.349.644 .127.298 298 .286 77 -4 +0 +0 +3 +4 0.3
202821 MLB 28%DET 285254 581027 25804 61 .228.307.366.674 .138.299 289 .299 87 -4 +1 +0 +5 +8 1.0
202922 MLB 48%DET 394350 8114310 361075 92 .231.312.374.686 .143.300 279 .308 94 -3 +1 +0 +7 +11 1.7
203023 MLB 65%DET 468415 9616313 441256 112 .231.314.378.692 .147.300 279 .315 99 -0 +1 +0 +8 +13 2.3
203124 MLB 82%DET 516454 10718315 501367 122 .236.321.388.709 .152.301 2610 .320 103 +2 +2 +0 +9 +15 2.8
203225 MLBDET 520457 11018416 511367 132 .241.326.403.729 .162.301 2610 .323 105 +3 +2 +0 +9 +15 2.9
203326 MLBDET 520456 10818316 521367 122 .237.324.395.719 .158.302 2610 .324 106 +4 +2 +0 +9 +15 3.0
203427 MLBDET 520455 10818316 531377 122 .237.326.396.722 .158.302 2610 .324 106 +4 +2 +0 +9 +15 3.0
203528 MLBDET 520455 10818316 531387 112 .237.326.396.722 .158.301 2710 .323 106 +3 +1 -1 +9 +15 2.9
203629 MLBDET 520455 10818316 531397 101 .237.326.396.722 .158.301 2710 .321 104 +2 +2 -1 +9 +15 2.7
203730 MLBDET 520455 10618315 531417 91 .233.322.385.707 .152.299 2710 .318 102 +1 +1 -2 +9 +15 2.5
203831 MLBDET 504441 10217315 521396 70 .231.321.385.706 .154.298 2810 .314 99 -1 +1 -3 +9 +14 2.2
203932 MLBDET 487428 9816314 501366 40 .229.318.379.697 .150.296 2810 .310 95 -3 +1 -4 +9 +14 1.7
204033 MLBDET 445392 8714312 451285 20 .222.310.365.675 .143.295 2910 .304 91 -5 +0 -4 +8 +13 1.2
204134 MLBDET 389342 7412210 391155 10 .216.306.351.657 .135.293 3010 .298 86 -6 +0 -5 +7 +11 0.7
204235 MLBDET 330290 621028 331014 00 .214.303.345.648 .131.291 3110 .290 80 -7 +0 -6 +6 +9 0.2
204336 MLBDET 269237 50826 27853 00 .211.300.338.637 .127.288 3210 .281 73 -8 +0 -6 +5 +8 -0.2
204437 MLBDET 209185 37614 20682 00 .200.285.308.593 .108.284 3310 .271 66 -8 +0 -7 +4 +6 -0.6
▸ Career Totals (MLE all levels + projections)
Career 77196787 155225747213 7592146106 12720 .229.316.375.690 .146.300 2810 .309 95 -45 +17 -38 +138 +219 29.7
/ 162G 650572 13122418 641819 112 .229.316.376.692 .147.301 2810 .309 95 -4 +1 -3 +12 +18 2.5

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
202417 ROKDSL Tigers 1 7357 8100 8237 31 .140.319.158.477 .018.235 3211 .251 51 -4 +0 +2 -0.2
202518 ROKDSL Tigers 1 4033 10000 571 11 .303.410.303.713 .000.370 1812 .332 112 +1 -0 +1 0.2

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
Armando Lao (OGILVIE) 19 .202/.268/.292 .090.290 11 31% 7% 55 -0.1
Tim Beckham
2009 · A
19 42→52 38→55 49→50 38 .202/.248/.282 .080.290 57 31% 5% 43 -2.2 .219/.267/.307 .088.310 510 29% 5% 57 -1.2 .248/.301/.421.173.31922428%6%100+1.3
Brendan Rodgers
2016 · A
19 43→53 40→50 46→45 39 .205/.255/.298 .093.301 77 33% 6% 50 -1.8 .224/.267/.352 .128.288 145 27% 4% 69 -0.4 .253/.308/.383.131.29813019%6%93+0.8
Andres Regnault
2018 · A
19 39 38→55 47→45 39 .185/.251/.256 .071.289 66 36% 7% 39 -2.5 .226/.287/.352 .126.291 137 26% 6% 79 +0.3 .248/.309/.417.169.29019621%6%103+0.7
Alex Liddi
2008 · A
19 41→51 41→60 47→50 36 .200/.246/.304 .104.297 87 34% 5% 48 -1.9 .229/.277/.361 .132.323 128 31% 6% 76 +0.1 .241/.296/.424.182.33620533%6%99+1.7
Wilin Rosario
2008 · A
19 39→49 37→60 45 35 .189/.235/.257 .068.297 66 37% 5% 31 -3.0 .219/.259/.344 .125.302 145 31% 5% 64 -0.8 .265/.302/.457.192.30126421%5%107+1.6
Pedro Severino
2012 · A
19 38→48 39→50 49→45 40 .187/.241/.272 .084.263 65 30% 6% 37 -2.6 .189/.233/.264 .075.239 53 22% 4% 31 -3.0 .246/.315/.384.137.30417324%8%95+0.7
Maikel Franco
2012 · A
19 36→46 38→55 48→40 37 .180/.226/.261 .081.253 64 30% 5% 28 -3.2 .239/.273/.382 .143.277 163 20% 4% 80 +0.4 .263/.299/.434.171.29019217%4%100+1.6
Amed Rosario
2015 · A
19 39→49 40→50 43→55 36 .196/.231/.287 .092.270 75 30% 4% 37 -2.7 .236/.274/.327 .091.314 412 25% 4% 64 -0.8 .286/.323/.422.136.344121420%5%107+1.7
Lane Thomas
2016 · A
20 43→51 37→55 51→55 42 .200/.259/.277 .077.294 39 32% 7% 46 -2.0 .194/.260/.302 .108.313 1013 38% 8% 54 -1.4 .248/.312/.427.179.308211325%7%107+2.0
Michael Chavis
2015 · A
19 44→47 38→60 48→45 39 .203/.258/.292 .090.318 48 36% 6% 50 -1.8 .193/.237/.327 .134.278 156 35% 4% 50 -1.7 .235/.292/.438.203.30429332%6%100+1.1
Yonathan Perlaza
2018 · A
19 40→50 37→60 48→50 37 .195/.235/.273 .078.279 412 31% 5% 34 -2.8 .213/.257/.285 .072.313 49 31% 6% 46 -2.0 .235/.307/.417.182.303191228%9%100+1.6
Luis Vázquez
2019 · A
19 40→46 36→50 49→45 39 .193/.237/.259 .066.276 38 30% 5% 32 -3.0 .202/.246/.272 .070.280 410 28% 5% 39 -2.5 .230/.295/.366.136.29817827%6%82+0.3
Michael Wing
2008 · A
19 44→53 37→55 51→40 37 .207/.253/.288 .081.305 46 32% 5% 46 -2.0 .220/.269/.322 .102.300 65 27% 6% 62 -0.9 .244/.285/.411.167.30419326%4%91+0.7
Jose Alvarez
2008 · A
19 41→51 38→60 49→50 38 .197/.247/.279 .082.270 58 28% 5% 42 -2.3 .198/.241/.288 .090.275 68 29% 3% 41 -2.3 .293/.324/.482.189.31826917%2%126+2.8
Gilberto Celestino
2018 · A
19 42→52 39→45 53→50 43 .202/.260/.288 .085.282 612 29% 7% 50 -1.8 .216/.267/.306 .090.280 711 24% 6% 57 -1.2 .239/.310/.323.084.31381424%9%75+0.0
Eguy Rosario
2019 · A
19 42→49 39→55 48→55 40 .202/.255/.294 .092.284 614 30% 6% 49 -1.8 .217/.266/.330 .113.302 915 30% 6% 63 -0.8 .223/.285/.369.146.292152128%7%80+0.2
José Fermín
2017 · A
18 43→51 38→45 48→55 44 .204/.260/.288 .084.278 48 27% 7% 50 -1.8 .202/.252/.277 .075.241 410 17% 5% 43 -2.2 .241/.336/.380.139.254142611%10%103+0.9
Jhonny Pereda
2014 · A
18 39→48 37→45 47→40 44 .190/.244/.262 .072.250 54 25% 6% 36 -2.7 .193/.250/.256 .063.231 43 17% 6% 37 -2.7 .276/.346/.381.105.3659025%9%105+0.9
Aaron Altherr
2010 · A
19 42→51 38→55 51→50 43 .201/.253/.279 .078.267 511 26% 6% 44 -2.1 .200/.241/.279 .079.282 616 30% 4% 38 -2.6 .244/.318/.420.176.303171424%8%104+1.5
Davis Schneider
2018 · A
19 40→44 41→55 48→50 50 .198/.276/.300 .102.259 86 26% 9% 60 -1.0 .193/.268/.290 .097.299 87 35% 8% 54 -1.4 .213/.322/.409.196.27524930%12%106+1.6