Luis Santana2B West Michigan Whitecaps
Age 27 R/R 5'8" / 196 lbs A+ HR +5%H +3% Svc 0.0 · Ctrl thru 2035
wRC+†70
AVG/OBP/SLG.214 / .276 / .336
PA249
HR5
K%25
BB%6
MLB%0%
BAT: -8.3 runs (wOBA-derived runs vs avg)-8BATRUN: +0.5 runs (SB/CS + UBR baserunning)+0RUNFLD: +0.0 runs (Defensive runs vs avg)+0FLDPOS: +0.9 runs (Positional adjustment)+1POSREP: +7.1 runs (Replacement-level credit)+7REPTotal WAR: -0.00-0.0WAR
Scouting · nowfuture
HIT
4949
PWR
3838
SPD
4646
EYE
4040
trajectory · 10 yrs
0.1peak
2028

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
2031Arb-3$0.9M
2032Ext / FA-deal$0.9M
2033Ext / FA-deal$0.2M
2034Extbeyond projection horizon · no WAR estimate
2035Extbeyond projection horizon · no WAR estimate
Totals $-2M $-11M -$9M
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
201617 ROKDSL Mets 2 8276 17310 2104 02 .224.280.289.570 .066.258 122 .259 56 -4 -1 +0 +0 +2 -0.2
201718 ROKDSL Mets 2 287250 671062 213211 164 .268.351.380.731 .112.298 117 .316 100 +0 +2 +0 +1 +8 1.1
201819 ROKKingsport Mets 242214 611003 173310 83 .285.365.374.739 .089.324 147 .325 107 +2 +0 +0 +1 +7 1.0
201920 AACorpus Christi Hooks 6659 12200 4123 00 .203.288.237.525 .034.255 186 .234 37 -5 +0 +0 +0 +2 -0.3
202122 A+Asheville Tourists 190175 30604 8595 52 .171.229.274.503 .103.228 314 .220 27 -16 +0 +0 +1 +5 -1.0
202223 A+Asheville Tourists 396356 8316210 259813 114 .233.307.374.681 .140.292 256 .291 81 -9 +1 +0 +1 +11 0.5
202324 AA3 teams 354334 7314111 131015 41 .219.259.365.624 .147.278 294 .271 65 -14 +0 +0 +1 +10 -0.2
202425 A+3 teams 316284 49805 187110 41 .173.247.254.500 .081.208 226 .225 30 -25 +0 +0 +1 +9 -1.5
▸ 2026 Season
202627 MLBDET 249228 491015 15624 41 .215.275.333.609 .118.269 256 .277 70 -8 +0 +0 +1 +7 -0.0
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
202728 MLB 8%DET 260237 521016 17654 31 .219.283.346.629 .127.271 257 .281 73 -8 +0 -1 +1 +7 -0.0
202829 MLB 18%DET 303275 601217 20765 31 .218.283.345.629 .127.272 257 .282 74 -9 +0 -1 +1 +9 -0.0
202930 MLB 28%DET 330300 651317 22835 31 .217.281.337.618 .120.272 257 .281 73 -10 +0 -2 +1 +9 -0.1
203031 MLB 39%DET 335304 651317 23865 20 .214.280.332.612 .118.271 267 .278 71 -11 +0 -3 +1 +9 -0.3
203132 MLB 49%DET 328298 631217 22855 00 .211.277.329.606 .117.269 267 .274 68 -12 +0 -4 +1 +9 -0.5
203233 MLB 63%DET 306278 581116 21824 00 .209.274.320.594 .112.268 277 .268 63 -13 +0 -4 +1 +9 -0.7
203334 MLB 80%DET 268244 49915 18744 00 .201.267.307.574 .107.266 287 .262 59 -13 +0 -5 +1 +8 -0.9
▸ Career Totals (MLE all levels + projections)
Career 43123912 8531591885 266102997 6321 .218.284.333.618 .115.272 246 .275 69 -153 +4 -20 +15 +122 -3.2
/ 162G 650590 12924313 4015515 93 .219.286.336.621 .117.272 246 .275 69 -23 +1 -3 +2 +18 -0.5

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
201617 ROKDSL Mets 2 8275 22420 374 02 .293.354.400.754 .107.324 94 .340 118 +2 -1 +2 0.3
201718 ROKDSL Mets 2 287237 771283 342211 164 .325.433.481.914 .156.346 812 .402 165 +21 +2 +8 3.2
201819 ROKKingsport Mets 242204 711304 272310 83 .348.448.471.919 .123.376 1011 .414 175 +20 +0 +7 2.8
201920 AACorpus Christi Hooks 6657 13200 693 00 .228.333.263.596 .035.271 149 .287 77 -2 +0 +2 0.0
202122 A+Asheville Tourists 190170 391006 13435 52 .229.303.394.697 .165.268 237 .310 95 -1 +0 +5 0.5
202223 A+Asheville Tourists 396343 10223211 386913 114 .297.388.472.861 .175.343 1710 .382 151 +23 +1 +11 3.5
202324 AAErie SeaWolves 268252 6014112 12594 21 .238.284.444.728 .206.265 224 .320 103 +1 +0 +8 0.9
202324 A+West Michigan Whitecaps 5952 19201 6111 10 .365.441.462.902 .096.450 1910 .408 170 +5 +0 +2 0.7
202324 INTLGigantes del Cibao 2723 2001 230 10 .087.160.217.377 .130.050 117 .162 -18 -4 +0 +1 -0.3
202425 AAErie SeaWolves 11597 16500 11224 21 .165.277.216.493 .052.205 1910 .235 38 -8 +0 +3 -0.5
202425 A+West Michigan Whitecaps 184164 33305 13306 20 .201.284.311.595 .110.215 167 .274 68 -7 +0 +5 -0.1
202425 ALakeland Flying Tigers 1713 5101 420 00 .385.529.6921.222 .308.400 1224 .522 257 +3 +0 +0 0.4

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
Luis Santana (OGILVIE) 27 49 38 46 40 .214/.276/.336 .122.269 54 25% 6% 70 -0.1
Trey Harris
2023 · AA
27 45→51 42→45 43→45 40 .223/.277/.322 .100.285 118 25% 5% 66 -0.6 .208/.259/.288 .080.284 68 27% 5% 49 -1.8 .190/.236/.251.061.2662628%4%26-1.7
Gavin Cecchini
2021 · AAA
27 45→55 43→45 48→45 43 .225/.271/.335 .110.276 1110 23% 6% 66 -0.6 .218/.250/.309 .091.274 811 23% 4% 50 -1.8 .213/.237/.287.074.2666922%3%36-1.6
Julian Laurean
2011 · AAA
27 45 45→40 44→40 41 .224/.277/.347 .122.291 129 27% 6% 72 -0.2 .226/.281/.334 .108.280 97 22% 6% 71 -0.3 .222/.281/.307.085.2695018%6%64-0.3
Sharlon Schoop
2014 · AA
27 43→44 45→40 46→45 43 .219/.272/.337 .119.277 138 26% 6% 68 -0.5 .212/.259/.296 .084.278 74 25% 6% 51 -1.7 .204/.257/.319.115.25912026%6%52-0.5
Chuckie Robinson
2022 · AA
27 40→50 45 47→45 40 .204/.266/.319 .115.281 138 31% 6% 61 -1.0 .228/.277/.351 .123.290 147 26% 5% 74 -0.1 .227/.276/.326.099.30112427%5%64-0.4
Jake Kahaulelio
2012 · AA
27 43→44 43→45 45 44 .211/.272/.325 .114.259 117 23% 6% 66 -0.6 .212/.287/.313 .101.256 811 20% 7% 69 -0.4 .196/.305/.245.049.23102313%9%59-0.2
C.J. Hinojosa
2021 · AA
27 48→54 41→45 42→45 46 .233/.278/.333 .100.270 97 17% 6% 69 -0.4 .239/.278/.364 .125.291 127 22% 5% 77 +0.1 .233/.273/.355.122.28112721%5%70-0.3
Devin Ivany
2009 · AA
27 45→48 43→50 47→45 40 .225/.266/.334 .109.281 119 24% 4% 64 -0.8 .222/.276/.351 .129.287 149 27% 6% 73 -0.1 .213/.270/.335.122.27513826%7%65-0.3
Adam Pavkovich
2009 · AAA
27 42→46 47→45 43→45 43 .215/.268/.349 .134.268 149 26% 6% 69 -0.4 .210/.254/.324 .114.259 1210 23% 5% 56 -1.3 .193/.232/.278.085.2348921%5%31-2.2
Arturo Rodriguez
2019 · AAA
27 45→41 43→45 46→30 43 .223/.266/.329 .107.272 125 23% 5% 63 -0.9 .258/.294/.402 .144.289 196 18% 4% 94 +1.3 .282/.311/.427.146.30523216%3%103+1.0
Jaime Pedroza
2014 · AA
27 46→52 42→45 46→50 43 .224/.279/.329 .104.292 108 26% 6% 69 -0.4 .232/.279/.347 .115.294 108 24% 5% 72 -0.2 .248/.314/.372.124.323121025%7%97+0.6
Alberth Martinez
2017 · AA
26 47→49 44→50 43→45 43 .232/.278/.346 .114.280 126 22% 5% 72 -0.2 .216/.261/.338 .122.272 128 25% 5% 63 -0.8 .205/.247/.332.127.25413625%4%53-1.1
Cody Clark
2009 · AA
27 43 42→45 47→40 41 .214/.262/.317 .103.260 106 22% 4% 59 -1.1 .222/.270/.348 .126.258 145 20% 5% 70 -0.3 .219/.268/.341.122.25112118%5%64-0.3
Sergio Garcia
2006 · AA
26 45→51 41→45 45 45 .220/.280/.316 .096.270 106 22% 6% 66 -0.6 .237/.295/.342 .105.274 108 17% 7% 79 +0.3 .245/.303/.348.103.2779815%7%81+0.2
Davis Stoneburner
2012 · AA
27 47→48 44→45 51→50 42 .230/.284/.355 .125.290 1113 24% 5% 77 +0.1 .206/.262/.297 .091.279 615 27% 6% 53 -1.5 .168/.224/.225.057.24101728%5%15-2.4
Tyler Ladendorf
2015 · AAA
27 45→49 42→40 47→50 46 .218/.280/.320 .102.273 96 23% 7% 67 -0.5 .214/.264/.297 .083.280 67 24% 6% 53 -1.5 .199/.257/.293.094.2519423%6%47-0.6
Nate Samson
2015 · AAA
27 47→57 43→40 47→45 45 .232/.284/.339 .107.280 1011 21% 6% 72 -0.2 .214/.267/.311 .097.255 812 19% 6% 59 -1.1 .186/.230/.232.047.21601113%5%17-1.1
Billy Fleming
2019 · AAA
26 47 45 45→40 43 .235/.279/.358 .123.281 125 21% 5% 76 +0.1 .228/.282/.345 .117.312 126 29% 6% 74 -0.1 .215/.277/.314.099.32611035%7%62-0.3
Dominic Miroglio
2022 · AA
27 41 44→45 44→40 43 .205/.269/.321 .117.279 115 30% 7% 63 -0.9 .216/.284/.361 .145.260 155 23% 8% 80 +0.4 .203/.270/.374.171.21220216%7%72-0.1
Jonathan Mota
2014 · AAA
27 46→48 46→45 45 41 .231/.272/.360 .129.283 145 24% 5% 73 -0.1 .216/.250/.308 .092.277 96 24% 4% 50 -1.8 .205/.231/.273.068.2616424%3%30-1.7