Kobe Kato2B Columbus Clingstones
Age 27 L/R 5'11" / 170 lbs AA BB -5% Svc 0.0 · Ctrl thru 2034
wRC+†66
AVG/OBP/SLG.198 / .280 / .310
PA207
HR4
SB6
K%31
BB%9
MLB%2%
BAT: -8.0 runs (wOBA-derived runs vs avg)-8BATRUN: +0.6 runs (SB/CS + UBR baserunning)+1RUNFLD: +0.0 runs (Defensive runs vs avg)+0FLDPOS: +0.7 runs (Positional adjustment)+1POSREP: +5.9 runs (Replacement-level credit)+6REPTotal WAR: -0.10-0.1WAR
Scouting · nowfuture
HIT
2525
PWR
4040
SPD
6060
EYE
5560
trajectory · 10 yrs
0.0peak
2027

Contract

ESTIMATED  ·  service-time + WAR-based estimator (needs verification)
Status   MiLB
MLB Debut   2029
Service   0 yrs (est)
Team Control Through   2034
First FA Year   2035
YearStatusSalary Proj WAR Value Surplus
2026MiLBstill in minors · estimated debut 2029
2027MiLBstill in minors · estimated debut 2029
2028MiLBstill in minors · estimated debut 2029
2029Arb-1$0.8M
2030Arb-2$0.9M
2031Arb-3$0.9M
2032Ext / FA-deal$0.2M
2033Ext / FA-deal$0.4M
2034Extbeyond projection horizon · no WAR estimate
Totals $-4M $-13M -$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
202122 AFayetteville Woodpeckers 11699 20201 16221 33 .202.319.253.571 .051.250 1914 .275 69 -4 -1 +0 +0 +3 -0.1
202324 A+2 teams 323290 611601 29734 225 .210.291.276.567 .066.278 239 .258 56 -16 +2 +0 +1 +9 -0.3
202425 AAA3 teams 135119 27511 12443 84 .227.313.311.624 .084.347 339 .287 78 -3 +0 +0 +0 +4 0.1
202526 AAColumbus Clingstones 194171 25704 20772 154 .146.244.257.501 .111.231 4010 .223 29 -16 +1 +0 +1 +5 -0.8
▸ 2026 Season
202627 MLBATL 207184 37814 19642 62 .201.283.321.604 .120.281 319 .271 66 -8 +0 +0 +1 +6 -0.1
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
202728 MLB 9%ATL 271241 491115 25823 82 .203.286.320.606 .116.282 309 .275 69 -10 +1 -1 +1 +8 -0.1
202829 MLB 19%ATL 306272 561216 28923 82 .206.287.324.611 .118.282 309 .277 70 -10 +1 -1 +1 +9 -0.1
202930 MLB 29%ATL 330293 601316 30994 82 .205.287.317.605 .113.281 309 .276 69 -11 +1 -2 +1 +9 -0.2
203031 MLB 43%ATL 323288 581216 29983 71 .201.281.312.594 .111.280 309 .274 68 -12 +1 -3 +1 +9 -0.3
203132 MLB 57%ATL 309275 551215 28953 61 .200.281.305.587 .105.279 319 .269 64 -13 +1 -4 +1 +9 -0.6
203233 MLB 74%ATL 283252 491015 26893 50 .194.278.302.579 .107.277 319 .264 60 -13 +1 -4 +1 +8 -0.7
203334 MLB 92%ATL 242216 42914 22782 40 .194.275.301.576 .106.275 329 .257 55 -12 +1 -5 +1 +7 -0.9
▸ Career Totals (MLE all levels + projections)
Career 30392700 539117948 28491333 10026 .200.284.303.587 .103.280 309 .267 63 -128 +10 -20 +11 +86 -4.2
/ 162G 650577 11525210 611957 216 .199.284.302.585 .102.280 309 .267 63 -27 +2 -4 +2 +18 -0.9

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
202122 AFayetteville Woodpeckers 11691 22302 24161 33 .242.405.341.746 .099.274 1421 .352 128 +4 -1 +3 0.6
202324 A+Asheville Tourists 303258 601902 42543 194 .233.347.329.676 .097.287 1814 .315 99 -0 +2 +9 1.1
202324 AFayetteville Woodpeckers 2012 8200 701 31 .667.800.8331.633 .167.667 035 .681 379 +6 +0 +1 0.7
202425 AAATacoma Rainiers 6959 21610 8151 61 .356.441.492.933 .136.467 2212 .410 172 +6 +1 +2 0.9
202425 AAArkansas Travelers 3228 2000 3141 11 .071.188.071.259 .000.143 449 .145 -31 -5 -0 +1 -0.4
202425 ROKACL Mariners 3426 9101 751 12 .346.500.5001.000 .154.400 1521 .451 203 +4 -1 +1 0.4
202526 AAColumbus Clingstones 194161 29804 30602 154 .180.316.304.620 .124.255 3115 .291 81 -4 +1 +5 0.3

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
Kobe Kato (OGILVIE) 27 25 40 60 60 .198/.280/.310 .112.281 46 31% 9% 66 -0.2
Michael Gigliotti
2023 · AA
27 42 46→40 57→55 48 .206/.304/.336 .130.293 1425 32% 10% 82 +0.5 .214/.310/.321 .107.288 917 26% 10% 81 +0.4 .206/.316/.294.088.27051323%12%76+0.0
JJ Muno
2022 · AA
28 39 43→40 53→60 39 .192/.276/.299 .108.280 1120 33% 6% 62 -0.9 .204/.287/.299 .095.295 927 32% 7% 66 -0.6 .192/.283/.264.072.28063931%7%53-0.9
Connor Hoover
2023 · AA
27 34→30 47→50 50 44 .181/.258/.318 .137.259 1513 35% 9% 58 -1.2 .189/.267/.321 .132.273 1612 35% 9% 63 -0.9 .160/.249/.296.136.218191236%9%46-1.0
Nolan Fontana
2019 · MLB
28 40→43 42→40 51→50 49 .195/.279/.303 .108.267 912 29% 10% 63 -0.9 .201/.288/.323 .122.291 1210 32% 10% 72 -0.2 .122/.235/.206.084.19110038%11%20-0.8
Jacob Hannemann
2018 · MLB
27 41→43 43→45 57→60 40 .204/.256/.319 .115.274 925 29% 5% 56 -1.3 .201/.252/.307 .106.262 1025 26% 5% 51 -1.7 .188/.238/.281.093.238102825%5%35-1.3
Willie Argo
2017 · AA
27 42→36 39→40 52→55 47 .200/.282/.280 .080.283 719 30% 9% 58 -1.2 .197/.253/.328 .131.305 1415 38% 6% 58 -1.2 .160/.218/.290.130.244151740%6%33-1.5
Logan Warmoth
2023 · AAA
27 42→39 43→45 51→55 41 .202/.279/.316 .113.314 1119 37% 8% 66 -0.6 .197/.275/.297 .100.290 1022 33% 8% 59 -1.1 .177/.264/.256.079.25882532%9%44-1.3
Adam Greenberg
2008 · AAA
27 46→47 41→45 54→55 49 .217/.296/.326 .109.295 616 27% 9% 75 -0.0 .225/.295/.323 .098.300 718 25% 8% 73 -0.1 .233/.300/.296.064.30842424%7%64-0.4
Blake Tekotte
2014 · MLB
27 40→46 46→50 50→55 41 .204/.262/.336 .132.274 1320 30% 6% 63 -0.8 .203/.261/.323 .120.276 1110 29% 6% 60 -1.0 .193/.255/.309.116.26212430%6%50-0.7
Mark Contreras
2022 · AAA
27 38 49→50 50→55 37 .194/.258/.343 .149.284 1615 36% 6% 65 -0.7 .203/.264/.339 .136.292 1623 35% 6% 66 -0.6 .192/.256/.306.115.275143034%6%50-1.2
Cory Vaughn
2015 · AAA
26 38→40 45 54→50 42 .196/.270/.318 .122.273 1315 32% 7% 63 -0.8 .193/.258/.302 .109.284 1112 34% 7% 53 -1.5 .153/.220/.254.100.2339936%7%22-1.3
Jason Smith
2004 · MLB
27 46→35 48→55 56→50 42 .230/.284/.372 .142.308 1515 30% 7% 82 +0.5 .225/.268/.379 .154.286 1612 26% 5% 77 +0.1 .219/.261/.374.154.284151328%5%69-0.2
Dave Krynzel
2009 · AAA
27 41→46 43→45 53→55 40 .204/.262/.315 .111.290 1120 32% 6% 58 -1.2 .223/.269/.328 .105.322 1118 32% 5% 63 -0.8 .219/.264/.310.092.31992033%5%53-1.1
Jeff Duncan
2006 · MLB
27 44→46 42→45 53→60 46 .216/.282/.320 .104.285 915 26% 8% 67 -0.5 .233/.299/.323 .090.303 821 24% 7% 76 +0.0 .238/.309/.298.060.30862823%7%70-0.1
Mitch Longo
2022 · AAA
27 46→45 48→45 58→50 41 .230/.279/.372 .142.295 1520 27% 6% 79 +0.3 .224/.271/.370 .146.295 1715 29% 5% 76 +0.1 .186/.224/.319.133.23618330%4%38-0.6
Will Toffey
2022 · AAA
27 43 45 51→50 43 .198/.289/.321 .123.332 1311 41% 10% 72 -0.2 .208/.285/.343 .135.343 1312 40% 8% 76 +0.0 .199/.277/.341.142.322111238%8%68-0.3
Joseph Rosa
2023 · AAA
26 44→43 44→40 55→50 41 .215/.277/.335 .120.309 1119 33% 7% 69 -0.4 .216/.295/.313 .097.331 715 34% 9% 72 -0.2 .207/.298/.290.083.32761734%10%66-0.3
Ryan Aguilar
2022 · AA
27 38→41 43→45 50 41 .181/.265/.280 .099.307 1112 42% 9% 52 -1.6 .204/.296/.339 .135.334 1513 39% 10% 80 +0.4 .217/.319/.382.165.335191337%12%95+0.9
Clay Dungan
2023 · AAA
27 43→51 42→45 53→55 45 .211/.271/.315 .103.257 1019 22% 6% 62 -0.9 .213/.286/.318 .105.287 821 27% 8% 69 -0.4 .212/.293/.322.110.29982429%9%71-0.2
Evan Marzilli
2018 · AAA
27 44→45 38→40 50 48 .206/.284/.291 .085.292 515 29% 9% 61 -1.0 .198/.275/.289 .091.308 712 35% 9% 57 -1.2 .169/.248/.241.072.27141036%9%30-1.0