DataBaseball
2026

Head to head · 2026 batting

Tyler O'Neill vs Cal Raleigh

In 2026 Cal Raleigh has been worth 1.3 more wins. Both lines are computed from play-by-play on the same constants, so they are measured the same way rather than quoted from two sources.

2026 batting. The stronger figure in each row is highlighted — for strikeout rate that is the lower one.
StatisticTyler O'NeillCal Raleigh
G83126
PA260530
H4982
HR1023
RBI2369
SB12
AVG.212.182
OBP.300.296
SLG.377.368
OPS.677.664
ISO.165.186
BB%10.4%13.6%
K%27.7%30.9%
wOBA.304.299
wRC+9390
WAR0.21.5

Career

Totalled over the seasons published here, which is not the same as a whole career: a player who debuted before 2015 begins at 2015, not at his real first game.

Career batting totals. AVG and SLG are recomputed from the components rather than averaged; OBP, wOBA and wRC+ need each season’s own constants and are left to the table above.
StatisticTyler O'NeillCal Raleigh
G712744
PA2,5782,995
H547571
2B99110
3B42
HR128176
RBI327445
BB238338
SO773860
SB4923
AVG.239.218
SLG.454.464
WAR9.818.8

More head to heads

The same seasons, measured against somebody else.

How these are computed

wOBA uses linear weights measured from this season’s own play-by-play rather than published constants, and wRC+ is park-adjusted against that same league. dbWAR is our own open implementation — not fWAR or bWAR — and the full derivation, including its simplifications, is on the methodology page. To put these two beside a third, the comparison page takes up to four.