DataBaseball
2026

Head to head · Career pitching

Dan Haren vs Zack Wheeler

In 2014 Zack Wheeler has been worth 1.2 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.

Career

Totalled over the seasons published here, which is not the same as a whole career: a player who debuted before 2005 begins at 2005, not at his real first game.

Career pitching totals. ERA, WHIP and the per-nine rates are recomputed from the components rather than averaged; FIP needs each season’s own constant and is left to the season table.
StatisticDan HarenZack Wheeler
G363311
GS361311
IP2,301.01,890.1
W147127
L12180
SV10
SO1,9382,013
BB461537
ERA3.703.26
WHIP1.171.13
K/97.69.6
BB/91.82.6
HR/91.10.9
WAR36.841.3

2014 season

2014 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticDan HarenZack Wheeler
G3232
GS3232
IP186.0185.1
W1311
SO145187
ERA4.023.54
FIP4.093.55
WHIP1.181.33
K/97.09.1
BB/91.73.8
FIP−10995
WAR1.22.4

Postseason

Box-score figures only: October is kept out of the season constants, so there is no wOBA, FIP or dbWAR for it.

Every published postseason, pitching, summed with the rates recomputed from the counts.
StatisticDan HarenZack Wheeler
G213
GS211
IP11.074.1
W14
SV00
SO980
BB317
ERA4.092.30
WHIP1.730.77
K/97.49.7
BB/92.52.1

More head to heads

The same seasons, measured against somebody else.

How these are computed

FIP uses the constant solved from this season’s own runs, and FIP− is park-adjusted against the 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.