DataBaseball
2026

Head to head · Career pitching

Jacob deGrom vs Dan Haren

In 2015 Jacob deGrom has been worth 4.2 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.
StatisticJacob deGromDan Haren
G279363
GS279361
IP1,702.12,301.0
W107147
L76121
SV01
SO2,0521,938
BB391461
ERA2.733.70
WHIP1.001.17
K/910.87.6
BB/92.11.8
HR/90.91.1
WAR47.236.8

2015 season

2015 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticJacob deGromDan Haren
G3032
GS3032
IP191.0187.1
W1411
SO205132
ERA2.543.60
FIP2.704.61
WHIP0.981.13
K/99.76.3
BB/91.81.8
FIP−68116
WAR4.90.7

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.
StatisticJacob deGromDan Haren
G52
GS52
IP31.011.0
W41
SV00
SO379
BB103
ERA2.904.09
WHIP1.161.73
K/910.77.4
BB/92.92.5

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.