DataBaseball
2026

Head to head · Career pitching

Dan Haren vs Chris Sale

In 2015 Chris Sale has been worth 4.7 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 HarenChris Sale
G363420
GS361339
IP2,301.02,246.2
W147159
L12197
SV112
SO1,9382,779
BB461518
ERA3.702.95
WHIP1.171.04
K/97.611.1
BB/91.82.1
HR/91.10.9
WAR36.860.0

2015 season

2015 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticDan HarenChris Sale
G3231
GS3231
IP187.1208.2
W1113
SO132274
ERA3.603.41
FIP4.612.73
WHIP1.131.09
K/96.311.8
BB/91.81.8
FIP−11669
WAR0.75.4

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 HarenChris Sale
G213
GS29
IP11.046.2
W11
SV00
SO966
BB314
ERA4.095.79
WHIP1.731.33
K/97.412.7
BB/92.52.7

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.