DataBaseball
2026

Head to head · Career pitching

Jake Peavy vs Chris Sale

In 2016 Chris Sale has been worth 3.5 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.
StatisticJake PeavyChris Sale
G312420
GS301339
IP1,918.12,246.2
W119159
L10297
SV012
SO1,7882,779
BB540518
ERA3.662.95
WHIP1.171.04
K/98.411.1
BB/92.52.1
HR/90.90.9
WAR34.360.0

2016 season

2016 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticJake PeavyChris Sale
G3132
GS2132
IP118.2226.2
W517
SO102233
ERA5.543.34
FIP4.363.46
WHIP1.431.04
K/97.79.3
BB/92.71.8
FIP−10483
WAR1.04.5

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.
StatisticJake PeavyChris Sale
G913
GS99
IP38.146.2
W11
SV00
SO2166
BB1714
ERA7.985.79
WHIP1.831.33
K/94.912.7
BB/94.02.7

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.