DataBaseball
2026

Head to head · Career pitching

Zack Greinke vs Jake Peavy

In 2016 Zack Greinke 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.

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.
StatisticZack GreinkeJake Peavy
G562312
GS517301
IP3,244.11,918.1
W217119
L145102
SV10
SO2,8791,788
BB736540
ERA3.473.66
WHIP1.171.17
K/98.08.4
BB/92.02.5
HR/90.90.9
WAR64.734.3

2016 season

2016 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticZack GreinkeJake Peavy
G2631
GS2621
IP158.2118.2
W135
SO134102
ERA4.375.54
FIP4.124.36
WHIP1.271.43
K/97.67.7
BB/92.32.7
FIP−98104
WAR2.31.0

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.
StatisticZack GreinkeJake Peavy
G229
GS219
IP113.038.1
W41
SV00
SO10021
BB3317
ERA4.147.98
WHIP1.201.83
K/98.04.9
BB/92.64.0

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.