DataBaseball
2026

Head to head · Career pitching

Jake Peavy vs Zack Wheeler

In 2014 Zack Wheeler has been worth 0.9 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 PeavyZack Wheeler
G312311
GS301311
IP1,918.11,890.1
W119127
L10280
SV00
SO1,7882,013
BB540537
ERA3.663.26
WHIP1.171.13
K/98.49.6
BB/92.52.6
HR/90.90.9
WAR34.341.3

2014 season

2014 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticJake PeavyZack Wheeler
G3232
GS3232
IP202.2185.1
W711
SO158187
ERA3.733.54
FIP4.113.55
WHIP1.281.33
K/97.09.1
BB/92.83.8
FIP−11095
WAR1.52.4

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.
StatisticJake PeavyZack Wheeler
G913
GS911
IP38.174.1
W14
SV00
SO2180
BB1717
ERA7.982.30
WHIP1.830.77
K/94.99.7
BB/94.02.1

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.