DataBaseball
2026

Head to head · Career pitching

Cliff Lee vs Adam Wainwright

In 2014 Adam Wainwright 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.
StatisticCliff LeeAdam Wainwright
G284478
GS280411
IP1,915.02,668.1
W126200
L79128
SV03
SO1,6132,202
BB355736
ERA3.353.53
WHIP1.171.24
K/97.67.4
BB/91.72.5
HR/90.90.8
WAR41.749.9

2014 season

2014 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticCliff LeeAdam Wainwright
G1332
GS1332
IP81.1227.0
W420
SO72179
ERA3.652.38
FIP2.962.88
WHIP1.381.03
K/98.07.1
BB/91.32.0
FIP−7977
WAR1.75.2

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.
StatisticCliff LeeAdam Wainwright
G1129
GS1116
IP82.0114.1
W74
SV04
SO89123
BB1022
ERA2.522.83
WHIP0.931.11
K/99.89.7
BB/91.11.7

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.