DataBaseball
2026

Head to head · Career pitching

John Lackey vs Cliff Lee

In 2014 John Lackey has been worth 0.6 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.
StatisticJohn LackeyCliff Lee
G364284
GS363280
IP2,329.21,915.0
W155126
L11479
SV00
SO1,9301,613
BB656355
ERA3.813.35
WHIP1.271.17
K/97.57.6
BB/92.51.7
HR/91.00.9
WAR35.141.7

2014 season

2014 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticJohn LackeyCliff Lee
G3113
GS3113
IP198.081.1
W144
SO16472
ERA3.823.65
FIP3.782.96
WHIP1.281.38
K/97.58.0
BB/92.11.3
FIP−10179
WAR2.31.7

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.
StatisticJohn LackeyCliff Lee
G2411
GS2011
IP121.282.0
W67
SV00
SO9789
BB4110
ERA3.622.52
WHIP1.270.93
K/97.29.8
BB/93.01.1

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.