DataBaseball
2026

Head to head · Career pitching

Jacob deGrom vs Cliff Lee

In 2014 Jacob deGrom has been worth 1.6 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.
StatisticJacob deGromCliff Lee
G279284
GS279280
IP1,702.11,915.0
W107126
L7679
SV00
SO2,0521,613
BB391355
ERA2.733.35
WHIP1.001.17
K/910.87.6
BB/92.11.7
HR/90.90.9
WAR47.241.7

2014 season

2014 pitching. The stronger figure in each row is highlighted — for ERA, FIP, WHIP and walks that is the lower one.
StatisticJacob deGromCliff Lee
G2213
GS2213
IP140.181.1
W94
SO14472
ERA2.693.65
FIP2.672.96
WHIP1.141.38
K/99.28.0
BB/92.81.3
FIP−7179
WAR3.31.7

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.
StatisticJacob deGromCliff Lee
G511
GS511
IP31.082.0
W47
SV00
SO3789
BB1010
ERA2.902.52
WHIP1.160.93
K/910.79.8
BB/92.91.1

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.