Taken as a group, ground-ball pitchers are fascinating, in that they can succeed at the major league level with what might be seen as relatively average stuff. The group doesn’t miss many bats, but they do tend to have the benefit of both command and control, hovering around the strike zone in order to pitch to contact, and preventing balls from being hit in the air. Ground-ball rates themselves are stable and immune to large fluctuations; take any five-year span and run an intraclass correlation-testing the year-to-year stability on the individual pitcher level-and it will likely show a strong relationship somewhere in the 0.55-0.70 range. When a large fluctuation does surface, due diligence would require asking if a change in approach or skill has been observed, instead of a knee-jerk reaction that might dismiss the statistical shift as a luck-based indicator that is bound to regress.
All of which brings us to Cliff Lee, the reigning AL Cy Young Award winner, who experienced a large jump in his ground-ball rate last season, almost doubling his career GB:FB ratio to that point. There were plenty of cynical analysts on the web who fell prey to confirmation biases last year, performing exploratory statistical surgery in an attempt to diffuse the mainstream obsession with Lee’s success. When some of the telltale signs of luck normalized, such as his BABIP and strand rate, and Lee sustained his minuscule walk rate and newly increased ground-ball rate, it became less reasonable to disagree with the consensus that Lee was just flat-out dominant. When the season came to an end and Lee became the second straight Cleveland hurler to take home the Cy Young, questions arose once more, this time pertaining to whether or not Lee could build upon, or sustain, his incredible 2008 season.
When Marc Normandin, Kevin Goldstein, and I penned our Player Profile on Lee last year, we combined the quantified performance aspects with scouting information, concluding that Lee had altered his approach and was also pitching with more confidence than ever before. One of the major causes for his progress in both of these areas was his improved mechanics, as the team spent time getting the lanky lefty to repeat his release point consistently on each pitch. Nobody really expects Lee to repeat his lofty 2008 performance, but his ability to sustain even a fraction of his production from last season will hinge on whether or not the spiked GB:FB rate is random, or the result of a documented change in approach. While Lee himself will need to pitch another couple of seasons before this question can be completely answered, we can investigate how others with similarly large spikes fared in the seasons following their higher ground-ball rates; the information can at least provide some cursory insight into what might be expected.
Coding for balls in play is a bit problematic in the sense that different systems score plays in different fashions. I use a Retrosheet database for studies like this, which potentially carries different data than those from Baseball Info Solutions. For that very reason, the specific ground-ball rates will not be mentioned here and a bit more leeway will be given to the spikes and year-to-year differences. Once the ball-in-play rates were calculated, I queried the database for situations in which a pitcher experienced a ground-ball rate increase of at least 8% between two seasons while facing 500+ batters in the initial year as well as the year of the spike. To clarify, increases in percentages can be confusing depending on whether or not subtraction or division is used to make the calculations. The subtraction method is much more common so when referring to an 8% increase, an example would be a pitcher seeing his rate rise from 45% to 53%, even though this rate-change would actually constitute an 18% increase. Of the 86 pitchers since 1954 that met this criteria, the next step involved comparing their ground-ball rates over the next several seasons to the year of the spike; essentially, if a pitcher jumped from 45% to 57%, were the rates in the following seasons close to 57%?
Comparing the future years to the year of the spike is more accurate than looping the subtraction to occur each year, since our examples could then consistently drop off by a slim margin to the point that the ground-ball rate four years later would actually be lower than the year before the spike. Keeping with the theme of a minimum of 500 batters faced, I decided to set the low-end rate discrepancy to -0.03, so that the pitcher could fall no lower than 54 percent in any of the next few seasons. This made it easier to separate the flukes from those who had legitimately developed some new skill.
The size of the pitcher pool that met the above criteria and sustained the increased rates really depends on how many years are of interest. For instance, looking at the two years following the spike produces a list of 26 pitchers, or 30 percent of the total group. If the third year is added, the number of pitchers drops to 18, or 21 percent of the group, and the addition of a fourth year offers a total of 15 pitchers, or just 17 percent of the overall group. Under one-fifth of the pitchers who experienced a sharp spike in their ground-ball rate similar to that of Lee’s were able to sustain their increase in each of the next four seasons. The most recent pitcher to accomplish this feat was Johan Santana, who became much more of a ground-ball pitcher in his breakout 2004 season, and has since held steady in the category. Only three other members of that 17 percent had increased their rate in the post-strike era: Andy Benes and Andy Pettitte from 1995 to 1996, and Brad Radke from 1996 to 1997. Keep in mind that one of the qualifiers here is the minimum of 500 batters faced in each of these seasons, so pitchers who had fought through injuries and missed significant time are lost, such as A.J. Burnett and Chris Carpenter, both of whom would have otherwise been included.
What happens if the -0.03 minimum drop-off is changed to -0.04? In this scenario, the pools of 15, 18, and 26 pitchers increase to 19, 23, and 28 respectively. Interestingly, even with a few added pitchers, only one more name-Scott Erickson from 1994 to 1995-surfaces in the recent past. All of this information suggests that these vast increases in the rates are quite rare, and a very low percentage of these pitchers are actually able to sustain the higher ground-ball rates over any significant period of time. If we want to get really nutty and create a pool including only pitchers who faced 500-plus batters for the four years after the spike and then either increased their ground-ball rate in each successive season or remained stagnant, the discussion will be limited to Gaylord Perry, Frank Viola, Andy Pettitte, Brad Radke, Kevin Gross, and Steve Trout.
The odds certainly don’t seem to be on Lee’s side, but the sample of pitchers with large spikes in this category is extremely small relative to the number of pitchers who have toed the rubber over the last 50 years. It’s possible that he could sustain his improvement and prove that the spike was due to his change in approach, but there just haven’t been many pitchers over the course of baseball history that have been able to accomplish this.
There are also relationships with several other statistics that make ground-ball pitchers intriguing. For instance, common logic might suggest that they would produce higher HR/FB rates, because the fly balls that they allow generally occur on mistake pitches. David Gassko, J.C. Bradbury, and Matthew Carruth of The Hardball Times have looked into this, and they actually proved the opposite: that a higher GB:FB rate goes hand in hand with a lower HR/FB rate. Despite an ability to keep the ball in the yard, Gassko further proved that those with high ground-ball rates tend to have a much higher percentage of line drives per fly ball, as well as more unearned runs, and as a result earned run averages can overstate the contribution of such hurlers. Ground-ball pitchers also rely on the defense to convert balls in play into outs, so there are several factors that could affect Lee’s performance line even if he maintains his GB:FB rate.
Lee had a remarkably low HR/FB rate last season that seemed to demand some sort of regression, but if he can sustain a high ground-ball rate, that regression might be minimal. He had a poor first start this week, but nothing should be assumed from just one game. Even so, it will be interesting to track his progress throughout the season, as he will need to remain aggressive to be effective, even if the effectiveness proves to be but a shell of last season’s success.