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In my preview of the American League Divisional Series between the Indians and Yankees, I noted that the Yankees’ Game One starter Chien-Ming Wang had shown a pronounced home-field advantage over the course of his short career, with a home ERA (3.04) more than 1.5 runs lower than his road ERA (4.62). With Wang pitching the series opener at Jacobs Field and then-assuming a four-man rotation and regular rest-on track to pitch a potential Game Five in Cleveland as well, it appeared Joe Torre had aligned his rotation to his disadvantage. That’s before we might consider the choice of gimpy Roger Clemens over able-bodied Philip Hughes to start Game Three, but let’s keep our attention on Game Four today.

Wang’s performance in Cleveland-4 2/3 innings, nine hits, eight runs, four walks-made my criticism look slightly prophetic, although Joe Sheehan wasn’t as convinced, suggesting the possibility that the split’s persistence over three years was just statistical noise given the limitations of sample size. One way or another, with Torre having deviated from the script to tab Wang to pitch Game Four on three days’ rest in Yankee Stadium tonight, those splits are worth a closer look. Here they are (courtesy of Baseball-Reference.com), broken down year by year:


Home     IP     ERA  BABIP    FIP   Diff.
2005    66.0   3.55   .260   4.20  -0.65
2006   118.2   3.03   .267   3.79  -0.76
2007   111.1   2.75   .262   3.63  -0.88
Total  296.0   3.04   .264   3.82  -0.78

Road     IP     ERA  BABIP    FIP   Diff.
2005    50.1   4.65   .276   4.25   0.40
2006    99.1   4.35   .322   4.11   0.24
2007    88.0   4.91   .336   3.63   1.28
Total  237.2   4.62   .318   3.96   0.66

First, a quick definition, because one of those terms might be new to you. FIP is Fielding Independent Pitching, a quick-and-dirty ERA estimator based on the Three True Outcomes (strikeouts, walks, and home runs) and created by Tangotiger. The formula is: FIP = [(13*HR + 3*BB – 2*K)/IP + 3.20].

Looking at the performance record, note the consistent disparity in innings pitched across the two splits. Overall, Wang has thrown 55 percent of his innings at home, suggesting that the Yanks may regard that setup as optimal. Second, while Wang’s home/road split has been consistent across all three years, the actual ERA disparity is much, much wider than suggested by his peripherals, as reflected via FIP; an apparent home-field advantage of 0.14 runs according to FIP turns into a 1.58 run advantage according to ERA. For those wise enough to pooh-pooh the earned/unearned run distinction, the spread is 1.82 runs per nine innings.

The difference appears to be largely due to the results of balls in play. Wang’s BABIPs at home have consistently been about 40 points below the league averages (.296, .305, and .308, respectively, over the last three years), enabling him to beat his FIP estimates by 0.78 runs. On the road, his BABIPs have been about 15 points above, with a much wider variation from year to year; collectively, his road ERAs have been 0.66 runs higher than his FIPs.

This discrepancy could be random, but it may not be. Along with the ballpark-to-ballpark variations in fence distances and the amount of foul territory, home/road differences may be a reflection of field preparation. It’s no secret that groundskeepers can prepare the field to the benefit of the home team’s starting pitcher. For any pitcher, that may include tailoring the mound to his liking. For a groundballer, that may include watering down the area in front of home plate and leaving the infield grass longer; likewise, for an opposing groundballer, the crew may opt to cut the grass short and keep the plate area dry and hard. The TBS broadcast of Game Two of the CubsDiamondbacks series showed the Arizona crew watering down home plate before the game even as the umpires looked on. Lou Piniella complained, prompting the umps to order the application of a drying compound, but the results were still reportedly damp. Still, there’s an element of tradition involved-such groundskeeping gamesmanship goes back to the 19th century, as teams even back then were watering down the basepaths to slow down their speedier opponents.

So, field preparation may be a factor for Wang. It’s also possible that mental aspects-the encouragement of a crowd, the discomfort of living out of a suitcase and sleeping in a hotel bed; who among us prefers those to the comforts of home?-may contribute to his split, at least more so than for the average ballplayer. Without his telling us that’s the case, we don’t know, but some effect seems to persist. Which raises many questions, among them whether or not Wang is unique in performing better at home than on the road. Does pitching at home favor groundballers more than flyballers?

To obtain a quick answer to this question, I asked BP data guru Bil Burke to provide me with the home/road splits of all pitchers who, like Wang, had thrown at least 50 innings at home and on the road in each of the last three seasons. Sixty-five pitchers meet those criteria. Here’s how they break down in terms of home and road performances (innings totals are rounded):


All     IP    H/9  HR/9  BB/9   K/9  BABIP  G/F   ERA   FIP   RA   %UER
home  19081  8.96  0.99  2.63  6.65  .281  1.74  3.95  4.03  4.27  8.11
road  18391  9.43  1.03  2.84  6.25  .287  1.74  4.33  4.25  4.73  9.14

While this is a sample of better-than-league-average pitchers, this shows a decided home-field advantage. In terms of ERA, it’s a 0.38 run difference, and in terms of RA, it’s 0.46. But in terms of what the peripherals suggest via FIP, the gap is only about half that, 0.22. At home, these pitchers outstrip their projections by 0.08 runs, and on the road they’re off by the same margin in the other direction. Certainly, these results can be affected by factors like tailoring staff construction to match the ballpark’s tendencies (say, flyballers in Petco, or groundballers on the mounds of US Cellular, Citizens Bank, and Coors), and also making sure to use that type of pitcher going on a given day in a given park.

If we split the pitchers into two camps, groundballers and flyballers, we see a few other differences manifest themselves. Before I present the data, it’s worth noting that our groundball and flyball data comes from MLB Advanced Media, and may vary from that of Stats, Inc. (as seen on ESPN) or Baseball Information Solutions (as seen at The Hardball Times). Judgment calls on popups versus flyballs, line drives versus flyballs, and line drives versus grounders may result in differing numbers in each category. For example, our data for Brandon Webb shows 1397 groundballs and 326 flyballs (a 4.28 ratio) over the last three years. Stats, Inc.’s data as reported on Webb’s ESPN card has 1349 and 348, a 3.88 ratio. Fellow extremists Derek Lowe (4.14 versus 3.41) and Wang himself (3.81 versus 2.90) show higher G/F ratios in the MBLAM data than in the Stats data. Given the parameters of this study, we’ll live with the discrepancy, knowing that the numbers you see here skew higher than those at ESPN.com.

Based on a median (and mean) of 1.65 in our groundball/flyball data within this sample of pitchers, here’s the breakdown:


All     IP    H/9  HR/9  BB/9   K/9  BABIP  G/F   ERA   FIP   RA   %UER
GB    20252  9.15  0.91  2.65  6.31  .286  2.12  4.00  3.99  4.37  9.26
FB    17220  9.23  1.13  2.83  6.62  .282  1.38  4.30  4.31  4.65  7.97

Though their collective BABIP is slightly higher, the groundballers show a better ERA, RA, and FIP by about three-tenths of a run, thanks to their ability to limit long balls. Given the choice between the two groups, these are the guys you want to invite to your party. Note the last column, which is the percentage of runs that are unearned; groundballers tend to generate more infield errors, resulting in more unearned runs.

Slicing and dicing into home/road splits for each category:


GB      IP    H/9  HR/9  BB/9   K/9  BABIP  G/F   ERA   FIP   RA   %UER                     
home  10394  8.93  0.88  2.57  6.49  .283  2.12  3.78  3.88  4.12  8.93
road   9858  9.39  0.94  2.74  6.12  .289  2.12  4.23  4.11  4.63  9.57
Home-field Advantage                             0.45  0.23  0.49

FB      IP    H/9  HR/9  BB/9   K/9  BABIP  G/F   ERA   FIP   RA   %UER
home   8687  8.99  1.13  2.70  6.83  .278  1.38  4.16  4.21  4.46  7.23
road   8533  9.47  1.13  2.96  6.40  .286  1.39  4.45  4.40  4.84  8.68
Home-field Advantage                             0.39  0.19  0.38

Groundballers maintain their advantages over flyballers across each split. Both groups show decisive home-field advantages, with the groundballers’ being slightly larger, but with the actual advantages wider than those predicted by FIP. The home-field advantage in on balls in play across both types of pitchers appears to account for about half of the discrepancy.

What this in-no-way-definitive study suggests is that a groundballer pitching at home-exactly like Wang in Yankee Stadium-would appear to be the best of the limited permutations available. Further research along these avenues is needed to clarify the matter, but at River Avenue and 161st Street in the Bronx on Thursday night, with the Yankees’ continued presence in the postseason and Joe Torre’s tenure in pinstripes riding on Wang’s performance, it will have to do.

Thank you for reading

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