All Fly Balls Are Not Created Equal by Jeff Zimmerman February 6, 2014 When Juan Lagares took over in center, the fly ball outs started coming in bunches (via slgckgc). The longer a ball is in the air, the more time a fielder has to catch it. Sounds simple, doesn’t it? Sometimes, in this world of advanced fielding stats, we forget the simple things. While we’re busy measuring things like pitch velocity and deflection, or angle of the ball off the bat, or the exact zone a ball lands in, why not also talk about hang time? The first research on this subject was published in the 2004 Hardball Times Annual when Robert Dudek manually tracked the fly ball hang times of eight pitchers and tabulated the results. Nowadays, thanks to Inside Edge, the data are available on every batted ball that is in the air for at least 1.5 seconds. (This includes line drives, flies and pop-ups—but we’re going to use the generic term “fly ball.”) There is a lot we can do with this data. First, here is a comparison of Dudek’s original data with the Inside Edge 2013 data. The next table shows the percentage of the time a fly ball was caught for an out, broken out by how many seconds it was in the air. The data include all fair (not foul) fly balls (balls in the air at least 1.5 seconds) except for home runs. 2004 Dudek Data 2013 Inside Edge Data Hang Time # Out% # Out% 1.5 to 3.0 449 12.7% 15,952 19.5% 3.0 to 4.0 354 48.9% 11,749 58.3% 4.0 to 5.0 368 73.6% 14,719 71.3% 5.0 to 6.0 324 90.7% 16,717 84.7% 6.0 plus 138 97.1% 6,281 93.3% Despite some differences in the percentages, the pattern remains the same: the longer the air time, the more often the ball is caught. There’s something else we can examine…how often does a fly ball land for an extra-base hit (in this case, just doubles and triples)? Does this depend on hang time? Yes, it does. Balls that are in the air between 1.5 and 3 seconds land for an extra-base hit 15 percent of the time (think of line drives down the line or in the gap). If the ball is in the air three to four seconds, the percentage rises to 19 percent. After that, however, the odds of a fly ball landing for an extra-base hit decline the longer it is in the air. The data from this past season: Frequency of Fly balls Landing for Extra-Base Hits, 2013 Hang Time # XBH% 1.5 to 3.0 15,952 15.0% 3.0 to 4.0 11,749 18.6% 4.0 to 5.0 14,719 11.0% 5.0 to 6.0 16,717 2.3% 6.0 plus 6,281 0.8% The last figure amounts to essentially 50 extra-base hits on balls that stay in the air that long. We’re talking those high wall scrapers, or that random ball that gets lost in the lights/sun, or perhaps even those bloopers that land in that Bermuda Triangle between first-second-right or third-short-left. Those plays happened fewer than 10 times a month last season, so when you see one, know that it’s pretty random. Of course, where the ball is hit matters, too. For instance, a ball that is in the air for three to four seconds is fielded for an out… 44 percent of the time if the hit is shallow 75 percent of the time is the ball is hit a routine depth 55 percent of the time if the ball is hit slightly deep, and 21 percent of the time if the ball is hit very deep. These are somewhat arbitrary distinctions, of course, but I didn’t want you to think that I had forgotten how important location is. There are two essential components to every batted ball: how long it is in the air and where it lands. Most people pay a lot of attention to the latter, including Inside Edge — you can see its data in the fabulous new spray charts over at FanGraphs. Today though, we’re going to talk about the former — hang time. Let me slap some data on you: Fly Ball Count, 2013 Hang Time Infield Shallow Routine Slightly Deep Deep 1.5 to 3.0 2,349 20,732 6,926 1,438 128 3.0 to 4.0 676 6,073 7,859 7,264 1,536 4.0 to 5.0 2,104 5,444 6,472 8,580 6,982 5.0 to 6.0 5,660 7,250 6,502 7,254 6,912 6.0 plus 3,036 3,772 2,411 2,162 1,291 Fly Ball Out%, 2013 Hang Time Infield Shallow Routine Slightly Deep Deep 1.5 to 3.0 80.5% 8.2% 31.6% 26.0% 3.1% 3.0 to 4.0 95.8% 44.3% 74.8% 54.8% 21.5% 4.0 to 5.0 99.6% 83.1% 95.7% 75.6% 25.4% 5.0 to 6.0 99.7% 96.6% 99.2% 90.6% 37.9% 6.0 plus 99.3% 98.3% 99.2% 94.6% 49.0% Fly Ball XBH%, 2013 Hang Time Infield Shallow Routine Slightly Deep Deep 1.5 to 3.0 2.8% 11.1% 22.4% 51.9% 69.5% 3.0 to 4.0 1.1% 7.1% 12.5% 33.8% 36.6% 4.0 to 5.0 0.0% 3.2% 2.4% 15.7% 21.2% 5.0 to 6.0 0.0% 1.1% 0.4% 3.3% 6.0% 6.0 plus 0.1% 0.6% 0.4% 1.3% 2.1% To make some categorical observations about these data, I concentrated on two categories of batted balls: All batted balls (in the air for at least 1.5 seconds) Batted balls in the air between 2.5 and 4.0 seconds. If a ball is in the air 2.5 to 4.0 seconds, it is fielded for an out nearly 50 percent of the time. Also, if the ball is not caught, it is more likely than other fly balls to end up as an extra-base hit. Plays in this time range are the most critical for determining which teams make the most important run-preventing plays and which ones don’t. Hang Time Comparison, 2013 Hang Time Out% XBH% 2.5 to 4 49.8% 17.9% All 62.0% 10.0% Going forward, I’m going to call balls that hung in the air between 2.5 and 4.0 seconds “sharp fly balls.” It’s just easier that way. A Case Study During the first couple of months of 2013, the Mets primarily played Lucas Duda in left field, a series of players in center—including Rick Ankiel for a while—and Marlon Byrd in right. The Mets needed Duda’s bat in the lineup, but he was a liability in left. Ankiel was a decent center fielder but didn’t hit a lick and only Byrd managed to put together a solid year. In mid-June, Duda was placed on the disabled list, Ankiel was let go, and the Mets picked up Eric Young from the Rockies and handed the center field job to youngster Juan Lagares. Voila, new outfield defense. Young and Lagares did an excellent job covering ground with their speed and instincts and Byrd continued his solid play before being traded to the Pirates in August. In April and May, the Mets turned just 41 percent and 42 percent of sharp fly balls into outs, a number far below the major league 50 percent average. In June, as their personnel changed over, their out rate climbed to 50 percent. It was 47 percent in July, but then shot up to a remarkable 70 percent in August! Young and Lagares fielded everything batted their way, and I’m pretty sure the Mets’ pitchers took notice. Their percentage dipped back down to 55 percent in September, which was still the second-highest month for them. The outfield play should stay at a high level in 2014. Lagares and Eric Young will be joined by new additions Curtis Granderson and Chris Young, and even though Granderson’s best defensive days may be behind him, the additions should permanently move Duda to first base or the bench, and that can only be a good thing. Mets Fly Ball Percentages By Month, 2013 Type April May June July August Sept. All out% 60% 59% 61% 64% 65% 63% All XBH% 11% 10% 12% 9% 8% 10% Sharp fly ball Out% 42% 41% 50% 47% 70% 55% Sharp fly ball XBH% 15% 15% 23% 16% 11% 15% Ballparkin’ It Certain ballparks will affect the fielding values differently. Here is how each team did at home and on the road, and how the road team did at the home team’s park in 2013. The first table is looking at the out percentage and the second table is looking at the extra-base hit percentage for each team. (The major league average out percentage was 62 percent for all fly balls and 49.8 percent for sharp fly balls. The league average of extra-base hits is 10% for all fly balls and 17.9% for sharp fly balls.) Out%, by Team, Ballpark and Fly Ball Type, 2013 At home On the road Away team Team All Sharp Fly All Sharp Fly All Sharp Fly Angels 63.8% 48.6% 60.8% 48.4% 62.1% 48.9% Astros 60.3% 46.8% 61.6% 49.2% 59.7% 45.9% Athletics 66.9% 53.3% 65.6% 49.4% 65.2% 46.0% Blue Jays 61.0% 48.9% 64.3% 49.4% 61.3% 49.1% Braves 63.0% 52.5% 59.9% 43.7% 62.0% 52.3% Brewers 59.7% 48.9% 61.8% 46.4% 62.8% 51.2% Cardinals 62.0% 51.0% 60.5% 53.1% 60.4% 49.0% Cubs 63.1% 48.0% 60.9% 49.5% 62.9% 52.3% Diamondbacks 60.3% 48.0% 60.7% 47.0% 61.7% 49.8% Dodgers 61.5% 50.0% 64.2% 52.6% 62.2% 50.2% Giants 64.2% 52.7% 63.8% 51.6% 61.8% 47.1% Indians 61.2% 52.7% 61.8% 49.2% 60.0% 44.5% Mariners 63.4% 49.1% 66.5% 50.4% 60.3% 45.3% Marlins 63.3% 53.4% 63.7% 49.7% 62.6% 52.2% Mets 63.8% 52.5% 64.4% 53.6% 61.0% 47.9% Nationals 62.1% 49.0% 62.9% 52.4% 63.3% 51.2% Orioles 61.2% 51.8% 61.0% 45.9% 62.6% 46.2% Padres 62.4% 50.6% 61.9% 51.1% 61.4% 50.4% Phillies 60.7% 47.5% 61.7% 50.7% 61.2% 48.2% Pirates 63.4% 54.4% 63.4% 50.7% 60.3% 48.4% Rangers 62.2% 51.4% 61.4% 48.0% 64.0% 52.1% Rays 64.2% 54.6% 64.7% 46.5% 62.3% 49.0% Red Sox 59.4% 47.7% 57.1% 46.1% 61.9% 47.6% Reds 62.6% 52.4% 61.8% 49.0% 64.2% 52.6% Rockies 52.8% 44.9% 54.5% 44.3% 60.7% 48.9% Royals 63.4% 46.9% 62.5% 49.8% 64.0% 50.5% Tigers 62.7% 50.1% 61.2% 48.4% 61.6% 48.2% Twins 61.4% 50.8% 61.8% 54.3% 61.5% 48.1% White Sox 63.1% 49.5% 62.6% 51.0% 64.1% 52.8% Yankees 62.0% 51.9% 62.3% 45.4% 61.5% 51.3% XBH%, by Team, Ballpark and Fly Ball Type, 2013 At home On the road Away team Team All Sharp Fly All Sharp Fly All Sharp Fly Angels 9.3% 17.3% 10.7% 18.6% 10.9% 21.1% Astros 11.7% 19.6% 11.0% 19.4% 12.6% 21.9% Athletics 8.8% 16.9% 10.5% 20.6% 8.6% 16.2% Blue Jays 13.3% 23.7% 11.5% 24.5% 11.6% 18.7% Braves 10.6% 18.0% 11.6% 24.2% 10.9% 18.1% Brewers 9.6% 17.6% 11.6% 22.8% 10.0% 17.0% Cardinals 11.1% 18.7% 12.0% 19.7% 13.1% 23.3% Cubs 11.5% 22.1% 12.2% 19.2% 11.2% 20.6% Diamondbacks 12.2% 19.9% 13.8% 24.6% 11.9% 20.3% Dodgers 10.5% 18.5% 9.3% 16.4% 11.3% 20.6% Giants 11.1% 19.8% 12.0% 19.6% 11.1% 20.2% Indians 11.8% 19.8% 11.5% 21.3% 12.1% 22.2% Mariners 10.7% 21.1% 8.7% 17.5% 12.0% 23.0% Marlins 12.0% 19.7% 10.7% 18.6% 10.8% 18.2% Mets 9.3% 15.3% 10.5% 17.6% 11.6% 21.0% Nationals 12.0% 20.5% 10.7% 20.5% 10.5% 17.8% Orioles 10.1% 16.9% 10.5% 20.3% 11.2% 23.0% Padres 10.6% 17.6% 11.5% 17.9% 12.6% 23.4% Phillies 12.3% 21.5% 10.9% 20.0% 12.0% 23.0% Pirates 10.1% 15.7% 12.2% 21.4% 11.1% 20.4% Rangers 11.0% 18.2% 10.4% 21.0% 10.5% 19.0% Rays 10.4% 18.1% 9.6% 18.3% 10.6% 18.5% Red Sox 12.7% 19.5% 16.4% 24.4% 10.9% 19.6% Reds 10.5% 21.5% 11.3% 22.3% 11.1% 17.4% Rockies 13.7% 20.8% 14.2% 21.4% 12.8% 20.7% Royals 10.1% 19.7% 11.6% 18.7% 9.6% 17.4% Tigers 11.1% 20.0% 10.6% 17.9% 11.2% 19.3% Twins 12.0% 19.9% 11.4% 18.7% 10.7% 19.3% White Sox 8.6% 17.3% 8.2% 15.8% 10.2% 18.8% Yankees 11.8% 19.1% 9.2% 17.8% 12.0% 21.6% The Rockies, who play at the expansive Coors Field (the second most spacious field in the game) are easily the worst fielding team. At Coors Field, the home and away teams field 53 percent and 55 percent of fly balls, respectively, which is well under the league average of 62 percent. It’s not just Coors Field, though. Over the past two seasons, the Rockies have been below average on the road. There are some who believe that by the time the Rockies adjusts when they are on the road, the road trip is over, but that probably doesn’t account for the entire discrepancy. And at home, their fielding rate is actually a few percentage points less than the average away team at Coors. With this information, some defensive metrics, like UZR, have the Rockies’ outfield defense near the bottom of the league. Considering their fly ball fielding percentage, the Rockies may be getting short changed in some defensive metrics, but they’re still not very good. The second notable item is Boston’s low fielding rate. Red Sox Fielding Rates, 2013 Location and Team Sharp Fly ball Out% Sharp Fly ball XBH% At home 47.70% 19.50% Away team at Fenway 46.10% 24.40% On the road 47.60% 19.60% This seems to indicate that Red Sox fielders have an ability to limit the amount of hits, especially extra-base hits at Fenway. Boston allows an extra-base percentage of 19.5 at home; the away team stands at 24.4 percent. The difference in extra-base hits hits allowed is almost twice the value of the next largest difference (Pirates at PNC Park). The difference can probably be attributed to fielding balls ricocheted off the Green Monster. That is something that we have heard for years, but now we can see that there is something to it. Besides just looking at the data at the team level, here are the hang times for some individual pitchers. Each pitcher has what seems to be his own unique mix of batted balls. By grouping pitchers by their groundball and fly ball tendencies, clear baselines of pitcher batted ball types can be determined. Here are the top 10 2013 groundball and fly ball starters: Top Groundball Pitchers, 2013 Out% Fly ball% Name BABIP GB% FB% 1.5-2.5 2.5-4.0 4.0+ 1.5-2.5 2.5-4.0 4.0+ Justin Masterson 0.285 58% 24% 14% 62% 75% 22% 37% 51% A.J. Burnett 0.305 57% 24% 18% 46% 84% 20% 42% 47% Rick Porcello 0.315 55% 24% 20% 56% 74% 22% 40% 50% Doug Fister 0.332 54% 24% 13% 52% 80% 21% 37% 54% Jeff Locke 0.278 53% 26% 17% 59% 85% 15% 45% 49% Andrew Cashner 0.269 53% 29% 14% 46% 84% 16% 34% 58% Wade Miley 0.296 52% 27% 7% 61% 76% 16% 37% 57% Stephen Strasburg 0.263 52% 31% 15% 54% 83% 13% 31% 61% Felix Hernandez 0.314 51% 27% 12% 43% 83% 21% 38% 51% Edwin Jackson 0.322 51% 28% 6% 50% 70% 18% 40% 53% Average 0.298 54% 26% 14% 53% 79% 18% 38% 53% Top Fly ball Pitchers, 2013 Out% Fly ball% Name BABIP GB% FB% 1.5-2.5 2.5-4.0 4.0+ 1.5-2.5 2.5-4.0 4.0+ A.J. Griffin 0.242 32% 50% 5% 53% 82% 10% 30% 66% Max Scherzer 0.259 36% 45% 9% 55% 87% 10% 28% 67% Travis Wood 0.248 33% 45% 24% 57% 88% 13% 33% 61% Mike Minor 0.272 35% 43% 12% 58% 83% 14% 33% 60% Dan Haren 0.302 36% 42% 16% 48% 81% 11% 35% 60% Shelby Miller 0.280 38% 41% 0% 48% 83% 11% 30% 65% Julio Teheran 0.288 38% 41% 8% 40% 83% 12% 31% 64% R.A. Dickey 0.265 40% 41% 12% 48% 79% 14% 25% 67% Jeremy Hellickson 0.307 40% 40% 6% 64% 80% 16% 29% 62% Miguel Gonzalez 0.260 39% 40% 12% 55% 80% 14% 28% 65% Average 0.272 37% 43% 10% 52% 83% 12% 30% 64% Fly ball pitchers will have a lower BABIP because hitters put more air under the ball. The higher the ball goes, the more likely it will be an out. The issue with being a fly ball pitcher is that some of those balls will leave the yard as home runs. One interesting case is Jeremy Hellickson. Hellickson had been known for dancing around his poor marks in ERA-predictive stats such as xFIP, FIP and SIERA. In fact, he became somewhat of a punching bag in sabermetric circles as a player you should not trust. From 2010 to 2012 he posted a FIP of 4.46 with an ERA of 3.06. In 2013, many analysts claimed victory, when Hellickson’s ERA (5.17) finally rose as expected while his FIP (4.22) stayed about the same. Hellickson maintained a similar fly ball mix from 2012 to 2013. The main issue was that more batted balls which were in the air for a short time went for hits, especially extra-base hits. Jeremy Hellickson Fly Ball Rates, 2012-2013 Season 2012 2013 %Total – 1.5 to 2.5 15% 16% %Total – 2.5 to 4 33% 29% %Total – 4 or more 59% 62% Out% – 1.5 to 2.5 14% 6% Out% – 2.5 to 4 67% 64% Out% – 4 or more 78% 80% XBH% – 1.5 to 2.5 11% 13% XBH% – 2.5 to 4 8% 18% XBH% – 4 or more 7% 7% In the shortest two air time categories, he his out percentage declined and his extra-base percentage increased. Now, part of that could be that the Rays defense did not perform as well as it had in past seasons. The Rays struggled to make outs in 2013 (49 percent) compared to 2012 (55 percent) in the sharp fly ball category. It will be interesting to see how Hellickson fares in 2014 with Wil Myers spending more time in the outfield instead of Matt Joyce. Wrapping Up and Next Steps A fly ball’s hang time helps determine a fielder’s ability to catch it for an out. In 2004, Robert Dudek looked at a small sample of data to get the results of a fly ball depending on its air time. By using Inside Edge’s data, Dudek’s data is varied using an entire season’s data. The results were very similar. If a batted ball has too little hang time, it will be a hit. If it has too much hang time, it will likely be an out — if it stays in the field of play. With Inside Edge, much more data can be examined, such as how each team performs at home and away. Different teams and players will be able to field these batted balls for an out at different rates. The key for some teams is to make sure their outfield defense matches the type of pitchers they plan on using. The next step is to look at the data in a more detailed manner. For example, how many runs do the Red Sox save because of their familiarity with the Green Monster? I feel I created more questions by writing this article than I actually answered. Time to get back to work.