Examining Changes in Fly Ball Rate

Ever since the boss, Mr. Eno Sarris, showed me how to use the VLOOKUP function in Excel, I can’t stop comparing recent numbers to past rates. The function makes it easy to put this season’s numbers in one sheet, past season or career numbers in another sheet, and then pull the past numbers and place them right next to the corresponding season numbers for any sample of players.

Instead of billing a client from 1:15-3:05 yesterday afternoon at work, I toyed around comparing 2012 and career fly ball rates to 2013 numbers. I chose those two because we’re at the point in the year where most qualified hitters have a sample of 80+ balls in play, which is the point at which FB% stabilizes according to Russell Carleton.

The first thing I looked at was whether the hitters with the highest fly ball rates in 2012 had seen a shift so far this season. The idea was that the guys who cut down on the fly balls would see a corresponding rise in average given that fly balls go for hits somewhere in the neighborhood of 13%-15% of the time, while ground balls are hits roughly 25% of the time and line drives about 71-73% of the time.


2013 FB%

2012 FB%

FB% Gap

Jed Lowrie




Mike Moustakas




Edwin Encarnacion




Jose Bautista





We’ll get to Moustakas in a bit, but first let’s see whether the three who have cut their fly ball rate have seen a higher batting average so far.

Lowrie has taken that 14% decline in FB% and 9% has been added to his LD% with the other 5% going to GB%. As a result, his BABIP and batting average are currently career high marks at .344 and .299, respectively. But we’re nowhere close to the point where we could think his 28.3% LD% is sustainable. With the obvious batting average regression and his injury history, Lowrie is a clear sell at this point. He’s currently 11th among shortstops on ESPN’s player rater, and I’d swap him straight up for Asdrubal Cabrera (14th), Jimmy Rollins (15th) or maybe even Andrelton Simmons (19th).

Bautista has taken his 10% dip in FB% and applied the excess equally between LD% and GB%. Again, the LD% will likely regress and the average along with it because Bautista probably isn’t going to continue hitting line drives at a rate 3% higher than he has for his career. The dip in FB% obviously also comes along with a dip in HR/PA, but Bautista still has a high enough HR/FB (over 20%) that he can top 30 HR and approach 35. With an average around .260, that power is worth holding on to. Don’t move Bautista.

Encarnacion has only seen a slight shift downward in FB%, but you would expect a few more line drives and ground balls to lead to a slight uptick in average or at least hold it steady. Instead, Encarnacion’s BABIP has plummeted despite the increase in the types of batted balls that go for hits more frequently. He’s not striking out at a higher rate, so we should fully expect to see some positive regression in BABIP and average. And he’s still hitting fly balls out at the same clip that he did last year. I’d say he’s a good buy option, but he’s fifth among first basemen on the player rater, so I’m not sure too many people are selling. Hold on to him if you have him.

As for Moustakas, he’s gone from the second highest fly ball rate in 2012 to the highest fly ball rate in 2013 (among players with 80+ BIP in 2013). His line drive rate is down 3% from last year to a paltry 13.3%. That’s contributed to a .198 BABIP. Admittedly, his BABIP is way too low even with his poor batted ball profile. His xBABIP is roughly .255. And he has cut his K% about 5%. There’s definitely some positive average regression coming. But unless he stops hitting the ball in the air so much, he’ll have a tough time hitting even .250 the rest of the way. Unfortunately, there’s nothing you can do but ride it out and hope he makes some sort of swing adjustment and puts fewer balls in the air.

One spot below Moustakas is Paul Konerko. Thanks to a 13% increase in FB%, Konerko owns the 2nd highest FB% in the league so far (min. 80 BIP). He’s actually hitting line drives more than he did last year and more than he has in his career, but he’s hitting significantly fewer balls on the ground. The extra fly balls have certainly contributed to his .238 BABIP and .215 average. But his career-high 18.8% K% isn’t helping either. And thanks to a below average batted ball distance, Konerko’s HR/FB is just 7.7%. If you were looking at that .238 BABIP and considering buying low, you shouldn’t. Turn out the lights; the party’s over.

If you’ll allow me one final note, I noticed quite a few Athletics popping up with high fly ball rates. Of the eleven A’s with 100+ PA through Wednesday, eight of them have career fly ball rates above league average (36%). And their most recent additions have the highest fly ball rates on the team. The A’s have acquired Jed Lowrie, Josh Reddick and Chris Young by trade recently, and all three have career fly ball rates of 48% or higher, which is well above average. Even Yoenis Cespedes hits fly balls at an above average clip (42.4%).

Because of these recent acquisitions, the A’s currently have the highest fly ball rate in the league. And this seems odd given the spacious home park they play in. That home park has helped contribute to them having the 5th lowest HR/FB rate.

Or at least it would seem odd if Oakland was actively seeking out guys who put the ball in the air a lot. That might not be the reason they have made these acquisitions. The players obviously have other skills. Aside from Cespedes, three of them are above average defenders. Lowrie and Young know how to take a walk. It’s also possible that the commonality of the high FB% is just a coincidence. Oakland may have acquired each guy simply because the value was there with no thought given to their fly ball tendencies. Or maybe Oakland knows something we don’t. It wouldn’t be the first time.

You can find more of Brett's work on TheFantasyFix.com or follow him on Twitter @TheRealTAL.

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Would someone at FG be kind enough to post a brief tutorial on using VLOOKUP? I’m handy with Excel but not familiar with this command, and available online tutorials (as expected) don’t give handy examples of utilizing VLOOKUP for baseball data mining purposes. I’m aware this would be a super-nerdy article, but I want to know about a new way to spend the afternoon sorting baseball data!


Say you have a sheet called “fb12” that has player names in column A and their 2012 FB% in column B. Sheet “fb13” has a similar setup with the 2013 numbers. You want to get the 2012 numbers into column C on “fb13” so you can compare. Put this formula in C2 on “fb13”:

The parameters are
-thing I want to look up (player name)
-table containing data I want to look up (players in first column, 2012 FB% in second column)
-column number I want returned (2nd column)
-don’t worry about the last one, just always put FALSE



I just use index and match. Index(B:B,match(“Jose Bautista”,A:A,0)) will find jose bautista in column A and and give you whatever corresponding number is in column B. It’s more robust than vlookup and in my opinion, easier to use.


index and match are great to use instead of vlookup when you’re having file size and memory issues; the vlookup formula stores a copy of the entire range in the 2nd portion of the formula in memory for each instance of the formula. the index and match functions store less in memory. this is great for both reducing file size when you’ve got a ton of these formulas and for improving refresh / update speed.

Will Hannon
Will Hannon

Go straight to the source: VLOOKUP – Excel