Fly Balls: Finding Home Runs is Easier than You Think
If you want to win tournaments in DFS, you’re going to need some home runs, as there is no quicker way to accumulate points in a hurry. A 2-HR game can cover up a lot of holes elsewhere in your lineup.
On August 16, 2014, I had the chance to win a million dollars playing fantasy baseball. With that kind of money on the line, you might think I dug deeper into some advanced metrics than usual trying to find an edge. But in fact, I used the same very basic stats that I’ve talked about here to determine which pitchers to play against.
I had 2 lineup priorities that day. As I said in the opening of this series, the first thing I found was my starting pitcher, as that is the most predictable position on any given day. Second, I wanted to find not just a player who could hit a home run, but two players regardless of cost that I thought had a chance to hit two home runs that night. I settled on the trio of David Price at starting pitcher along with David Ortiz and Jose Bautista as the core of my roster.
The process of choosing Ortiz and Bautista was not difficult or intensive. Simply put, they are home run hitters, and they were facing fly ball pitchers. It was not relevant to me how many home runs the opposing pitchers had allowed that year or in their careers. I didn’t even look at those numbers. Why not? Because as we discussed earlier, I know that every pitcher should be expected to allow a 10 percent home run to fly ball ratio, so I only care that they are allowing fly balls.
The handedness of the pitchers and batters also came into play, which we’ll dig further into in the next section. Jose Bautista had a 48.5 percent fly ball rate and 21 percent home run to fly ball ratio against left-handed pitchers in 2014. The opposing pitcher, lefty John Danks, allowed 41 percent fly balls to right-handed batters.
David Ortiz had a 46 percent fly ball rate against right-handed pitching with an 18 percent home run to fly ball ratio. He was facing righty Brad Peacock, and his 44 percent fly ball rate against left-handed batters. Anything over 40 percent is generally considered a fly ball pitcher.
As you can see, every angle of those matchups was over 40 percent fly balls from both the hitters and the pitchers. The fly ball chasing worked out as Ortiz ended up hitting two home runs that night in leading me to a life-changing payday.
If you can come to accept the randomness with which fly balls turn into home runs for a pitcher, you can really streamline your process of targeting home run hitters on any given day. Of course, ground ball pitchers occasionally give up homers too, but on a day with a full slate of games, out of 30 pitchers, you’re almost certainly going to find some guys with substantially higher fly ball rates than others.
I rarely play a fly ball hitter against a ground-ball pitcher in tournaments. This is not because there is no chance of getting a home run off the ground-ball pitcher, but simply because there is almost certainly a hitter at that position of similar quality in a matchup against a fly ball pitcher. So much is unpredictable, so why not just take every edge you can to add small odds on your side. Let’s put together a hypothetical game line for two pitchers.
Pitcher A) 50 percent fly ball rate, 7 innings pitched, 28 batters faced, 5 strikeouts, 1 walk = 22 balls hit. At a 50 percent fly ball rate, he will allow 11 fly balls in that game. At a 10 percent HR/FB rate, he can be expected to allow 1.1 home runs per game.
Pitcher B) 25 percent fly ball rate, 7 innings pitched, 28 batters faced, 5 strikeouts, 1 walk = 22 balls hit. At a 20 percent fly ball rate, he will allow 5.5 fly balls in that game. With a 10 percent home run to fly ball ratio, he can be expected to allow 0.55 home runs per game.
That is a big difference. Pitcher A is statistically likely to give up a home run every single game he pitches. Pitcher B will only allow a home run every two games.
Now, let’s take a look at some real-life numbers to see how fly ball rates affected home runs allowed by pitchers in 2014. In an attempt to keep the data as unbiased as possible, I’m going to compare pitchers who have similar strikeout rates and fell near the 10 percent home run to fly ball ratio.
Dallas Keuchel vs. Jered Weaver, 2014
Strikeout Rate – Keuchel, 18.1 percent | Weaver 19.0 percent
Home Run to Fly Ball Ratio – Keuchel, 9.6 percent | Weaver 8.9 percent
Fly Ball Rate – Keuchel, 19.3 percent | Weaver, 47.9 percent
Innings/Batters Faced/Home Runs – Keuchel, 200 IP/808 BF/11 HR | Weaver, 213 IP/888 BF/27 HR
Home Runs/Batters Faced – Keuchel, 1 home run for every 73 batters | Weaver – 1 home run for every 33 batters.
Keuchel and Weaver have extremely similar skills outside of a vastly different fly ball rate. Keuchel had the highest ground-ball rate in the league, but note how he still had right on the league average home run to fly ball ratio. It’s not that he has a skill of keeping fly balls in the park; he has a skill of keeping balls on the ground.
Zack Wheeler vs. Drew Hutchison, 2014
Strikeout Rate – Wheeler, 23.6 percent | Hutchison 23.4 percent
Home Run to Fly Ball Ratio – Wheeler, 10.1 percent | Hutchison, 9.7 percent
Fly Ball Rate – Wheeler, 27.3 percent | Hutchison, 45.2 percent
Innings/Batters Faced/Home Runs – Wheeler, 185 IP/794 BF/14 HR | Hutchison, 184 IP/786 BF/23 HR
Home Runs/Batters Faced – Wheeler, 1 home run for every 57 batters | Hutchison, 1 home run for every 34 batters.
Wheeler and Hutchison are both good young pitchers with above-average strikeout rates. Their ground ball and fly ball splits are not as severe as Keuchel and Weaver, but you still can see a clear difference in the number of home runs they allow.
Tim Hudson vs. Colby Lewis, 2014
Strikeout Rate – Hudson, 15.2 percent | Lewis, 17.5 percent
Home Run to Fly Ball Ratio – Hudson, 9.3 percent | Lewis, 10.1 percent
Fly Ball Rate – Hudson, 25.9 percent | Lewis, 44.2 percent
Innings/Batters Faced/Home Runs – Hudson, 189 IP/789 BF/15 HR | Lewis, 170 IP/762 BF/25 HR
Home Runs/Batters Faced – Hudson, 1 home run for every 52 batters | Lewis, 1 home run for every 30 batters.
Unlike Wheeler and Hutchison, Hudson and Lewis both have below-average strikeout rates. You can see that this leads to a slightly higher rate of home runs per batters faced for both pitchers as compared with the higher strikeout pitchers. But even if you compare a higher strikeout, fly ball pitcher like Hutchison to a lower strikeout, ground-ball pitcher like Hudson, you still get a much higher home run rate for the fly ball pitcher.
If you want to add one more layer to your research in looking for home runs, you should become familiar with ballpark factors. As you probably know, certain parks are much more hitter friendly than others. RotoGrinders has a ballpark factors page, where you can sort a list of parks in order of highest home run rate. If you see two pitchers on a slate with similar fly ball rates, you are better off playing against the one in the more homer-friendly ballpark.
DFS Takeaways
The search for home runs begins not with the number of home runs hit nor the number of home runs allowed. It starts with fly balls. You are more likely to get a home run off of a highly-skilled, fly ball pitcher than you are off of a mediocre journeyman pitcher with a high ground-ball rate. In DFS tournaments, whether you’re playing for $1 or $1 million, you’re going to need those home runs to win. And just remember where home runs come from: fly balls.