Everyone Wants to Win Consistently: But what’s the secret? – Written by Daniel Veino
Using Advanced statistical data in the daily fantasy sports realm is a relatively new concept over the past few years. This new technology allows for the spectators to see how fast the ball is coming off the bat, how fast a player truly is, & even the spin rate of a ball being pitched. For example, back in 2013 Collin McHugh pitched 15 games and had an atrocious ERA of 8.94. However, the Astros noticed Collin’s spin rate with his curveball was among the best in the league. The following season they had him focusing more on mastering the curveball and he finished that year with an ERA of 2.73 over 25 starts. That’s just one of the many examples where these new statistics can actually help teams find a diamond in the rough. So what are some of these newer statistical categories, and what do they offer DFS users?
Weighted On Base Average – (WOBA)
This statistic gives individual value to a batters means of reaching a base. On-base percentage captures how much a player ends up on base due to plate appearances and hits alone. With weighted on-base average, every type of hit has its own point system. Walks, singles, doubles, triples, & home runs have a specific point value which all gets calculated into the hitters (Woba). This is useful because you can now see what type of hitter is at the plate. The higher the Woba percentage, the more likely the batter will get extra base hits or hit more home-runs. The lower the hitters woba percentage is, the less likely they will get extra base hits.
Applying WoBA –
WOBA is a great way to identify what kind of hitter is at the plate. If the hitter has a higher WOBA percentage, he has more value based on what type of hits he brings to the table. Conversely, if a hitter with a low WOBA percentage is at the plate, he is more likely to keep the ball in the park or on the ground.
Expected Weighted on Base Average – (xWOBA)
Expected weighted on base average separates itself from (WOBA) because it does not include defensive plays. If Mookie Betts got up to the plate and crushed a ball to mid-center, only to then get robbed of a home-run – His xWOBA would still go up still. This statistic measures where the ball actually ends up landing and the trajectory on how it got there. This is known as the Launch Angle.
Applying xWOBA –
xWOBA is very useful in situations when you want to know pound for pound what kind of hitter a player is. For example, J.D. Martinez gets up to the plate and smacks a high fly ball to the outfield. Only to then be robbed of a home run by Mike Trout at the warning track. The hitters wOBA percentage will still go up because xWOBA takes into account the trajectory of a hit. The trajectory was a home-run and in this case, a defensive player had to make a very tough play to nullify it. So in this scenario, J.D. Martinez may have gotten his home run robbed, but his xWOBA percentage still increased given the trajectory of his hit. Overall this gives you a more precise look at the true skill of the hitter, rather than the traditional WOBA does itself.
Launch Angle Types:
There are four different types of launch angles that are associated with pitchers and hitters.
- 1.) Ground ball –> Less than 10 degrees
- 2.) Line drive –> 10-25 degrees
- 3.) Fly ball –> 25-50 degrees
- 4.) Pop up –> Greater than 50 degrees
Applying Launch Angle:
This concept is useful in DFS because it can tell you whether or not a pitcher is more apt to give up ground balls or fly balls. When more ground balls are given up by a pitcher, it tends to mean they allow fewer extra-base hits & home-runs. On the contrary, if you give up more fly balls and line drives; the pitcher is more likely to allow extra-base hits and home-runs. Bringing it all together now, if a pitcher has a lower ‘average launch angle against’ % (aLAA), then they are more attractive to pick and to use in your lineup. This is because you want the pitcher who can keep the ball on the ground, as well as keep it inside the park. If a pitcher has a high (aLAA), then it means on average, they allow more line drives and fly balls. This can be useful in identifying an exploitable pitcher; which can ultimately lead to a lineup stack against them.
This measures the speed the ball comes off of the bat as well as the angle at which the ball is contacted. It doesn’t matter if its an out, a hit, or if there’s an error on the play.
It can also help determine ‘topped’ ‘or ‘poorly hit’ balls which can then help track the batters sprint speed.
Applying Exit Velocity:
The exit velocity is useful because it spits out a percentage that records how fast the ball came off the bat. The harder you hit the ball, the less time a defense has to react to it. Which in turn allows for the batter to reach base more often. In DFS, finding the players with a higher exit velocity will translate to more hits. A higher exit velocity correlates directly with how fast the ball is coming off the bat.
Example: Say you have a solid batter that is having a tough time and hitting .150 in the month of October, but he has a very high exit velocity in that span. Based off the high exit velocity alone, one can infer that the hitter will return to his normal averages in the near future. Conversely, if a player is hitting .300 in the month of October with a low exit velocity; then a smart DFS player would see that and understand a regression is on the horizon.
Hit Probability Percentage:
Hit probability is a stat that was introduced back in 2015 by Statcast. The idea behind it is simple; every time a batter hits the ball a percentage gets assigned with it. This percentage is based off of batted balls in the past that were similar.
Applying Hit Probability to DFS:
For this stat, a pitcher cannot control what happens to a ball once it is in play; as well as a batter cannot control what happens to a ball once contact is made. Overall this gives you an idea as to what the pitcher and hitter can control in a game by taking out the defense entirely. For example: a fly ball to the outfield with a hit probability of 50 percent means that five out of 10 times it will become a hit. This percentage is based off of other hit balls with a similar exit velocity and launch angle.
Expected Slugging Percentage: (xSLG)
This statistical category is also found by using the launch angle, exit velocity, and at times the players sprint speed. Each hit by a batter has a point value associated with it. (Listed below).
It’s more advanced than the traditional method of finding out a players straight slugging percentage. With xSLG, the defense is not incorporated at all.
What each hit is worth: (xSLG)
Single – (x) – Double – (2x) – Triple – (3x) – Homerun – (4x)
Applying Expected Slugging Percentage:
Similar to xWOBA, the xSLG uses the launch angle and exit velocity of a hitter to determine the final outcome of a hit. So if Andrew Benitendi hits a fly ball to left center and he gets robbed of a home run at the wall; Andrew’s xSLG percentage will still go up. This is because the trajectory of the hit was a homerun. A defensive player had to make an amazing play to take the points away.
Bringing It All Together:
All of these statistics are relatively new to the daily fantasy sports realm, but DFS players are learning to exploit these numbers and improve their final scores across the board. If you design a process in which you incorporate many of these statistical categories into; you in turn will start seeing better results than the average player that uses basic data points. If you are reading this and feel overwhelmed by all this information, don’t panic. It’s much easier than it all sounds. In a nutshell, these advanced statistics help you create the exact type of lineup you want by delivering industry changing metrics; that in many cases, wasn’t available to DFS users 5 years ago.