Daily Fantasy NFL: Expected Versus Actual Running Back Touchdowns

The Patriots are at the one yard line. Running play to Blount… he’s stopped for no gain. Next play looks again like a running play to Blount… but wait! It’s play action, Brady hits Gronkowski in the end zone… But he drops it!. 3rd down, Brady drops back to pass, Amendola catches the slant… Touchdown!

How many times have you seen a series of plays like I’ve described above, where it seemed like several guys had golden opportunities to score and just missed? There is a lot of variance in Touchdowns. You can see it clearly when you watch a team in the red zone. There’s so much that can go on that is out of a players control that causes one player or another to score. Because TDs can happen quite randomly, we can model how many TDs a player should be scoring versus his actual TD numbers to see who has been getting lucky or unlucky in the TD department, and who we can expect to perform well for the rest of the season. Today, I’m going to look at rushing TDs specifically.

NFLsavant is a fantastic NFL data site that supplies Red Zone Rushing Attempts (RZRA) data for free. What the RZRA data shows is rushing attempts in the red zone, as well as TDs scored in the red zone. Unsurprisingly, these two values are highly correlated, with an r squared of 0.77 for 2014. The more chances a player gets to rush in the red zone, the more TDs we can expect them to score. Since RBs score the majority of their TDs in the red zone, red zone rushing attempts is going to be the main driver of expected TDs.


If you fit a line to the data for the past two seasons, you find that each rush is worth approximately 1/6th of a TD. Using linear regression as a model, I looked at how many rushing TDs we would expect for an RB in 2015 versus the amount of rushing TDs they have actually scored. You can look at this data for 2015 here. You can see the fit in the graph above, it’s the red line. The one big outlier on the bottom right is LeSean McCoy last season, He rushed in the red zone 57 times, but only scored 4 times.

On the linked table, DIFF shows us the difference between expected red zone TDs and actual red zone TDs. Positive values mean this player should have scored more TDs than he actually did, negative means this player should have scored less TDs. Chris Johnson is in the lead on the positive side, he was expected to score about 5.3 TDs, but only scored 2. Alfred Morris hasn’t scored any red zone TDs this season, but was expected to have about 2.75, which puts him in second. On the flip side, Jeremy Langford and Spencer Ware have gotten the luckiest, each expected to have 3.77 and 3.28 TDs less than their actual totals. While these numbers do not account for huge differences in fantasy points, they are significant.

One possible issue with this approach is we assume each running back is just as likely to score on a rush attempt in the red zone than anyone else. My first thought was heavier running backs would have better red zone efficiency. It turns out the correlation between DIFF and weight is quite small, -0.17 for 2014. So weight only explains a small amount of the variance between rushes and TDs.  Another factor could be height, but that showed no relationship at all. So weight and height do not make much of a difference, if any, Nor does RB skill it seems. There are good and bad players on both sides of the equation.

The only problem I see with this method is we can’t assume players who have a lot of red zone rushing attempts will get a lot in the future. Looking at the data from the past two seasons, there is a pretty big trend. Teams that run the ball a lot, and players who get the majority of snaps tend to be the guys who rush the most in the red zone. Seattle and Dallas were 2nd and 3rd in rushing play percentage last season, and Marshawn Lynch and Demarco Murray led the league in red zone rushing attempts. This season, Carolina leads the league rush play percentage, and Jonathan Stewart has a commanding lead in red zone rushing attempts. You can use our estimated rush percentages in our Sportsbook Projection tool for a good idea on which players should have the most red zone rushing opportunities.

We can see that red zone rushing attempts play a huge part in expected rushing TDs. Players who have had less than their expected rushing TDs are probably good buys for the rest of the season, while players who have more than expected rushing TDs may be worth a fade in coming weeks. You can estimate which teams will have the most red zone rushing attempts by looking at our Estimate Rush Percentage model. You can look at RZRA data on a Week to Week basis over at NFLsavant.


View all posts by Daniel Steinberg
Daniel Steinberg

About the Author

Daniel Steinberg Daniel Steinberg is a former bond trader at a multi-billion dollar proprietary trading firm in Chicago. He uses his knowledge of statistics and his creativity from his career as a poker professional to create the most advanced Daily Fantasy statistical analysis that you will find anywhere. Follow him on twitter @DanielSingerS

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