Using Our Run/Pass Share Tool for NFL Daily Fantasy
After writing this article examining how workload of run/pass is more important than proficiency against the pass or run, I added a feature to our NFL Sportsbook Point Projection tool. The tool attempts to quantify good teams to target in fantasy in the running game and the passing game by looking at how run or pass happy that team is and how much their opponents are run or passed on. Based on the theoretical run/pass workload, we separate the results into two categories: Run Point Share and Pass Point Share.
How It Works
How often a team is run/passed on or how often they run/pass is mostly a function of the team makeup. We know the Saints are a very pass oriented team, while the Texans are a very run first team, mostly because both teams are much more proficient at passing and running respectively. We know that the Raiders get run on a ton, and the Jets seem to only be passed on because of the same lack of proficiency (and incredible defensive tackeles). But how often a team runs or passes is also a function of the texture of each game they’ve played in a given season.
Scoring Margin is a statistic that is points scored minus points allowed divided by the number of games, or average win/loss margin. This number has a correlation of nearly .5 to the proportion a team runs the ball versus passes the ball. Why? Because teams that are behind by a lot of points have to pass to catch up, and teams that are ahead by a lot of points take conservative approaches that involve mostly running the ball.
To get a teams true inclination to run or pass or to get run or passed on, we need to take scoring margin out of the equation. I did this by running a linear regression on scoring margin and run play percentage. The equation I got was 42%+.3%*Scoring Margin. In other words, for every 10 points in scoring margin, we can expect a team to run the ball 3% more of the time. After I did that, I subtracted a teams actual run play percentage by their theoretical run play percentage on scoring margin alone. This gave me what I called the True Rush Rank, how often a team is inclined to run the ball without scoring margin bias.
I did the same thing for opponent rush play percentage, and therefore found a more accurate rank of how often opponents run or pass on a certain team.
What you see on the tools page in the third column is how much a team is favored by. Given that estimated scoring margin, I estimate the teams theoretical run play percentage, which is under the TRRP column. After that is calculated, I take the teams True Rush Rank, which is under the TRR column, and the opponents Rush Rank Against, under the RRA column. I add the TRR and RRA to the TRRP to get the Estimated Run Play Percentage, which is abbreviated by ERRP. 1-ERRP will give you the Estimated Pass Play Percentage, which is the EPPP column.
Workload isn’t all that matters, but since run versus pass workload seems to be quite predictive of fantasy value, I simply multiply the ERRP and EPPP by the point projections to get the Run Point Share and Pass Point Share. For example, New England has a 37.74% ERPP and a 28.5 point projection, so their Run Point Share is .3774*28.5, which equals 10.76.
How To Use Run and Pass Point Share
Run Point Share and Pass Point Share are not to be literally interpreted as the amount a team will score running the ball and how much they will score passing the ball. A complete estimate of that would involve looking at special teams, field goals, defensive points, and how teams generally score running or passing. But what RPS and PPS do give us is a good metric on how we can expect fantasy points to be distributed throughout a team. The higher the RPS, the more appealing a RB on that team becomes, and vice versa.
Dallas has the highest RPS this week, with 14.46. This suggests that figuring out the Cowboys RB situation is going to be extremely key to winning in Week 1. It’s expected that Darren McFadden and Joseph Randle will split time at RB, but I don’t really buy it. The Cowboys are not used to having a two back system, as Demarco Murray saw nearly 100% of snaps last season, and I suspect one of McFadden or Randle will end up with the bulk of the snaps. Randle has almost no experience or success as a receiver, so my guess is McFadden gets most of the workload since Randle doesn’t seem that viable on 3rd downs.
An interesting team high on Run Point Share is the Jets. Fantasy points for running backs is highly correlated to snaps. That’s mostly why Chris Ivory, who is a fairly good running back, didn’t score a lot of fantasy points last season: He split time with Chris Johnson and only saw about 40% of snaps. That number could greatly increase this year if new offensive coordinator Chan Gailey takes a different approach. Chris Johnson is gone, but Bilal Powell could be another guy that sees more touches,
The Patriots have the highest Pass Point Share. There isn’t anything particularly interesting to glean from this, besides that Rob Gronkowski and Julian Edelman both seem like solid Week 1 plays.
Green Bay comes in 3rd in Pass Point Share and is probably the most interesting team to look at Week 1 with Jordy Nelson out for the season. The Packers run a lot of 3 WR sets, so while Davante Adams may be the most slam dunk fantasy play of Week 1, figuring out who gets the biggest workload between Ty Montgomery and Jeff Janis may be the key to winning a million dollars on FanDuel or two million dollars on DraftKings.
With PPR on DraftKings, looking at pure pass percentage projections can be useful as well. Baltimore is supposed to pass the most Week 1, so Steve Smith, Kamar Aiken, and Crockett Gilmore all seem like solid play. Gilmore and Aiken seem like more sensible targets, given the Broncos have arguably the best #1 cornerback in the league.
This Is Only A Small Factor
In general, I think a players pricing and team injury impact are the two most important factors in NFL Daily Fantasy. So I wouldn’t go and play Emmanuel Sanders just because the Broncos have a great pass share (although he is probably a solid play). But these metrics do suggest teams to look at for fantasy value, or teams to stay away from.
It’s also good to note that team makeup can change drastically from year to year, so the 2014 data we’re basing these projections on may be quite off until we get a few weeks of 2015 data. The Ravens, for example, no longer have one of their best run defenders in Haloti Ngata, who they lost in free agency to the Lions, so they may not be as stout against the run as last year. The Patriots no longer have Darrelle Revis, so their pass defense is going to take a huge hit. A lot of the skill of NFL early week daily fantasy is figuring out how team makeups have changed, and who to target based on those changes. As we get deeper into the season, Run/Pass share should become a lot more useful.
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