Which Draft-Hopeful Running Backs Produced Like Studs in College?

By looking strictly at college production, which running backs look like they'll be strong fantasy football assets in the NFL?

Where a running back gets drafted plays a huge role in how well that running back will perform in fantasy football.

Maybe it's because teams are really good at evaluating running backs. Or -- and this is more probable -- maybe it's because early-round picks get immediate opportunity, and opportunity is what drives fantasy value.

Whatever the case may be, if a running back gets selected in the first round of the NFL Draft, you better believe his chance of hitting as a pretend football asset skyrockets.

Draft capital matters. A lot.

That fact doesn't mean we should just ignore everything else about a running back prospect, though. Similar to the wide receiver position -- which was covered a week ago -- statistical modeling can help us pinpoint potential superstars at the running back position. It can help us predict how well incoming rookies will perform in fantasy football better than straight-up draft capital can.

Much better, actually.

The Model

So what exactly goes into a prospect model that helps predict fantasy football success? A lot of things. With my model, I'm looking at things like a running back's BMI, his weight-adjusted 40-yard dash time, and plenty of other statistical factors. Once a score is compiled with all this info, that score is compared to how fantasy running backs performed in the NFL during their first three years as pros to ensure a strong correlation.

More concisely: the model is attempting to predict how a prospect will perform in fantasy football through his first three years in the league.

Like I said before, draft capital matters. So where a running back gets selected in April is factored into all of this, too. But with the other inputs, the predictiveness of the model is far better than draft capital alone.

Statistically, the model looks at how a college running back performed in three major categories: final-season total touchdown share, final-season reception share, and final-season total yards per team play. Since the model's using historical player information to help find good prospects, that means the majority of top running backs in the NFL -- the top running backs in fantasy football -- were also productive when they were in college within these categories.

What does that mean for the potential success among backs in this year's class then?

The Process

Like last week with wide receivers, the goal here is to look at a subset of successful NFL running backs, see how they performed within the three main statistical categories, and use that information to spot gems in this year's group. The problem is, how exactly do we define who's in that subset? What's a "successful running back"?

Quite simply, I've arbitrarily defined a successful running back as one who's posted multiple top-20 fantasy seasons since 2011. That gives us 49 running backs. After filtering out the older players and ones who weren't drafted or invited to the combine (like Phillip Lindsay), the sample dropped to 42. Those 42 successful NFL backs are our "studs."

Here's how those 42 players performed in the three major statistical categories referenced above. (Note: if a player missed significant time during their final season, their next relevant season was used.)

Category NFL Studs
Total Touchdown Share 34.15%
Reception Share 11.33%
Total Yards Per Team Play 1.90

These numbers likely don't mean a whole lot to you, so here's how the NFL Studs sample stacks up against the 30 running backs who were invited to this year's NFL combine.

Category NFL Studs 2020 Class
Total Touchdown Share 34.15% 26.38%
Reception Share 11.33% 9.07%
Total Yards Per Team Play 1.90 1.36

Like the wide receivers that were looked at last week, the NFL stud running back group -- the players who've had multiple top-20 seasons over the last decade -- were more productive in college.

Which players from this year's class came close?

The Results

Total Touchdown Share

The average final-season total touchdown share (the percentage of team touchdowns scored by a running back) among the NFL Studs sample was a little over 34%. Within this year's class of 30, we saw 23 running backs who weren't able to get to that mark. There were 18 who were under 30%.

Player College Total Touchdown Share
JK Dobbins Ohio State 26.44%
Ben LeMay Charlotte 26.00%
Patrick Taylor Jr Memphis 23.68%
Sewo Olonilua Texas Christian 23.68%
DeeJay Dallas Miami (FL) 23.26%
Anthony McFarland Maryland 23.08%
Salvon Ahmed Washington 22.92%
Javon Leake Maryland 20.51%
Lamical Perine Florida 20.37%
Clyde Edwards-Helaire LSU 18.48%
D'Andre Swift Georgia 17.02%
Darius Anderson Texas Christian 15.79%
Brian Herrien Georgia 14.89%
Rico Dowdle South Carolina 13.33%
Tony Jones Jr Notre Dame 12.28%
JJ Taylor Arizona 11.90%
JaMycal Hasty Baylor 11.86%
Raymond Calais Louisiana 10.14%

Is this a death sentence for JK Dobbins, who's one of the higher-ranked running backs in this class? Definitely not. Of the three statistics we're analyzing here, total touchdown share matters least in the model. Not only that, but within our stud NFL running back sample, 31% of the backs had lower final-season total touchdown shares.

Only 9% had as low of a share as Clyde Edwards-Helaire, though. Maybe that's an issue, but do keep in mind the environment he was playing in. Quarterback Joe Burrow is likely going number-one overall in this year's draft, and he helped lead LSU to the 12th-highest pass-to-rush touchdown ratio in the country. Because, you know, he's good at throwing the football. As a result, there's less concern over CEH's low number.

D'Andre Swift's 17.0% final-season total touchdown share is a little scary as well. His whole profile is -- he was below the NFL Stud sample's average in all three categories.

Swift's season-long totals do show somewhat of a split backfield, but he was barely involved in cakewalk games versus Murray State and Arkansas State. He was then injured late in the year and wasn't able to carry the ball much at all.

Maybe you're saying, "This is why you can't prospect via data."


This is a big reason why implementing draft capital matters. Data won't show you everything. It'll allow you to get a good grasp on a class and see trends, but there will be instances like the one we're seeing with Swift where circumstances pushed his production -- his stat score (a weighted score using the three main statistical measures) -- down.

Reception Share

Even with Swift's bumps in the road, his stat score isn't that bad. His final-season reception share (the percentage of team receptions made by a running back) was 9.4%, a number above the class' average. It's not quite as high as the 11.3% NFL Stud average, but it's not glaring at all.

Reception share is a bigger deal to the model than touchdown share is. The narrative I've built to explain why reception share helps the predictiveness of the model is that good players see the ball in all sorts of ways. If a running back is good, then his coaches will find ways to get him in space. If a team is consistently targeting a running back, then he's likely talented.

This year's draft class is filled with pass-catchers. In fact, 27 of the 30 players invited to the combine hit a 5% reception share during their final collegiate season. Of the 37 running backs who were invited to the combine or drafted last season, 10 were unable to hit that mark. That's a much higher proportion.

Here's a quick look at some of the lower-ranking players in reception share from this year's class.

Player School Reception Share
Brian Herrien Georgia 6.27%
LeVante Bellamy Western Michigan 6.10%
Salvon Ahmed Washington 6.08%
Tony Jones Jr Notre Dame 5.93%
DeeJay Dallas Miami (FL) 5.49%
Javon Leake Maryland 5.23%
Joshua Kelley UCLA 4.23%
Raymond Calais Louisiana 3.73%
Scottie Phillips Ole Miss 3.55%

One player to call out here is Josh Kelley, who evidently stood out at the Senior Bowl. He's not ranked among the elite backs in the class, but scouts are into him. His 4.2% reception share last season is a bit of a red flag, since so few successful NFL running backs had that low a share in college. He did see more work as a receiver in 2018, but final-season numbers are what's best for forecasting purposes.

Yards Per Team Play

The most meaningful statistic in the model is total yards per team play, which sort of captures everything. It helps bring together the standard market share statistics pretty well, since a player getting production at a high rate for his team is really what we're looking at with rushing yard share, receiving yard share, and so on. That's what yards per team play does. It also places an inherent emphasis on receiving, which is something that's clearly important for running back prospects. In turn, players who rank highly within the statistic get the most love from the model.

According to our NFL Studs subset, the average final season yards per team play rate was 1.90. That was met by just four running backs in this year's class: Jonathan Taylor, JK Dobbins, Zack Moss, and AJ Dillon.

Of the 42 successful fantasy running backs, just 5 had a total yards per team play rate below 1.40, and Chris Carson is the only back who had a rate under 1.00. There were seven players with that low of a final-season mark in this year's class.

Player College Total Yards Per Team Play
DeeJay Dallas Miami (FL) 0.99
Raymond Calais Louisiana 0.98
Anthony McFarland Maryland 0.96
JaMycal Hasty Baylor 0.86
Rico Dowdle South Carolina 0.77
Sewo Olonilua Texas Christian 0.72
Brian Herrien Georgia 0.64

There aren't many callouts on this list, but if you see a running back on it that you like, that's not a great sign. Chances are, none of these players will be productive fantasy football assets at the next level.

The Studs

No player from this year's draft class hit on all the averages from the NFL Stud sample. That doesn't mean there aren't good prospects -- there are a lot of good ones.

If we loosen the parameters a bit, here's who comes out on top.

Player College Total TD Share Reception Share Tot Yards / Team Play
Jonathan Taylor Wisconsin 46.43% 10.57% 2.36
Zack Moss Utah 31.48% 12.02% 1.98
Ke'Shawn Vaughn Vanderbilt 47.62% 13.86% 1.75
Eno Benjamin Arizona State 35.29% 18.03% 1.70

As of today, Jonathan Taylor looks like the most complete back in the class. His total yards per team play is elite, and the only thing that's lacking slightly in his profile -- according to the model -- is his final-season reception share numbers. Things could all change depending on where he gets drafted, but he's number one right now.

Zack Moss has been compared to Kareem Hunt, and he's another potential earlier-round pick this year. It'll be interesting to see how fast he runs the 40 at the combine, because that was an unnecessary knock on Hunt as a prospect.

Two of the lower-key players that the model likes a lot heading into the combine are Ke'Shawn Vaughn and Eno Benjamin. Vaughn was really strong across the board and actually has the second-best stat score in the class behind Jonathan Taylor. Draft capital may not be on his side, which will push him down the rankings, but he's a player to watch throughout the process.

A concern for Benjamin is that he may be a little undersized. He did carry the ball over 550 times during his final two collegiate seasons, which is a great sign, but he weighed in at 195 pounds at the Senior Bowl. Apparently this is due to an attempt to run faster at the combine, but the issue is that teams may end up typecasting him as only a pass-catcher. That would limit his fantasy football upside.

Overall, this is a really strong running back class. If anyone wants to place JK Dobbins, D'Andre Swift, Cam Akers, Clyde Edwards-Helaire, Jonathan Taylor -- if any of those guys end up as the number-one running back on draft boards, it's totally defensible. They each have solid-enough production profiles to be successful fantasy backs at the next level.

So, as usual, draft capital will go a long way.