How to Spot a Fantasy Football League Winner: RBs

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The phrase “league winner” gets bandied about a lot in fantasy football circles, often carelessly. Sometimes, analysts use this phrase as nothing more than an attention-getter to hype some mediocre player they love. But when used properly, there is truth to this concept – the idea that one single player can dominate for your team enough to nearly guarantee, on his own, a championship for your fantasy team.

Of course, no player can truly win a fantasy championship alone. Even Christian McCaffery’s historic 2019 season, where he scored a ridiculous 413.2 fantasy points, was only enough to get 48% of his managers into fantasy championships (still an absurd number, by the way). So, fantasy managers still must put together a solid team around a “league winner”, work the waiver wire, and play the matchups. Nevertheless, rostering some players undoubtedly gives fantasy teams an increased chance at a fantasy championship, just like McCaffery nearly gave his managers a 50-50 shot in 2019.

From my analysis of the past five years, league-winning players typically separate themselves from the pack. That means that the top 1-3 players each year, at any given offensive position, generally score at least 30 points more than their next closest competitor, where the end-of-year rankings start to bunch up. That’s good! We want our “league winner” not just to score a few more points than RB3 or WR2; we want them to score way more points. That means these types of players really do have “league winning upside”.

In this series, I define “league winners” for each of RB, WR, QB, and TE, I analyze historical league winning seasons at all four positions, and I use history to try and spot league winners for 2021. I can’t wait to take you along for the journey. I hope you enjoy the series, now go win some fantasy championships.

Defining a League Winning Running Back

As I said above, I studied the fantasy finishes of the running back position over the last five years. I wanted to find players who stood out, not just finished RB1 overall, but player(s) who separated themselves from the crowd. What I found was that very few running backs hit the 300 fantasy point threshold (in 0.5 PPR scoring), and those who did, separated themselves from the rest of the top 12 running backs. Thus, this threshold worked quite well in establishing an objective definition of a league-winning running back.

By setting that 300 fantasy point threshold, I was able to generate twelve instances of a league-winning running back in 5 years, which also “felt about right” (about 2 per year).

League Winning Running Backs
Ezekiel Elliott (2016)
David Johnson (2016)
Le’Veon Bell (2017)
Todd Gurley (2017)
Alvin Kamara (2018)
Christian McCaffrey (2018)
Saquon Barkley (2018)
Todd Gurley (2018)
Christian McCaffrey (2019)
Dalvin Cook (2020)
Derrick Henry (2020)
Alvin Kamara (2020)

This is our set of league winners. Now let’s see if we can find out why these players ended up as league winners.

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Historical Analysis of League Winning Running Backs

Now that we have a nice definition and a decent sample size, we can start to look at these players to decide what is important in predicting fantasy league winners.

In my research leading up to this article, I generated a list of eighteen possible statistical or other factors that explain why these twelve instances, represented by nine different running backs, resulted in a league-winning season. Those eighteen factors include touches, catches, carries, targets, opportunities, ADP, Broken Tackles, Yards before Contact, Percent of Yards before Contact, Team wins, PFF’s End of Year OL Rankings, PFF’s Beginning of the Year OL Rankings, Offensive Plays, Run-Pass Ratio, QB teammate’s fantasy finish, Snap Share, Age, and Year in the NFL. In other words, I analyzed a ton of data, so much data in fact that it doesn’t fit nicely onto one chart.

League Winning Running Backs Fantasy points Touches Catches Carries Targets Opportunities
Ezekiel Elliott (2016) 309.4 364 32 332 39 371
David Johnson (2016) 367.8 373 80 293 120 413
Le’Veon Bell (2017) 299.1 406 85 321 106 427
Todd Gurley (2017) 351.3 343 64 279 87 366
Alvin Kamara (2018) 313.7 275 81 194 105 299
Christian McCaffrey (2018) 332 326 107 219 124 343
Saquon Barkley (2018) 340.3 352 91 261 121 382
Todd Gurley (2018) 342.6 315 59 256 81 337
Christian McCaffery (2019) 413.2 403 116 287 142 429
Dalvin Cook (2020) 315.8 356 44 312 54 366
Derrick Henry (2020) 323.6 397 19 387 31 418
Alvin Kamara (2020) 336.3 270 83 187 107 294
League Winning Running Backs ADP Broken Tackles Yards before Contact % of yards are before contact Wins PFF EOY OL Rank PFF BOY OL Rank
Ezekiel Elliott (2016) 8 36 693 42.4% 13 31 32
David Johnson (2016) 4 44 502 40.1% 7 6 23
Le’Veon Bell (2017) 2 44 455 35.9% 13 20 29
Todd Gurley (2017) 20 39 522 40.0% 11 26 14
Alvin Kamara (2018) 6 28 464 52.5% 13 24 26
Christian McCaffrey (2018) 13 22 633 57.6% 7 15 11
Saquon Barkley (2018) 7 43 571 43.7% 5 11 7
Todd Gurley (2018) 1 25 634 50.7% 13 26 22
Christian McCaffrey (2019) 3 30 513 40.0% 5 14 22
Dalvin Cook (2020) 7 39 801 51.4% 7 6 9
Derrick Henry (2020) 8 35 954 47.1% 11 17 17
Alvin Kamara (2020) 4 35 526 56.4% 12 24 30
League Winning Running Backs Plays Pass-Run Ratio QB Fantasy Finish Snap Share Age Season Touchdowns
Ezekiel Elliott (2016) 982 50.8% 6 67 21 1 16
David Johnson (2016) 1014 55.4% 19 84 25 2 20
Le’Veon Bell (2017) 1027 57.4% 10 85 25 5 11
Todd Gurley (2017) 972 53.3% 12 76 23 3 19
Alvin Kamara (2018) 990 52.4% 8 63 23 2 18
Christian McCaffrey (2018) 979 57.5% 12 91 22 2 13
Saquon Barkley (2018) 937 62.2% 17 83 21 1 15
Todd Gurley (2018) 1027 55.3% 7 75 24 4 21
Christian McCaffrey (2019) 1019 62.1% 93 23 3 19
Dalvin Cook (2020) 984 52.4% 11 62 25 4 17
Derrick Henry (2020) 1006 48.2% 7 66 26 5 17
Alvin Kamara (2020) 1016 51.4% 61 25 4 21

Finally, I plotted each of the 18 factors against their fantasy points scored (and calculated the R2 of each plot) and also calculated the average value of each column from above. I am going to use the term R2 quite a bit below – without getting too deep into the mathematics, just understand that R2 is basically a measurement representing variance. We can use it to measure how closely two sets of data (e.g. touches and fantasy points) correlate with each other linearly.

Here is what I found.

  • Touches, Carries, and Opportunities do not correlate that well with fantasy points scored among our league winners. Fantasy football is a game that immensely rewards players for scoring touchdowns. As we have long known, getting a handoff is not particularly valuable as touches go.
  • No surprise, touchdowns correlated quite well (R2 of .26) with fantasy points scored among our league winners, but touchdowns actually correlated lower than targets (R2 of .313) and approximately the same as catches (r2 of .256)! When considering this factor with the lesson about carries and touches, it’s interesting to note that Lev Bell had one of the lowest league-winning fantasy outputs (in fact he only is on this list because I rounded up), but had 406 touches – the most of any of our twelve instances. Meanwhile, Alvin Kamara was a league winner twice with fewer than 280 touches. Still, 270 touches appear to be an outlier in terms of insane efficiency (Kamara is the only running back on this list to be a league winner with fewer than 315 touches) – we likely still want someone likely to touch the ball at least 320 times, just to be safe. Also, touchdowns have generally been considered hard to predict, whereas targets are easier to project. That’s good news.

Otto Greule Jr/Getty Images

  • No League Winning running back came after pick 20 in ADP, and only two players came after pick 8. If we remove the two “outliers” who had ADPs of 20 and 13, the average league-winning running back was taken at pick 5. That means that fantasy drafters are quite good at drafting league-winning running backs. It also puts a strong emphasis on trying to get a top 5 pick.
  • The oldest league-winning running back was 26 (Derrick Henry last year), and the latest into a running back career was their fifth season. Meanwhile, the average age and experience level was 23.5 years old in their 3rd season. It’s safe to say that we are generally looking for players age 24 or younger going into, at most, their third year.
  • Team wins and QB teammate fantasy finish correlated surprisingly well, particularly QB teammate finish (R2 .435!). I assumed that a teammate throwing a lot of touchdowns wouldn’t bode well for a fantasy running back. Instead, having a strong performing fantasy QB as a teammate is a big indicator of league winning upside. We also prefer running backs who play on NFL teams who are going to win 9 or more games (probably 10 in the 17-game season).
  • Team Offensive Plays had almost no correlation with fantasy points scored among our league winners, but the run-pass ratio did have a strong correlation – in the opposite sense that you’d expect. Fantasy points for league-winning running backs actually correlate positively with teams that pass more heavily (see graph below).

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  • Unfortunately, neither pre-season nor post-season PFF OL rankings had much correlation with fantasy points scored, but the good news is that pre-season PFF rankings correlated better. This is probably the only actual data we will definitely have before trying to draft our 2021 league winner. Still, a .09 R2 is nothing to write home about. Also, percent of yards before contact, which is a stat I invented as an attempt to objectively measure offensive line strength, turned out to be a fruitless attempt to predict league winners – this data plot actually generated a negative trendline, mostly because Christian McCaffery and Derrick Henry totally skewed the results. In the end, I think that the offensive line is just not as important as we think.
  • Finally, snap share correlated strongly (nearly .3 R2 ). The average snap share was 75%, but I think we can comfortably say that 67% playing time will be sufficient in the modern NFL (Christian McCaffrey‘s ridiculous 91% and 93% snap rates skew this average).

I know that’s a lot to take in, but I had to “show my work”. I will try to distill what I found into something more digestible.

  • A league-winning running back is going to be a heavily targeted, pass-catching running back (80+ targets, 65+ catches) who still manages to touch the ball around 320+ times.
  • A league-winning running back is going to be drafted in the top-8 picks, but likely within the top 5.
  • A league-winning running back is usually younger than 26, and probably in his 2nd or 3rd year. Rookies have been league winners, but it’s a rare occurrence.
  • A league-winning running back will be on the field about 67% of the time.
  • A league-winning running back plays with a good QB, from a fantasy perspective, and plays for a team likely to win more games than they lose.

Now, let’s use the UDK’s projections, the UDK’s ADP, and Vegas win projections to see if we can find a league-winning running back for 2021!

Who is the 2021 League Winner?

Sadly, the answer here is pretty easy. It’s Christian McCaffrey. Andy has McCaffery projected for 110 catches and 413 total touches, his ADP is 1.01 and unlikely to change, he’s only 25, and he never comes off the field. His QB is unproven in this different, non-Adam Gase offense, and Carolina is only projected for 7.5 wins. But bad quarterback play and the bad team didn’t prevent him from scoring over 400 fantasy points in 2019, so I’d be unlikely to bet against him if he stays healthy.

But McCaffrey is too easy – the low-hanging fruit. Let’s really dig in here. We typically see two league winners per year, so who else is it going to be?

If Saquon Barkley were healthy, he’d be the next, most logical answer. He is also heavily targeted, currently being picked in the top 5, never leaves the field, and fits our age/year criteria. But notice that none of our twelve instances was a league winner the year after an ACL tear. We have plenty of players who have recovered from ACL injuries in the sample (Lev Bell tore his in 2015, Cook tore his in 2017, Gurley tore his in college in 2014), but each of those players who recovered from a major knee injury was a few years removed from the injury when they exploded. So I rule out Barkley.

That means we need to dig deeper, and I have two guys who meet most of the criteria we previously defined.

Aaron Jones

Jones plays for a good team, he has a fantastic quarterback, and he just barely qualifies from an age perspective (coming into age 26). But here’s the kicker: Jones doesn’t have to compete with Jamaal Williams for targets anymore. There isn’t a huge sample size of games where Aaron Jones played when Jamaal Williams didn’t, but the numbers are significant.

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In games where Jamaal Williams doesn’t play, Aaron Jones sees almost two more targets a game, leading to a pace of 83 targets per year. That’s right on par with what we need out of our pass catches. Certainly, A.J. Dillon will take some of the “Jamaal Williams role”, but these numbers indicate a much bigger passing game role for Mr. Jones.

Austin Ekeler

Again, a slightly older running back, but this is only his third “full season” (he was used in a part-time role his first two years). I am going to discount his age as a result of having less “tread on the tires”. Everywhere else, Ekeler fit our definition of a league-winning running back To. A. Tee. For example, when he returned from injury last year, he was on pace for 128 targets!

Furthermore, Justin Herbert looks to be the real deal, and you should know by now that I love the Chargers to “make the leap” this year, which should increase Ekeler’s touchdown scoring opportunities. I’ll be drafting Ekeler everywhere I can in the early second round.


Well, that wraps it up for the Running Back Position. Stay Tuned this whole month as I will do a similar exercise with WR, TE, and QBs! Now, go win some championships!


Nate Henry (the author) says:

Thanks for the comments everyone:

salhaney: In split/Out of Split is written in fine print below the two tables: In split: Ekeler’s first half of the season; out of split: Ekeler’s second Half of the Season

RE: Zeke fits pretty well. He’s on the older side of things. He was very much in consideration!

Tim Berry: A lot of this data comes from the very awesome, very free A lot comes from PFF, and some comes from Also, some of the data I calculate myself using data from those databases

lenny_aponterosario says:

This was an amazing read!

Sean Lindy says:

um… these analyses are amazing!

RE says:

What about Zeke? How well does he fit this criteria?

rs_sully says:

Wow, this article is fantastic. Thank you! Very excited to see the other positions, and how best to attack the draft.

salhaney says:

What does in split and out of split mean?

Tim Berry 🍓 says:

Wow! I am Very Impressed by your work! How do you find all the stats to compare going back 5 years? Or is that a trade secret? Nicely done! You mentioned that you wanted to show your work, yet after reading I could not find who wrote this or how to “Follow” you. Please let me know how to continue to appreciate your work.
Thank You!

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