Hello everyone!

I was listening to The Fantasy Footballers earlier this week discuss teams that did not have a running back drafted among the first 24 RBs, but finished inside the Top 24. The example brought up was Javonte Williams last year, a late-round RB that ended up being a huge value.

They brought up that about five NFL teams a year end up with a running back finishing in the Top 24 despite not having a RB drafted inside the Top 24, and that most of them come from good offenses. That got me thinking, how many teams don’t have a running back drafted in the Top-24 on average? Where should we be looking to increase our chances of hitting?

So, to the Footballers, a big thanks to you for inspiring me to look into this area further. Here’s to them and their show!

For this study, I went and grabbed all fantasy-relevant running back seasons since 2020 (6+ PPG, 8 games played) from Stathead and fantasy consensus ADP from FantasyPros. I already had team offense data from previous studies (studies you, the reader, are acquainted with), so I had a good start.

I then paired each running back season with the applicable ADP, determined which teams didn’t have a running back drafted inside the Top-24, and then which DID have a running back in the RB25-48 range. Why RB48? Well, I need to stop the data somewhere. If I did all the way to Round 18 or 20 in ADP, as you see in bestball formats, you’re drafting backups of backups. That’s not helpful. Most drafts in fantasy end about Round 15, and should end at Round 13 if you subscribe to the “draft kicker and DST last” style, as I do.

Further, there are 32 teams in the NFL, giving us 32 “RB1’s”. The other 16 of the 48 are either the premium handcuffs (Blake Corum, Tyler Allgeier) or are running backs we are drafting later because of an ambiguous situation, such as Jacory Croskey-Merritt and Rachaad White in Washington. With how teams utilize running backs these days, including most of the relevant split backfields in our study sample to try to capture the one who “won out,” seems reasonable.

From there, it was a lot of sifting through the data to find out relevant takeaways.

Since 2020, an average of 12 teams a year do not have a running back drafted inside the Top-24 running backs. It’s been as high as 14 and low as 10. As the Footballers found, an average of five teams end up with a Top-24 fantasy running back by the end of the season. Interestingly, if you expand it to include all drafted running backs, a little over half (6.2 teams a year, to be exact) of the teams end up with a Top-24 running back.

Of our sample set of running backs from teams that did not have a Top-24 ADP RB- let’s call them the “Late Values” for short - 63% of them come from offenses that are in the top half in the NFL, the other 37% from the bottom half offenses.

All of that is well and good, but that doesn’t predict things. It’s merely describing what’s worked before. We should be looking at offenses that are projected to improve; that is clear. But can we extract anything more from this data?

The problem with looking simply at what has worked is that offenses change every year. We have to do a lot of projection, and in some cases, we’re pretty good at it thanks to the team's track record and such. The Lions and Bills should be good, for example. We also believe the Vikings will improve after a down season on offense. But again, that’s projection. There is a place for that, and it is useful here, but I want to find another way to spot potential sleepers.

That’s where the previous year's team offense comes in. Using previous season data, we can get an idea of whether or not a team is due for some improvement, like we did when looking at team offense regression a few weeks ago.

When we pair the Late Values fantasy finishes with their team's offensive production from the year prior, we find that, of the 29 players that qualify (on a team without a Top 24 drafted RB, selected between RB25-48, and finished a Top-24 RB):

I thought I had found a eureka moment. This is it! Targeting running backs on offenses that ranked in the Bottom-10 from the previous season, because regression in the positive is likely coming, is the way to go. But wait, while this does tell us that those from a previously bad offense make us the largest part of our list of players who hit, it doesn’t tell us the hit rate and who didn’t hit.

Think about it this way, we have two groups of players, and three in each group scored 14 PPR PPG. But the first group only has 6 players in it, the second has 15. The number of players who hit in each group is the same, but the hit rate is different.

🔎 To solve this problem, I then had to layer on exactly how many players were drafted in our Late Values range, RB25-48 in ADP, regardless of whether they hit or not. I then looked at how the hit rates changed.

When looking at how many players were drafted from each type of offense, I found that 42% of RBs drafted from a Top-10 offense hit, and a nearly 52% hitrate among RBs drafted from Bottom-10 offenses.

Further, when you look at running backs with a positional ADP of RB25-30 from a Bottom-10 offense, you find a 66% hitrate (15 player sample size)! Moving further back to RB31-36, it’s a 50% hit rate, but it’s also only a six-player sample size.

Past RB36, Top-10 offenses maintain their 42% hitrate from RB37-48, while running backs in Bottom-10 offenses see a rapid decline down to a hit rate of just 25%.

TLDR: When looking at running backs who fit our criteria of not having a teammate drafted within the Top-24 at the position, and are between ADP RB25-48, it is more advantageous to draft a RB from a Bottom-10 offense when looking in the RB25-36 range, and running backs in Top-10 offenses afterwards. 📝

Teams that finished as a bottom 10 offense in 2025 who currently don’t have an RB drafted inside the Top 24 are: Carolina, Minnesota, and Tennessee. And currently, Chuba Hubbard, Tony Pollard, Jonathon Brooks, Jordan Mason, and Aaron Jones are being drafted before RB48, but I’ll have an honorable mention, Tyjae Spears, at RB49.

Brooks, Jones, and Pollard are my current favorites to grab out of that group. Hubbard is volume-dependent and isn’t an effective pass catcher. Mason is not a pass catcher and is reliant on either touchdowns or an Aaron Jones injury to be relevant.

🟣 Jones is older, but still fairly efficient when he gets volume, and he can do it on the ground and through the air.

While many might feel let down by Pollard, as the stink of the 2025 Titans offense is still on him, he’s not a bad bet either. He ended 2025 on a high note, finishing as an RB2 or better in four of the last five weeks of the season, including 28 and 18-point weeks in Weeks 14-15. 🔥

🐈‍⬛ Brooks is the big unknown here. What’s crazy is that while he is going into his third NFL season, he is still just 22 years old, younger than TreVeyon Henderson, RJ Harvey, and Omarion Hampton, and is the same age as several of the 2026 rookies. If he can get back to his pre-injury self, the Carolina backfield could be his for the taking, as he is the more dynamic pass catcher between him and Chuba Hubbard, and he showed some nice get-up while at Texas. He is also cheaper than Hubbard, making me want to take the cheaper bet. However, this could easily turn out in Chuba’s favor, and he has shown the ability to handle a large workload when asked to take it on.

🐆 While I am using full PPR ADP sourced from Fantasy Pros, I do want to mention someone else: Bhayshul Tuten. In half-PPR scoring, he is being selected outside of RB24 territory (just barely). He is in a Jacksonville offense that was Top-10 in offensive TD scoring last year, so he’s worth mentioning here.

That’s all I have for today! Don’t be surprised if I bring this study back up again next year; this could be fun. I could bring larger sample sizes as well and look at team RB1’s vs team RB2’s. There are so many layers to explore!