A deep dive into Zero-RB: Is it ever the optimal strategy?
Zero-RB is a popular strategy in fantasy football leagues, having been popularized as a way to zag against the common refrain of hammering running backs in the draft. While it continues to gain popularity, I truly think that while it is an important strategy to know, it is not something you should ever set out to do. Rather than a pre-planned strategy, it is a backup plan. A way to make do when you are dealt a bad starting hand in the draft in the first 2 rounds of the draft. In my previous snake draft recap posts, I have consistently shown that teams that go Zero-RB reduce their odds of a championship. While I stand by my analysis, those posts were, fairly, criticized for how I defined Zero-RB. So today, I want to take a deeper look at Zero-RB. What is it? How can we define it? And is it ever really worth it?
This is going to be a longer post, so let's get to it.
What is Zero RB?
To take a step back first and make sure we are all on the same page of the general principles of Zero-RB. Zero-RB was a draft strategy popularized by Shawn Siegele in 2013. The idea is that running backs were being overvalued (due to a variety of reasons), leaving valuable wide receivers available early in the draft. After locking down the WR and other starting positions, you could then go and draft a large number of running backs who were undervalued for various reasons, whether that is an uncertain backfield, a talented handcuff, a pass catching specialist, or any other reason. While the team may struggle in the beginning of the season, as the year wore on, some of these high variance running backs would hit, and with the greater consistency at the WR position, you could have a juggernaut of a team at the end of the season.
Zero-RB was always meant as a zag to the common draft strategies and was thought to be more effective in some leagues vs others. League settings like full PPR and starting a 3rd wr are thought to make Zero-RB a better strategy. Additionally, how extremely you follow the Zero-RB mindset is up for debate. I have historically defined Zero-RB as no running backs selected in the first 5 rounds of the draft (which aligns with Shawn Siegele's original proposition), but some say you should wait 6, 7, or even 8 rounds before taking a RB. There has also been an offshoot of Zero-RB in recent years called Anchor-RB or Hero-RB, where you draft 1 stud RB in the first 2 rounds and then wait until late in the draft to target the same types of high variance RBs to fill the second slot. So today, we are going to look at these different definitions, along with different league settings to see if and when Zero-RB may be a winning strategy.
As with previous posts, I will be using public leagues from ESPN (2019-2022). I filtered leagues to only include leagues with 8, 10, or 12 teams and removed extreme team point totals to try to filter out some extreme leagues. At the end, I was left with ~15,000 leagues across the 4 years. As with previous draft posts, I will be reporting how making a draft decision (we'll get into those in a second) affects a team's odds of a championship. For each year and each condition, I calculated the conditional probabilities of winning the championship given whatever conditions we are examining. Also note that in all cases, I required at least 30 teams to have matched our settings for the probability to make the given graph.
As I mentioned, algorithmically determining that a team tried to go Zero-RB is a difficult thing to define. I could show you a lineup and you could probably make a guess, but defining hard rules is trickier. So instead of setting some thresholds, I am going to report the full range of a couple different metrics that we can use to define Zero-RB. The hope is the combination of these metrics may suggest scenarios for when a Zero-RB strategy is beneficial.
Round of 1st RB drafted: This should be obvious, but if you are going Zero-RB you should not be taking a running back early, what constitutes early is up for some debate which is why I will provide a range in the following graphs
Round of 2nd RB drafted: Similar to the round of the 1st RB, if you are prioritizing the other positions then this should be later. This also allows for the Anchor-RB strategy to be examined as a team may be taking their first RB early, but their second should be late.
Positional Rank of RB1 or RB2: This is just a different version of the last 2 metrics and should align, basically if you are emphasizing other positions, you should have worse positionally ranked running backs, either your RB1 (for Zero-RB) or RB2 (For Anchor-RB). Note, positional rank is based on ADP, not where the players finished at the end of the season.
Average Positional Rank of Top 3 or 4 WRs: I will report both, but this should be negatively correlated with the last 2 metrics. If you are emphasizing WRs you should have a number of good WRs and therefore your average rank of your top 3 or 4 WRs should be low (good) if you are drafting Zero-RB or Anchor-RB since this will be the core of your team.
Number of RBs and WRs Drafted: Some argue that a good Zero-RB strategy requires making up for the lack of top tier RBs with a large volume of running backs later in the draft such that you end up drafting more running backs than average. The opposite would be true for WR with 4ish studs drafted rather than the more balanced 5-6 WRs drafted.
The other aspect I will be exploring here is how different settings make a league more or less conducive to Zero-RB. To that end I will be comparing how PPR settings (0 vs 0.5 vs 1.0 point PPR) and the number of starting WRs (2 vs 3) change the effectiveness of Zero-RB.
Ok, enough of a preamble, let's look at some baselines. How does Zero-RB fair in average leagues?
Average League Settings
Round of First and Second RB Drafted
Line plots of the change in championship odds based on when the team drafted their first RB (Left) and their Second RB (Right). Different colors represent the different years in the dataset with the black line and shading representing the mean and 95% confidence interval across the years.
When we look at the average league, we see that you should be drafting a RB in the first round. That is the only way to ensure plus odds on average, though as long as you get a RB in your first 4 picks you aren't hampered that much. Now considering that most zero-rb advocates suggest not drafting a running back until round 6 or later, this does not look good for Zero-RB.
Anchor-RB faired a little better, with even or plus odds with your second RB being as late as round 6, but even then that is the least extreme Anchor-RB as you can go and your odds start to really drop if you wait later than that. While there is some variability, with a more extreme Anchor-RB strategy working well in 2021, it certainly is not a consistently winning strategy.
Positional Rank of First and Second RB drafted
Line plots of the change in championship odds based on the Positional ADP Rank of the first RB (Left) and Second RB (Right) drafted by a team. Different colors represent the different years in the dataset with the black line and shading representing the mean and 95% confidence interval across the years.
When you look at positional ADP rankings, we see the same story. You generally need a top 15 RB1 and a top 20 RB2 before the drop off occurs. Again, these are based on ADP rankings, not year-end finishes. And again if you are going Zero-RB its unlikely you are hitting these marks. I will say that Anchor-RB doesn't fair too badly here, with reasonable odds all the way out to a top 30 RB2, but you are still lowering your championship odds.
Average Positional Rank of top 3 or 4 WRs
Line plots of the change in championship odds based on the average Positional ADP Rank of the top 3 (Left) or top 4 (right) WRs drafted. Different colors represent the different years in the dataset with the black line and shading representing the mean and 95% confidence interval across the years.
The average ranking of your top 3 or 4 WRs tells the same tale. Specifically, that you can draft WRs that are too good! 3 top 10 WRs hurts your championship odds on average, as does 4 top 20 WRs. I am sure this is a reflection of the previous graphs because if you are drafting top tier WRs you are passing on RBs, but the story is the same, Zero-RB is not a consistently winning strategy.
Number of RBs and WRs
Line plots of the change in championship odds based on the total number of RBs (left) or WRs (right) drafted by a team. Different colors represent the different years in the dataset with the black line and shading representing the mean and 95% confidence interval across the years.
Here we see that balance is the key. You want a roughly even amount of RBs and WRs with no extreme bias one way or another. This is a weaker point against Zero-RB than the others, but again, not looking good.
So as a baseline we can see that frankly Zero-RB is not a consistently winning strategy, while Anchor-RB may be passable, but you are still making things harder for yourself. I need to be clear that this does not mean you can't win with them, just that managers have worse finishes on average. With that established, lets look at how some settings affect the strategy. For the following graphs I will be just showing the average performance across all 4 years, since they generally aligned.
Please note that when I am plotting the PPR settings, almost all of the leagues were some form of PPR, while some of the graphs include a little bit of data from standard leagues, the more robust comparison will be half vs full point PPR.
Draft Round of RB1 and RB2
Line plots of the change in championship odds based on when a team drafts their first (left) or second (right) RB. Half point PPR leagues are in orange, with full point PPR in green. Mean and 95% confidence intervals across the years are shown.
Our sample sizes are getting smaller here so there is going to be more noise, but once again, neither Zero-RB or Anchor-RB seem like a great strategy. The data still suggests you want to draft your RB1 in the first 4 rounds and your RB2 in the first 6/7 rounds, with better odds going to earlier picks for each regardless of PPR settings.
Positional Rank of RB1 and RB2
Line plots of the change in championship odds based on the positional ADP rank of the first (left) or second (right) RB drafted by a team. Half point PPR leagues are in orange, with full point PPR in green. Mean and 95% confidence intervals across the years are shown.
Again, we see positional rank match draft round. You want a top 15-20 RB1 and a top 30 RB2, PPR settings do not change our interpretation.
Average Positional Rank of Top 3 or 4 WRs
Line plots of the change in championship odds based on the average positional rank o the top 3 (left) or top 4 (right) WRs drafted by a team. Half point PPR leagues are in orange, with full point PPR in green. Mean and 95% confidence intervals across the years are shown.
Here we see some differences, but I am largely chalking that up to noise (Not many teams are able to get 3 top 5 WRs, but if you can, it seems to be advantageous in 0.5 PPR). Outside of the initial spike in half point PPR, this matches what we've seen. You are sacrificing your team by focusing on early WRs.
Number of RBs and WRs
Line plots of the change in championship odds based on the number of RBs (left) or WRs (right) drafted by a team. Standard leagues are in blue, half point PPR leagues are in orange, and full point PPR leagues are in green. Mean and 95% confidence intervals across the years are shown.
Finally, more of the same. you want a balance between RBs and WRs. Note I am largely ignoring the standard line in number of WRs, that extreme of a jump without the additional data makes me think its more noise than anything else. It is also only coming from one year of data which is why there is no error shading.
So, to sum up. PPR settings don't seem to make Zero- or Anchor-RB a winning strategy. You still need prioritize RBs early.
Number of Starting WRs
As I have shown previously, PPR only slightly increases the value of WR whereas increasing the number of starting WRs really boosts their value. Given that, will Zero-RB strategies fair better when starting 3 WRs?
Draft Round of RB1 and RB2
Line plots of how a team's championship odds change based on when a team drafts their first (left) or second (right) RB. Leagues with 2 starting WR slots are in blue and leagues with 3 starting WR slots are in orange. Mean and 95% confidence intervals are averaged across the 4 years.
While we only have a limited number of leagues that start 3 WRs, leading to a noisier line, overall, we do not see some huge advantage on waiting on RB. We are missing the key comparison point at Rd 5-7 so I may have to increase my dataset to better answer this question, but as I said, first blush doesn't wow me.
Positional Rank of RB1 and RB2
Line plots of how a team's championship odds change based on the positional ADP rank of the first (left) or second (right) RB drafted by a team. Leagues with 2 starting WR slots are in blue and leagues with 3 starting WR slots are in orange. Mean and 95% confidence intervals are averaged across the 4 years.
Here we start to see some support for an Zero- or Anchor-RB strategy. With 3 starting WRs, we see an significant increase when your first RB is around RB15. While this is not a complete zero RB strategy, it is the first hint we've seen towards an advantage to waiting to draft your first RB. I still think we need a larger dataset to make any definitive claims, but zero-rb is showing signs of life.
Average Positional Rank of Top 3 and 4 WRs
Line plots of how a team's championship odds change based on the positional ADP rank of the top 3 (left) or top 4 (right) WRs drafted by a team. Leagues with 2 starting WR slots are in blue and leagues with 3 starting WR slots are in orange. Mean and 95% confidence intervals are averaged across the 4 years.
Again, we see some signs of life when starting 3 WRs, with better odds from having better WRs, though again the data is noisier than I would like with only one year having data at the far left of each line.
Number of RBs and WRs Drafted
Line plots of how a team's championship odds change based on the number of RBs (left) or WRs (right) drafted by a team. Leagues with 2 starting WR slots are in blue and leagues with 3 starting WR slots are in orange. Mean and 95% confidence intervals are averaged across the 4 years.
Interestingly, we see plus odds for leaning into either RB or WR when starting 3 WRs. You want to hit either of the extremes according to this, though the data is less robust than previous graphs. That probably supports the Zero-RB strategy as a viable option.
While the data is a little less robust than other comparisons, it does suggest that Zero-RB and its offshoots are viable options in leagues with 3 WR slots in their starting lineup.
There are a couple of obvious limitations that need to be addressed. As with previous posts, I am not controlling for fantasy manager skill outside of the most basic (like not starting players on bye weeks). Zero-RB requires more manager skill as you are banking on hitting on high variance, late round RBs or a free agent RB to round out your team. Additionally, I do not know if these managers were trying to do Zero-RB or were just drafting and ending up there. As discussed, Zero-RB drafters aim for certain types of RBs to make the strategy successful and defining these RBs algorithmically would require an entire other blog post.
While Zero-RB is a strategy that is gaining traction, I think it has to be said that on average, it lowers your odds of a championship. To me, that says that you should never go into a draft planning to do the Zero-RB strategy (at least if you are maximizing your championship odds). Instead, Zero-RB is a break glass in case of emergency scenario. Additionally, while PPR settings don't seem to matter, being in a league that starts 3 (or more) WRs will give you a much better chance at succeeding with the Zero-RB strategy.
Happy Drafting All.