When To Draft RBs In Best Ball: Points Contributed

Author: Billy Jones

Introduction

Hey fantasy football fam, welcome back to my blog! As the best ball summer rolls on, I find myself diving deeper into the captivating world of Best Ball Mania II and III data, provided as part of the Best Ball Data Bowl. A few months ago, I stumbled upon an intriguing article penned by Hayden Winks of Underdog Fantasy. He explored the optimal timing for drafting running backs in previous Best Ball Manias, presenting appealing visualizations and thought-provoking analysis. Although I found it fascinating back then, I hadn't fully succumbed to the best ball obsession that now consumes me (100+ drafts complete and it’s not even July 4th). Fast forward to the present addicted state, I decided to revisit Winks’ article in hopes of finding some new insights now that I had a much deeper understanding of the best ball and draft market. As I got into the article once again, my curiosity was piqued, compelling me to wonder about what insights could be gained from a slightly tweaked perspective on the visuals of prior year's results.

So, if you happen to be a best ball data nerd like me, eager to unravel the levers to optimal draft strategies in BBMIV, you're in for a treat. Join me on this data-driven exploration into the world of production by position group. Let’s get started with running backs.

BBM Basics

For those who may be less familiar with Best Ball Mania (BBM) by Underdog, it’s a unique and immensely popular fantasy football tournament. Best ball is a fantasy football format where participants draft a team and then have no in-season management requirements like waiver wire additions or setting lineups. Instead, the highest-scoring players are automatically placed in the starting lineup, and leagues are decided based on cumulative season points rather than head-to-head matchups.

BBM takes best ball to another level with its distinct two-stage structure: the regular season and playoffs. During the 14-week regular season, teams compete against others in their draft, with the top two teams advancing to the playoffs. The playoffs then consist of a series of single-week DFS-style competitions, where teams from different drafts, potentially with overlapping players to your roster, vie for advancement to the next round.

Data Source

Before I jump back into analytics, I would like to acknowledge the data source. The data used for this analysis was obtained from Underdog Fantasy and is the basis for the Best Ball Data Bowl. There have been three BBM’s but the Best Ball Data Bowl competition states the competitors should only be using the BBMII and BBMIII data as the BBMI data is a bit of a mess, so I’ll be following the same rules here.

From a Different Lens: Points Contributed

To kick things off, I present to you my version of Hayden Winks' visualizations from his original Underdog Network post. However, I've added a twist by showcasing the graph in a sleek #DarkMode. This allows for a direct comparison between Hayden's work and my own, ensuring an apples-to-apples data that we are working with.

In Hayden’s visual, you'll notice that it depicts the average total points based on the cumulative number of drafted running backs on a team at that particular stage in the draft. This graph provides valuable insights into when it was optimal timing for drafting your first, second, and subsequent running backs in BBMII and BBMIII (isn’t it fun when optimal is different year to year!).

In Best Ball Mania II the most optimal running back draft strategy was 2 running backs off the start then 3rd being selected somewhere around 10 or 11. 

In Best Ball Mania III the most optimal running back draft strategy was 0 running backs through 6 rounds and then accumulating one’s running backs in rounds 7 through 10.

While Hayden's visual was indeed insightful and captivating, my curiosity led me to explore a different perspective. Instead of focusing on teams' total average points, I wanted to delve into the average points contributed to a team by players drafted as the team's RB(n) in each round. There has been considerable conversation about the running back deadzone in the best ball community as of late and I thought this visual would help look into this range of the draft.

Heroes and Average Joes

When examining the scoring profile of running backs in Best Ball Mania II and III, we observe an intriguing pattern. As Pat Kerrane aptly terms it, there is a noticeable drop-off in performance after the running backs categorized as the "legendary upside" tier. Moving beyond this initial drop-off, we encountered a remarkably flat tier of running backs in BBMII, spanning from Round 3 all the way to Round 11. During this massive range, the scoring profiles among these running backs showed minimal variance of the average score by round selected. In BBMIII, a similar huge flat tier emerged, yet, there was a noticeable anomaly within this tier. In Round 7 and 8 of the draft, we observe a spike in the scoring profile of running backs selected in those rounds.

Player Level Average Contribution

I hate only presenting averages as that often doesn’t tell the whole story of what happened. As such I wanted to go a level deeper and see what contribution was like player by player. To do this I used a box and whisker plot which had all of the individual player’s average contribution plotted. I am a big fan of box and whisker plots as they are rich with information such as mean, median, minimum, maximum, and the interquartile range (middle 50%).

In Best Ball Mania II, we observe the presence of 4 "legendary upside" running backs at the beginning of the draft putting up huge figures in Jonathan Taylor, Austin Ekeler, Najee Harris, and Joe Mixon. Later in the draft we see two “deadzone defying” running backs in James Conner and Leonard Fournette, who were drafted anywhere from round 7 to 13. These players beat their expectations and delivered notable season long production, despite being drafted in the deadzone of the draft. 

Best Ball Mania III, we witness a similar trend with the “legendary upside” running backs in the first three rounds putting up huge figures, Austin Ekeler, Christian McCaffrey, Derrick Henry, Saquon Barkley, and Nick Chubb. In this year, it was Josh Jacobs who broke the mold and produced a legendary upside season from the depths of the deadzone. While the quest for the next Josh Jacobs captivates the attention of many, it's crucial to recognize the presence of some more “deadzone defying” running backs in Tony Pollard, Miles Sanders, and Rhamondre Stevenson. These players all delivered significant value to drafters, much like Conner and Fournette did in BBMII, even if it wasn’t the nuclear outcome of Jacobs.

A general thought from this analysis is that there are opportunities to acquire a highly productive running back later in the draft exists, it's important to note that the distribution of outcomes in the first round differs significantly from the subsequent rounds. The interquartile range floor and ceiling are notably higher in the “legendary upside” tier highlighting the importance of understanding the expected production variance associated with drafting running backs across different tiers.

How I am Playing the RB Market

- There is a huge distinction between the "heroes" and the "average Joes" in the running back landscape. Drafting heroes brings the legendary upside that Pat Kerrane is famous for. These players can be million-dollar players on your roster. In the current wide receiver centric Underdog market one can get running backs with that legendary upside in rounds 2 and 3 which feels pretty nice. In BBMII if you landed 2 running backs at the 1/2 turn that was the optimal strategy and this year it feels like that is now the 2/3 turn.

- Not everyone can be a hero, and that’s ok. While it's easy to assume you must find the next Josh Jacobs, breakthrough players who significantly exceed expectations exist in this range every year (2021 – Fournette, Conner, 2022 – Pollard, Stevenson, Sanders). 

- If the running back deadzone is a big flat tier as shown above, then I want to be underweight on the early part of the deadzone and overweight on the later ones. As the rounds get later, the floor, ceilings, and median outcomes for the deadzone players don't reduce in line with the reduction in draft capital cost. In a world where we are looking to maximize our roster production, we should be looking how to get the most points contributed to our rosters at the cheapest price possible. 

- Depending on the tournament entry structure I will be building my running back rooms differently. In tournaments where players can enter a large number of entries, e.g. BBMIV or one of the Puppy tournaments with 150 entries per contestant, I want to build my teams around optimal 95th percentile outcomes, not most likely or median. In these settings I will be overweight on Hero and Zero RB strategies to hopefully hit big on the upside of the deadzone. In tournaments where the max entry pool is much smaller, I will be doing the inverse and structuring rosters around bets that are more likely to realize as I will be comfortable that there will be less 95th percentile rosters to have to combat in the playoff rounds.

Conclusion

In conclusion, exploring the running back contributions in Best Ball Mania II and III from a different perspective was an insightful and fun exercise. While we uncovered valuable insights, it's important to remember that this analysis primarily served as a descriptive exploration. When approaching the current best ball market, it is essential to combine this information with current market factors to effectively construct your running back lineup. I also want to extend a special thanks to Hayden Winks for the inspiration and consistently fantastic work for the Underdog Fantasy Network. Stay tuned for more fantasy football analysis but until then, may your fantasy teams thrive, and your player takes never be wrong!

*This blog post was enabled by ChatGPT. The text was generated by me, and the content is my own, but some sentences and wording were provided by the model. I take full responsibility for all information produced in this blog. More information about OpenAI and their technology can be found at https://openai.com.*