Super Best Ball: Assessing Positions and Rosters Using Weekly Hits and Surplus

Take your pick of unconventional but intriguing combinations to use as an analogy, the el Camino, the mullet, light beer, or flip flops with bottle openers. Now insert Best Ball (BB), which is all the fun of drafting without the sweat of roster management in season. In this sense, you could expand your fantasy football portfolio to endless draft-and-hold leagues just to glance at the scores each week in hopes that your teams had a fortuitously small ownership percentage of the various 1st round RBs that had hit IR by week 5. BB was meant to ease the load of transactions and lineup setting, but it unveiled a unique and entertaining scoring format that could be utilized with almost any league type. Behold, the convergence of superflex (SF), BB, and dynasty.

The available content concerning the overlap of SF, BB, and dynasty is scant. We are blessed to have a partial startup draft case study, blogged by JJ Zachariason (Twitter Invitational Startup Draft). This league had unique starting roster positional requirements, but it was probably as close as we will get to near full coverage and commentary of an analyst draft in a format we might play. There are some introductory articles concerning BB and dynasty, but they generally convey topical BB strategy tropes like “boom or bust” and “quantity over quality,” without much detailed explanation of how to apply these concepts. There is a glimmer of hope, however, as Dynasty League Football (DLF) has a small repository of BB content geared towards dynasty (DLF BB Archive). Specifically, Nathan Powell wrote two informative pieces that sully the waters of ignorance with thoughtful content to help dynasty managers dipping their toes into BB (BB Dynasty Strategy and Dynasty BB Q&A). He discussed the role of depth and answered provoking questions on frankensteining multiple lower quality players to reach the production value of elite players, while minimizing associated draft cost. The real pearl of wisdom was that trade values are thusly skewed away from many-for-1 monster packages. However, his player comparison example, utilizing points per game (PPG), is not completely trustworthy in the BB format. The following is an alternative approach for escaping the player-focused mentality of fantasy football to a purely positional-output focus. This means less attention to Justin Jefferson as your WR1, but rather your WR1, composed of scores from several players that could include Justin Jefferson.

Difficulties Examining Frankensteins

Powell’s player comparison is an exercise to highlight the nuance of BB versus traditional scoring in fantasy football. It is not intended to solve team construction and player values, but there is a likelihood that his suggestion could be construed in this manner. Within his Q&A article he discussed the potential to combine the RB16 and RB17 to create a PPG output that would approximately frankenstein the RB8. It is superficially pleasing, but there remain some underlying concerns.

In a dynasty format with expansive rosters, the team with the actual RB8 will have other RBs that enhance the value to greater than RB8. The frankenstein is automatic in BB, and every manager is afforded that luxury. Depth enhances strength in SFBB dynasty, but in most cases, it cannot altogether replace it. The RB16/17 owner also needed to utilize two roster spots to achieve the same results as a single spot for the RB8 owner. Additionally, the RB8 owner would be able to roster another player, maximizing point scoring potential with roster optimacy. As this scenario unfolds, it becomes clear that the starting roster spot (RB1, WR1, TE, etc) is the frankenstein we are trying to piece together. However, it is not clear how to properly evaluate players using the conventional measures of PPG and total fantasy points when only the valuable, or elevated weekly scores are relevant.

Weekly Hits

I endeavored to find a cleaner method of player and team comparison to use for my SFBB dynasty league. I came back to a hypothesis I had during the season; the weekly projections for our teams were inadequate. The site simply used individual projections and chose the optimal lineup for that week. How was this accounting for the optimization of the lineup? BB means best scores; I am looking for projections of the high range of scores likely generated from my pool of players at a given position. If I have 10 WRs rostered, I can reasonably expect that slightly better than 1.5 out of 10 WRs will score greater than +1 standard deviation from the mean, slightly better than 3 out of 10 WRs should score above the mean projection but within +1 standard deviation, and the remaining WR scores will follow symmetrically below their respective projections (I am applying the 68-95-99 rule for standard distributions to generate my WR expectations, however, it will become clear that this is a conservative estimate of the elevated score range). Given that 4.5 of my 10 WRs figure to perform above their projected score, with 1 scoring well greater than the mean, I would hypothesize that we should expect the sum of the resulting optimized scores to be significantly greater than the sum of the projected optimized scores. The lone caveat is that perhaps your lowest projected players are the ones who perform above expectations, such that even their high range is not better than mean projections for your more valued players. To counter this argument, there is a significant right skew inherent to the distribution of scores because of the closed minimum range (0) and open maximum range. This would indicate that the positive range of score outcomes will be markedly greater than the detriment of the negative range outcomes. An example of this could be an RB with a mean projection of 15.9 pts for the week, but ultimately scores 41.2 pts. There is no equivalent in the negative range because of the 0 baseline (+25.3 vs. -15.9).

After discussing this with a trusted math and statistics expert, I sensed that my projection quest was an unrealistic task. It was too complex. I was not trying to create an AI program to rule the world of SFBB, I just wanted to look at players, positions, and rosters with clarity. Eventually, I decided a less restrictive, global approach to player and positional production would be ideal. Thus, I began to delve into the idea of weekly hits, which was the number of times during a fantasy season that a player registered a meaningful production week at their position. This would be tracked based on the number of roster spots per position, such that a hit at WR1 would be considered a top 12* weekly finish at the position, while a hit at WR2 would be considered a 13-24th weekly finish at the position, and so forth (*This assumes a 12-team league. This number would adjust to match the size of any given league.). Here is a comparison of WR corps from two fictitious teams evaluated for a traditional format (draft capital for each player taken from my May, 2020, SFBB dynasty startup draft):

Team WR StrongStartUp Capital (Rd)2020 Fantasy Points2020 PPG
Tyreek Hill2328.921.93
AJ Brown3247.517.68
Mike Evans4248.615.54
Deebo Samuel680.711.53
Michael Gallup9173.310.83
DeSean Jackson1844.88.96
Team WR MehStartUp Capital (Rd)2020 Fantasy Points2020 PPG
Tyler Boyd7192.812.85
Diontae Johnson10221.814.79
N’Keal Harry1173.95.28
Brandon Aiyuk13184.515.38
Tee Higgins14194.612.16
Chase Claypool15214.913.43
Allen Lazard1797.89.78
Corey Davis18191.413.67
Demarcus Robinson23107.66.72

The difference in build is clear, and the point discrepancy is vast for Team Strong’s starting 3 and whoever was the starting 3 for a given week by Team Meh. The difficulty for Team Meh is deciding who to play each week, and although streaming matchups could workout favorably, there are seldom cut and dry solutions to these start-sit scenarios. Some of these players had excellent seasons but the manager may have missed the boat on some big scores like Chase Claypool’s monster 4 TD game and Corey Davis, whose resurrection probably earned him starting nods right when AJ Brown returned to take away target volume. The bonus for Team Meh is that the value of several players dramatically increased after one season, which will allow for maneuvering in the market. Now look at the weekly hits breakdown for both teams and analysis from a BB perspective:

Team WR StrongStartUp Capital (Rd)WR1 WHWR2 WHWR3 WH
Tyreek Hill2742
AJ Brown3531
Mike Evans4451
Deebo Samuel6110
Michael Gallup9301
DeSean Jackson18011
Team WR MehStartUp Capital (Rd)WR1 WHWR2 WHWR3 WH
Tyler Boyd7331
Diontae Johnson10612
N’Keal Harry11001
Brandon Aiyuk13341
Tee Higgins14323
Chase Claypool15243
Allen Lazard17111
Corey Davis18323
Demarcus Robinson23011

The utility of depth is now more apparent in BB, as Team Meh suddenly looks like the more valuable WR group with respect to the Totals for each weekly hit. This is the indication that BB can be more of a numbers game, if strategy is applied effectively. Despite investing 3 extra picks at WR, Team Meh spent considerably less quality capital. Consider the allocation of premium resources; Team Meh used picks 1-6, 8, and 9 (8 total) on some combination of QB/RB/TE. Team Strong used picks 1, 5, 7, 8, 10 (5 total). Think of what this means from a construction standpoint! If Team Strong elected to use their picks in a balanced fashion, they would likely be drafting QB3+ and RB3+ from beyond the 10th round! From the same draft, the best QBs and RBs passed the 10th round were Cam Newton (while still unsigned), Ryan Fitzpatrick, Tyrod Taylor, Jameis Winston (signed as backup in New Orleans), Antonio Gibson (prior to Derrius Guice derailment), Kareem Hunt, Ronald Jones, AJ Dillon, Tarik Cohen, Sony Michel, Darrell Henderson, Chase Edmonds, Damien Harris, and James Robinson (prior to Fournette release). Through a little over 1/3rd of the draft, these were your best remaining players available at these positions, and the two best options, Gibson and Robinson, didn’t have the obvious path to volume that would later improve their ADP. Meanwhile, Team Meh could have built 3QBs and 4/5RBs that would be incredibly formidable relative to the handful drafted by Team Strong to that point. Team Meh has leveraged quantity and quality appropriately with draft capital.


Now that weekly hitscould be used to indicate the instances where player scores were valuable enough to be applied to the starting lineup, it is useful to identify other information that this brings to light. Given a 16-week fantasy season, an average team should have roughly 16 weekly hitsfor each starting roster position to ensure they are not losing ground to other teams. Excellent teams will have a positive surplus of weekly hitsat some positions where they hold a significant advantage. For example, Team Strong and Team Meh both held positive surpluses at the WR1 position (+4 and +5 respectively). The surplusis a monumental factor in identifying strength and weakness as it signals whether you can, for example, push RB1 weekly hits into the RB2 position or must use QB2 weekly hitsin the QB1 position. The surplus also signals how well a team can produce at flex positions, as these become the leftover scores that were not necessary for the isolated starting position requirements (WR3/RB2/TE vs Flex1/2). There is also the consideration that weekly hits are finite, such that a positive surplus for one team results in a shortage elsewhere in the league. To create a roster analysis, group all the players by position and sum the weekly hits per each individualized starting roster spot. Below is a roster analysis of Welcome to the Jungle, a team from my SFBB dynasty league, (*The SF is treated as a QB2 for the breakdown. The starting lineup consists of the following positions: QB, RB1, RB2, WR1, WR2, WR3, TE, SF, Flex1, Flex2):

(s = Surplus; amount greater or less than 16. ~ = Surplus not needed as QB cannot be used beyond SF spot.)

Welcome to the Jungle had an excellent season due to the positive surplus at QB1 and no significant negative surpluses. This team built a balanced foundation around a centerpiece of QB strength. The team finished 3rd in the playoffs and was consistently in the top third of the standings for the entire season. Moving forward, this team has no weaknesses to address but rather how to compile more strength. Note that no single QB or position player could generate a positive surplus by themselves.

The Art of Best Ball

The contrast between traditional dynasty leagues and BB dynasty is akin to comparing two classic video/computer games: Mortal Kombat and Civilization. In traditional dynasty, the handpicked, best players from your “realm” are pitted to compete against the handpicked, best players from your opponent’s “realm.” Everyone else on your roster is left to wonder whose realm will be vanquished and whether this fantasy football thing is reallyall it’s cracked up to be? In BB dynasty, every piece of your budding fantasy civilization plays an important role in your quest to build an empire. The fantasy civilization that neglected to build a powerful army to defend its borders will fall just as easily as the civilization with an impressive army, but no resources dedicated to scientific research or culture development. Efficient team building in SFBB means synthesizing team construction with positional requirements and available roster spots. Identifying the nuances of the unique format will provide a blueprint for a vehicle of SFBB dynasty devastation.

One thought on “Super Best Ball: Assessing Positions and Rosters Using Weekly Hits and Surplus

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  1. After a bit of research, I believe that weekly hits and surplus are less of a predictive tool than a method of analyzing the results. It certainly works great for identifying different outcomes between builds, but PPG projections are likely still ideal for determining the most efficient players. A consideration is to identify stretches where the PPG avg within positional tiers flattens considerably. Pinpointing the values and identifying intelligent gambles on players within these stale-market zones can inform your processes earlier in the draft (trading up/back, knowing the start-up value of rookie picks). Thanks for reading, for those who’ve come this far!


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