RSO Roster Construction: Player Tier Variation

Updated: July 18th 2020

The question of optimal roster construction remains a mystery to many in RSO leagues.  How much should I allocate to different position groups?  How is the allocation distributed within each position?  How much should go to projected starters versus backups?  There exists practically near-limitless player combinations available to RSO teams and we can’t hope to cover any reasonable fraction of those.  This article gives a few examples of what various rosters can look like based on allocation of salary cap to different tiers of players.  We utilize average salary data taken from 2020 RSO startup auctions in order to construct 20-player rosters fitting near the RSO salary cap limits.  I assume 1QB/1SF/2RB/2WR and 1 or 2 flex spots in the starting lineup for this exercise.   I also allocated the same number of roster spots at each position for all rosters as a consistency measure.

The goal of this article is not to recommend individual players or even which type of roster construction is best.  League settings and conditions will have a big impact on the type of roster you desire on auction day.  The article does provide a starting point in evaluating different types of roster builds and the sort of trade-offs one must take into account when choosing how your team is constructed by examining a few rosters with differing cap distributions among players.

Top-Tier Heavy Roster

Top-tier Heavy Roster Example

This roster paid a premium for top-tier players, holding one at each position.  The top-4 players combined for about 75% of the salary cap.  These top-tier players show the most certainty in production which means this roster construction profile puts most of the cap dollars in highly reliable players.  The hope for this type of team resides in exploiting the consistent week-winning upside of the high priced players while getting just enough production from lower priced players.  The team has potential for extremely high weekly production in shallow leagues if it gets lucky and hits on one or two low-priced, low-probability players.  That strategy gets murkier as the number of required starters increases when more “hits” on questionable players are needed to produce a winning lineup.

The main issue with a team constructed this way is that many roster spots are filled with minimum salary and other low-cost players with very small odds of significant fantasy production.  There is little chance of seeing significant value increases from these players.  Most trades will necessarily involve moving one of the prized star players to help alleviate any team deficiencies.  Any injury or underperformance of your star players is also a major issue for a team like this as there simply isn’t going to be a viable replacement in most cases.

 

Starter Heavy Roster

Starter Heavy Roster Example

This roster variation divests cap dollars away from the very top-tier players.  Most of our salary is still allocated to the starters but is more evenly divided among them.  We can see that secondary and tertiary starters see significant potential upgrades over the previous top-tier heavy roster both in upside and certainty.  The main question for teams utilizing this strategy is how they view the secondary starters.  The move away from the top-paid players may well be worth the cost if an owner sees potential top-tier production in the next tier of players.

Balanced Roster

Balanced Roster Example

This distribution notably puts more cap dollars in potential flex starters and bench players.  The flatter cap distribution approach displays two primary benefits.  First, the roster offers enhanced injury mitigation.  Unavailability of even the best players on this roster will potentially have a more diminished effect.  The statistical projections between players are less as the salary gap narrows.  There is a certain amount of “plug and play” replacement aspect here.  Second, this type of roster construction acknowledges the inherent randomness in statistical production.  New coaching, surrounding personnel, schemes, schedules, etc. have major impacts on the fantasy performance of players.  Dividing money to more players allows additional chances on players with reasonable chances of significantly out-producing respective salaries.   There exists a good chance one of the backups produces at starter-quality as a replacement for an underperforming projected starter.

The downside to this build is a team will usually not have the potential weekly upside using this roster methodology compared to more concentrated distributions.  Even when many of the questionable players exceed expectations, they are unlikely to achieve truly top-tier production levels and many may not make your starting lineup.  This becomes less of a concern as in deeper leagues as more of the “hits” can be utilized on a weekly basis.

 

Key Implications

  1. Highly concentrated cap teams attain more viability in leagues with shallower starting requirements. Flatter cap distribution among players finds its strength in deeper leagues as lower-tier players have more value.
  2. Injury and production risk decrease as we flatten the cap distribution. The risk is actually lower that key players underperform in a more concentrated distribution due to fewer key players but the harm done to a team is substantially higher when underperformance does occur. 

Bio:  Bernard Faller has degrees in engineering and economics.  He currently lives in Las Vegas and enjoys athletics, poker, and fantasy football in his free time.  Send your questions and comments (both good and bad) on Twitter @BernardFaller1.

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