Are you preparing to blow up your dynasty team and start a rebuild? Do not be rash to trash your roster until you know how your team compares to others in your league.
For most fantasy football dynasty leagues, 2025 rookie drafts begin soon after the NFL Draft and Mr. Irrelevant is in the books. These are the days when fantasy General Managers make final assessments of their pre-draft rosters and identify the strengths and deficiencies of their teams. During that process, at some point, GMs will evaluate the team’s chances of success. This is when many GMs come to the proverbial fork of roster management—do I compete or do I rebuild?
To be fair this is more of a crossroad than a fork as there is an option to simply tweak for the following season. Nonetheless, devising a strategy and rendering a decision is important. How, then, how does a GM answer this question?
Several years ago, I devised a relatively simple “gut-check” I use to evaluate my teams with some easy-to-calculate metrics. This provides an overall picture of the roster’s health and an idea of how the team may be competitive.
There may be manual or fantasy football platform processes that resemble, or mirror, this routine. This would be purely coincidental.
My technique is simple. It compares player projections v the league’s recent historical scoring. We forego superior mathematics, probabilities, and numerous other variables. Each GM must decide the degree of precision sought to conduct their review. With numerous leagues to evaluate, this “quick snapshot” helps me bucket my teams into “compete” or “rebuild”. Depending on the outcome, I may dig deeper but often I already know enough to decide.
Where do we start?
For this exercise, I will use “Fun League”, a ten-team, 1QB league with DST and K. The starting lineup consists of 1 QB, 2 RB, 3 WR, 1 TE, 2 WRT, 1 K, and 1 DST. While most scoring is standard, this is a 0.5 PPR, passing is 0.05/yard, 6 for TD, with customer scoring for DST and K.
League Median/Average Scoring History
The first step is to establish the anticipated league median or average scoring based on history. We accomplish this by using the median and average over the last three seasons. This allows for any anomalies or fluctuations in scoring in a particular year. An important note—use of the last three seasons is contingent on stability with roster, lineup, and scoring rules. Changes require fewer seasons as stable scoring permits.
For the ten teams in the past three seasons in Fun League, 56,504.84 points were scored—an average of 1,883.49 points per team per season. The highest average for the three seasons was 1,891.70 and the lowest was 1,838.23. Confidence is strong that the upcoming season will be relatively close (all else equal with rosters and scoring rules). The median for those 30 team seasons was 1,876.33. For this exercise, I will settle on 1,880.00 as my target.
Player Scoring Projections – Sources and Scope
The second step is to determine the anticipated points for each rostered player. Personal projections or prognostications from one or more favorite analysts are a choice for each GM to make. Note that published projections may not emulate your league’s scoring rules if scoring deviates significantly from more traditional configurations. In those circumstances, manually calculating point projections based on statistical forecasts is prudent.
We all have sources for projections we trust. Conversion to unique scoring rules, however, can be time-consuming. Because Fun League is on Sleeper, and the platform’s projections are already based on the league’s scoring rules, we will use Sleeper for this exercise.
Before applying projections, it is crucial GMs understand if the source’s projections cover 14, 17, or 18 weeks of the NFL season (thus 13, 16, or 17 possible games). GMs often overlook this when confining evaluation to the current season. Projections beyond 14 weeks—which is common—require an adjustment. There are more precise methods for calculating this adjustment, especially after the NFL schedules are announced, but a simple percentage works.
Player Scoring Projections – Calculation
If a projection covers the entire 18-week NFL season, we multiply each player’s forecast by 0.7647 to derive Adjusted Projected Points (“ADJPP”). This is 13 potential games during the fantasy regular season (considering the bye week) divided by the total 17 potential games played. While I tend to ignore players unlikely to make it into my starting lineup, sans injuries, for this exercise we apply it to the entire Fun League team roster.
For each starting player, locate their projected points and record them in a spreadsheet. The ADJPP is then calculated for each.
The team in Fun League has Joe Burrow as the starting quarterback. Per Sleeper, Burrow is projected to score 427.00 points. Multiply that by 0.7647 and the product is 326.53. This is the ADJPP for Burrow during the regular season. For each starter, the presumption is players will not miss games. ADJPP, therefore, will equal Points Expected (“PEXP”), the approximate expected points for Burrow to contribute to the team’s overall regular season scoring.
To accommodate for bye weeks, I identify players most likely inserted into the starting lineup for each position. Then divide that player’s ADJPP by 13 and multiply by the number of games expected in a lineup position. This will be the replacement player’s PEXP.
Player Scoring Projections – Backups
At QB, this team has Michael Penix and Matthew Stafford as viable QB backups. Let’s use Penix. Sleeper projects 322.00 points for Penix. The ADJPP is 246.23. Divide the ADJPP by 13 and the PEXP is 18.94—the approximate expected points that Penix will contribute to the team. Therefore, the QB position is anticipated to contribute 345.47 total points during the 14-week regular season.
This roster has Rashid Shaheed as a potential bye-week replacement. His projection is 142.00, and he may be in the starting lineup five times during the season. 142.00 is divided by 17 and multiplied by 5, resulting in 41.77, which is Shaheed’s PEXP.
Many GMs ignore DST and Kicker in their team evaluation but for this exercise it is essential. The same process can be followed for these positions but with one modification. Because most GMs are not rostering back-ups for these positions, we multiply the projections by 0.8235 to accommodate 14 games. It is simpler than figuring out what is available on the wire, etc.
Once all starters and bye-week replacements have calculated PEXP, the sum of the PEXP represents the team’s expected total score. For the team in Fun League, the result is 1,814.18.
Evaluating Results
We previously established 1,880.00 as the benchmark for median/average points scored for the league. We calculated ADJPP and PEXP for starting and bye-week replacement players to determine an approximate expectation of 1,814.18. The roster falls short but the deficiency is less than five points per game. Does this team require a rebuild?
It is unlikely the team will dominate Fun League. A 7-7 record is entirely possible. Additional evaluation may be needed and likely include other factors not considered here—age of starting players, available rookie draft picks, willing trading partners, etc. Older producing veterans may be bartered for potential draft capital. At the same time, one or two well-executed trades and a solid rookie draft may provide this team a certain playoff berth—even if a run to the championship requires some good fortune.
To Compete or Rebuild?
While on the proverbial fence, this team plans to compete. The GM made the playoffs the previous season. Even with the middling expected points and a roster with minimal depth, a couple of shrewd moves can help this team make a deeper run.
When evaluating a team, the eyeball test may be sufficient. One team in Fun League is clearly above the league average (greater than 2,000 points) while another hovers around 1,500 points. This method does not benefit those obvious scenarios. But if you are not sure what side of average your team is on, this exercise can help shed some light.
There are times this down-and-dirty, back-of-the-envelope review of the team will provide everything to render a decision. It is also possible evaluation of other variables is necessary. But that exercise can be reserved for those scenarios where the team is close—as with our example in Fun League. While the absence of precision in this method may not satisfy everyone, this process can provide a snapshot of how the team will perform, relative to the rest of the league, in the new season. If, like me, you have numerous teams to evaluate and not enough time to thoroughly analyze each one, this method affords quick identification of teams needing additional review or those easily bucketed into compete or rebuild.
