Dynasty Trajectory Scores | Phase 1

The first layer of Dynasty Strategy:
Identify Historical Trends.
Follow Historical Trends.

As the NFL data pool continues to grow with tools like GPS tracking or play-mapping, fantasy analytics has stayed fairly rudimentary. Much of the dynasty analytics community is focused on rookie prospect evaluation. Once the player has been around long enough, college stats become less relevant and the market begins to focus on Average Draft Position (ADP). While ADP is efficient, the quest to outperform ADP must begin with an objective piece outside of the market framework. FFA's Dynasty Trajectory Scores offer a data-driven backbone for Dynasty Asset evaluation. Use them to provide valuable context for your startup draft board or insert them into your dynasty projection models.

Calculating the trajectory of a rocket requires recognition of several layers of variables. We can separate these into two main categories: Internal and External factors. Atmospheric factors are a critical part of the equation. Weather conditions, barometric pressure, and launch site latitude will all affect the trajectory. These situational External factors are akin to the NFL individual's teammates and coaching staff. We've seen Cooper Kupp double his productivity when the Rams added Matt Stafford and lost Robert Woods. We've seen Bills WR Stefon Diggs takeoff after being paired with Josh Allen. We've seen Bengals RB Joe Mixon struggle and succeed with the firing and re-hiring of offensive line coach Frank Pollack. These atmospheric elements play a big part in a player's productivity.

The most important components of trajectory are the characteristics of the rocket itself. How much thrust can its engines deliver? How much payload will it be carrying? These Internal Factors are not always constant: A rocket's mass changes as it burns fuel, shifting the calculated trajectory. This occurs with NFL athletes as well. As they burn more fuel, two inherent characteristics see a decrease in value:

1. Productive Value decreases
2. Market Value decreases

This change in value is intrinsic to the individual athlete. It occurs with every player across a reasonably consistent range. Quantifying this range is the initial focus of these Phase 1 Trajectory Scores. We will root out the additional noise of External Factors, such as NFL roster construction and playcaller history, in favor of isolating the Productive Value of the individual. External factors can be integrated during future phases.

As with Tsiolkovsky's ideal rocket equation, the projected performance range of a particular NFL player can be derived from simple Newtonian physics. Instead of:

Force = Mass x Acceleration

we'll use:

Future points = Previous points x Age

The premise is incredibly simple. The core of a player's intrinsic fantasy value is his on-field productivity. That data is enough to calculate the future trajectory of his career. By taking the average fantasy points per game of his last two seasons, we get a good idea of a player's recent value. A single season is not a large enough sample size and including a third season goes too far into a player's history - too much has changed since then. Two seasons gives us enough information to reduce the External factor noise. We get to see who he is in different seasons, with a different mix of teammates and an offseason to get healthy, master a playbook, or get a better playcaller.

The PPG from the past two seasons will allow us to put him in a cohort with other historical NFL players. From there, we can compare how players of a similar caliber performed in their subsequent seasons. We can see into the future based on the average productivity of similar athletes.

Ascending Example: