3CJRRFC Detroit Lions wide receiver Amon-Ra St. Brown (14) catches a pass during an NFL football game between the Detroit Lions and Green Bay Packers Sunday, Sept. 7, 2025, in Green Bay, Wis. (AP Photo/Matt Ludtke)
As the NFL enters Week 2 of the 2025 season, fantasy football players are looking for insights to gain an edge in their leagues. By utilizing advanced analytics and machine learning, we can identify players likely to receive increased targets, which is crucial for maximizing scoring potential.
Understanding Target Distribution
The foundation of this analysis is a model developed using PFF’s extensive route-level data. This model predicts the likelihood of targets for each receiver based on various factors, including their routes and the quarterback’s decision-making. The resulting metrics, known as Share of Predicted Targets and Share of Predicted Air Yards, provide a more stable forecast than actual targets observed in games.
Every route carries a probability of being targeted, but sometimes, quarterbacks may overlook open receivers. For instance, in the season’s opening game, Jalen Hurts focused his attention on DeVonta Smith, who had a 45% chance of being targeted due to his effective route running. Conversely, A.J. Brown found himself in a low-probability situation with only a 2% chance on a deep route. Such dynamics play a significant role in which players may see an uptick in targets in subsequent games.
Identifying Breakout Candidates
The model has undergone improvements this season, incorporating variables such as single-coverage situations, which highlight the advantages receivers face when isolated against a defender. Historically, wide receivers thrive in these scenarios, while tight ends and halfbacks often struggle. The updated model now accounts for these dynamics, enhancing its predictive power.
One prominent player to watch is Zay Flowers, who had an impressive performance in Week 1, achieving the highest Share of Predicted Targets in the league. If he maintains this trajectory, he could emerge as a top wide receiver by the end of the season. Similarly, DeVonta Smith, despite a disappointing Week 1, is positioned for a breakout as the Eagles’ passing game evolves.
Other potential breakout candidates include Travis Hunter, whose low average depth of target raises questions about the Jaguars’ strategy. Despite this, his performance suggests he could become a key target in future games.
The analysis also highlights players who finished in the top 80th percentile for Share of Predicted Targets yet had low actual target shares. This “Coach, I Was Open” list includes major stars like A.J. Brown, Amon-Ra St. Brown, and Nico Collins. These players might see increased opportunities in Week 2, particularly if their teams adjust their offensive strategies based on previous performances.
In prior seasons, players appearing on this breakout list frequently delivered substantial performances, making it a significant indicator for fantasy managers.
In reviewing Week 1, one key play involved Patrick Mahomes, who made an optimal decision by targeting Marquise Brown. Had he looked for Tyquan Thornton, who was in a more favorable single-coverage situation, it could have shifted the game’s momentum. Such analysis underscores the importance of target distribution and quarterback decision-making in fantasy football.
As the season progresses, staying informed on these metrics can provide a competitive advantage for fantasy football enthusiasts. Understanding which players are likely to see more targets is essential for making strategic lineup decisions and enhancing overall performance in fantasy leagues.
