
Kicker is a polarizing topic among fantasy football managers, but for those who play in leagues with the position included, there's a way to level up your lineup decisions. Owners can use kicker advanced stats to answer three questions that most casual gamers never even think to ask:
Kickers do not have a public next gen stats fantasy model as complete as xFP for the skill positions, but the NGS field goal model gives you the right starting point.
This is the No. 1 stat family for fantasy kickers. NGS built its field goal model to estimate make probability from kick difficulty, and the 2024 version added individual kicker skill through Field Goal Probability Over Expected. That matters because raw field goal percentage treats a 38-yarder and a wind-heavy 55-yarder too similarly. FG Probability tells you what should have happened. FG Probability Over Expected tells you what the kicker added beyond that baseline. For fantasy, this is the cleanest way to separate true kicking quality from a soft attempt profile.
Distance matters best through the lens of difficulty rather than raw makes. NGS originally described its field goal model as using distance, weather, and stadium type, and later upgraded it to better handle longer kicks. A kicker living on short attempts can post a strong percentage without giving fantasy managers much weekly ceiling. A kicker trusted from 50-plus yards has more paths to not only rewarding long three-point attempts but naturally offers more opportunities via the trust of his coaching staff.
EPA on field goals is a useful fantasy tiebreaker, because it highlights when made kicks changed games and carried real-world leverage. Fantasy managers should not chase clutch narrative by itself, but EPA can help identify kickers attached to offenses that create meaningful scoring chances instead of empty yardage. It is more useful as context than as a primary draft stat.
Extra points are less exciting than field goals, but they still matter in fantasy. The NGS PAT Decision Guide uses game-state simulations and the probabilities of successful extra points and two-point tries to guide post-touchdown choices. Fantasy managers do not need to model those decisions themselves, but they should care about the environment around the kicker. High-scoring offenses that keep generating touchdowns and still kick frequently after them raise a kicker’s floor, even in weeks when the field goal volume is modest.
The best process is to start with FG Probability Over Expected, then check attempt difficulty, then use EPA and extra-point environment as supporting context. That order keeps fantasy managers from overvaluing a kicker who merely feasted on easy tries while helping them spot strong legs attached to offenses that keep creating points.
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