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Best Ball Analyzing Usage Trends: How to Read Changing Offensive Usage for Best Ball

Why usage trend analysis is especially valuable in slow-draft best ball formats: a season-long best ball draft on Underdog or Drafters may take 4–8 weeks to complete; the actual NFL season begins during the draft; early-season usage trend data reveals role changes in real time while the draft is still ongoing; the manager who monitors week 3 usage data while week 3 picks are being made can identify emerging role changes before other managers have processed them, creating the opportunity to draft players at their pre-trend price.

The usage trend framework:

The metrics: (1) carry trend for RBs: compare a RB’s carries per game over the most recent 3 games versus their season average; a RB who averaged 14 carries per game in weeks 1–4 but received 22 carries in weeks 5–7 has a clearly increasing trend; this trend may indicate a teammate’s injury, a coaching adjustment, or the RB earning trust from the coaching staff; (2) target trend for WRs and TEs: compare targets per game over the most recent 3 games versus season average; a WR who averaged 6 targets in weeks 1–4 and received 10 targets in weeks 5–7 has a favorable trend; identify the source of the increase (did a competing WR get injured? Did the QB change?) before projecting the trend forward; (3) routes run per game: like target trend but one step earlier in the production chain; an increase in routes run precedes an increase in targets; a WR who runs 15 more routes per game than their prior average has more target opportunities even if targets haven’t yet increased; routes run is the leading indicator of targets; (4) connect usage trends to snap count trends — snap count is the earliest leading indicator; routes run is the next step; targets are the direct production input; the three-step chain snap → routes → targets → production provides the most complete picture of usage direction.

The usage trend types by cause:

The causes: (1) injury-driven usage increase: when a teammate is injured, the remaining players absorb the departed player’s usage; a WR2 who becomes WR1 in week 6 due to WR1’s injury gains 25–35% more targets per game; this usage increase is real and sustainable for the duration of the injury; (2) performance-driven usage increase: a player who performs above expectations (5 consecutive games with 80+ yards and a TD) earns trust from the QB and coaching staff; their route participation rate increases; the usage increase is earned and more likely to persist than an injury-driven increase that disappears when the starter returns; (3) coaching adjustment usage increase: the offense changes its scheme or game plan in a way that increases a specific player’s role; this is the hardest to identify in real time but often the most durable; when the offense adds a specific package (more 2-TE sets, more motion plays) that features a specific player, their usage increase is scheme-driven and persistent; (4) pair usage trend analysis with game script analysis — game script affects weekly usage in ways that can distort the trend; a RB with a big usage week may have been the beneficiary of a favorable game script (team running out the clock in a win) rather than a genuine role increase; always consider whether the usage spike was game-script-driven before projecting the trend forward.

Using usage trends in slow-draft best ball decisions:

The application: (1) in slow-draft best ball (4–8 weeks of picks), the usage data from weeks 1–3 can inform draft decisions in weeks 3–5; identify players with favorable usage trends and draft them before the trend is priced into the ADP market; (2) the trending-up player to target: a WR who emerged as a WR1 role in week 3 due to injury or performance has a new target share; their ADP in the draft platform may not have updated yet; grab them at their pre-trend ADP; (3) the trending-down player to avoid: a WR who was drafted in round 6 but has lost targets in weeks 2–3 due to a coaching change or scheme adjustment is overpriced at their current ADP; let other managers take them while you target emerging usage alternatives.

For how usage trend analysis connects to best ball strategy, see our snap count guide and game script guide. Start at the best ball hub for all resources.