Expected Points Added per play — the change in expected points caused by a play, from nflfastR's expected-points model. The site's universal currency: positive = good for the offense.

Denominator

all plays in the selected sample (QB coverage/route views: the QB's pass plays vs the scheme; team views: scrimmage plays, rps %in% c('pass','run'), excluding kneels/spikes/special teams)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

epa_play

The same nflfastR EPA, averaged over a receiver's targets — every play on which he was the targeted receiver.

Denominator

the receiver's targets (plays with him as targeted receiver)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

epa_target

The same nflfastR EPA, averaged over ALL dropbacks — including sacks and throwaways, not just throws. Used by the Passing Concepts QB-vs-Coverage value box and the Pressure sub-tab's EPA/Dropback Allowed.

Denominator

all dropbacks (rps == 'pass'), sacks and throwaways included

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

epa_dropback

Share of plays with EPA > 0.

Denominator

plays in the current sample with a non-missing EPA

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

success_rate

Turnover margin: takeaways minus giveaways, counted over ALL plays (special teams included) in the selected seasons. A turnover is an interception or a lost fumble (fumble_lost). Attribution follows possession: the offense (posteam) commits, the defense forces — EXCEPT on punts, where posteam is the PUNTING team while nearly every punt fumble lost is a receiving-team muff (97 of 98 in 2022-25). A punt fumble_lost with positive posteam EPA is therefore credited as a giveaway BY the receiving (returning) team and a takeaway FOR the punting team; a punt fumble_lost with EPA <= 0 (botched snap, failed fake) stays a punting-team giveaway. Kickoffs need no flip: posteam there is already the receiving team.

Denominator

counting stat, not a rate: all plays in the selected seasons, special teams included

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

to_margin

Empirical-Bayes stabilized EPA: eb_shrink(x, n, prior, k) = (n·x + k·prior) / (n + k) with prior weight k = 25 observations — small-sample means are shrunk toward a relevant prior so thin cells can't dominate rankings. Raw values and n always remain visible.

Denominator

the cell's own plays/targets (n), shrunk toward the view's stated prior: Route×Coverage heatmap — LEAGUE same-coverage mean computed from the full filtered pass frame (never the Team/QB-scoped frame); Passing Concepts QB-vs-Coverage concepts — league mean for that concept vs that coverage; receiver ranking — situation-pool mean; Read Progression — per-read league mean

Min n shown

none (all n shown)

Shrinkage

eb_shrink k=25 toward the view's stated prior

Era caveat

No

Source

derived

Registry id

stabilized_epa

Completion Percentage Over Expected — actual completion minus nflfastR's expected completion probability given play difficulty.

Denominator

pass plays with a non-missing cpoe value (~80% fill on pass plays)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

cpoe

Average Depth of Target — mean air yards on throws. The canonical instrument is pbp air_yards (coalesced with the 2022-only NGS ngs_air_yards); Weekly Stats shows NGS avg_intended_air_yards.

Denominator

throws with a charted air-yards value

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

adot

Share of throws with air yards ≥ 20 (the deep_throw flag, derived from coalesce(air_yards, ngs_air_yards)).

Denominator

throws with charted air yards (~93% of pass plays each season); deep = air yards ≥ 20

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

deep_throw_rate

Seconds from snap to release, from Next Gen Stats. QB-tab buckets: <2.3 / 2.3–2.8 / 2.8–3.3 / 3.3+ seconds.

Denominator

dropbacks with an NGS time_to_throw measurement

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

NGS weekly

Registry id

ttt

Share of opposing dropbacks with an FTN-charted pressure on the QB (was_pressure).

Denominator

charted pressures / opposing dropbacks (rps == 'pass')

Min n shown

100

Shrinkage

none

Era caveat

No

Source

FTN charting

Registry id

pressure_rate

Share of dropbacks with five or more total pass rushers (n_pass_rushers ≥ 5). One of two blitz definitions shown side by side, never blended.

Denominator

5+-rusher dropbacks / opposing dropbacks with a charted n_pass_rushers

Min n shown

100

Shrinkage

none

Era caveat

No

Source

FTN charting

Registry id

blitz_rate_rushers

Share of dropbacks where FTN's n_blitzers ≥ 1. n_blitzers counts only SECOND-LEVEL rushers, so this is a different construction from the 5+-rushers definition — the two are shown side by side, never blended.

Denominator

n_blitzers ≥ 1 dropbacks / opposing dropbacks with a charted n_blitzers

Min n shown

100

Shrinkage

none

Era caveat

No

Source

FTN charting

Registry id

blitz_rate_blitzers

Pressure generated without sending extra rushers: the pressure rate restricted to dropbacks with four or fewer pass rushers.

Denominator

pressures on ≤4-rusher dropbacks / ≤4-rusher dropbacks (charted n_pass_rushers)

Min n shown

100

Shrinkage

none

Era caveat

No

Source

FTN charting

Registry id

pressure_no_blitz

Share of sacks in the sample that FTN charted as the QB's fault (is_qb_fault_sack).

Denominator

FTN QB-fault sacks / sacks in the sample

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

FTN charting

Registry id

qb_fault_sack_share

How often a defense lines up in each charted coverage scheme, over dropbacks only (rps == 'pass' — QB scrambles with charted coverage are excluded, matching the QB coverage views). BLOWN (busted coverage — a data-quality bucket, not a callable scheme) is excluded from numerator AND denominator, so shown usage sums to 100%.

Denominator

team dropbacks in the scheme / team charted-coverage dropbacks (rps == 'pass'); league baseline = mean of per-team usage shares over ALL teams in the same filtered sample, with zero shares for teams that never show the scheme

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

FTN charting

Registry id

coverage_usage

Mean EPA a defense allows on dropbacks in each charted coverage scheme. Dropbacks only (rps == 'pass'): QB scrambles carry charted coverage too but belong to the run population, so they are excluded — the same denominator as the QB-vs-coverage views. League baseline is the play-weighted mean over all dropbacks in the scheme under the same filters.

Denominator

dropbacks (rps == 'pass') with the scheme charted vs the selected defense; league baseline over all such dropbacks league-wide

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

FTN charting

Registry id

coverage_epa_allowed

Player targets divided by team targets — computed PER TEAM STINT (player × team over that stint's weeks) so traded players are not blended across teams; the most recent stint is reported.

Denominator

player targets with the team / that team's total targets over the stint's weeks

Min n shown

30

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

target_share

Player carries divided by team carries over the selected regular-season game sample. This measures observed rushing workload, not snap share.

Denominator

player carries / team carries in the player's observed games

Min n shown

20

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

carry_share

Player targets charted as the quarterback's first read divided by all team targets charted as first reads across the games the player appeared. This measures the player's share of designed receiving priority rather than the mix of their own targets.

Denominator

player first-read targets / team first-read targets in games appeared

Min n shown

10

Shrinkage

none

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

FTN charting

Registry id

first_read_target_share

Completions on the receiver's targets (mean of complete_pass over targets) — of ALL targets, unlike Drop %, which uses catchable targets only.

Denominator

receptions / all targets (catchable or not)

Min n shown

30

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

catch_rate

Drops divided by CATCHABLE targets (FTN-charted catchable balls) — never of all targets (league ≈5.0%). Lower is better; inverted in pizza percentiles.

Denominator

FTN-charted drops on catchable targets / catchable targets

Min n shown

25

Shrinkage

eb_shrink k=25 toward the play-weighted league drop rate (computed from everyone before the display filter)

Era caveat

No

Source

FTN charting

Registry id

drop_rate_catchable

Contested-catch conversion: completed catches on FTN-charted contested targets.

Denominator

contested catches (contested & complete) / contested targets

Min n shown

25

Shrinkage

eb_shrink k=25 toward the play-weighted league contested conversion (computed from everyone before the display filter)

Era caveat

No

Source

FTN charting

Registry id

contested_conv

Share of dropbacks with an FTN-charted interception-worthy throw. Uncharted flags count as not-flagged (≥99.6% of plays are charted).

Denominator

INT-worthy throws / QB dropbacks (rps == 'pass')

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

FTN charting

Registry id

int_worthy_rate

Share of a QB's interception-worthy throws that were actually intercepted — computed as the intersection sum(int & int_worthy) / sum(int_worthy), because tipped-ball INTs aren't always charted worthy. League ≈48.5% pooled 2022–25. Descriptive; never framed as “luck”.

Denominator

intercepted INT-worthy throws / INT-worthy throws

Min n shown

100

Shrinkage

none

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

FTN charting

Registry id

int_worthy_conversion

Share of dropbacks FTN charted as throwaways (is_throw_away).

Denominator

throwaways / QB dropbacks (rps == 'pass')

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

FTN charting

Registry id

throwaway_rate

NGS avg_separation — yards between the receiver and the nearest defender at catch/arrival; the receiver's weekly NGS average joined per play.

Denominator

targets with an NGS separation value (weekly player average joined per play)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

NGS weekly

Registry id

separation

Rush Yards Over Expected — the NGS model's actual minus expected rush yards given blocking/box, as a per-attempt weekly average joined per play.

Denominator

carries with an NGS RYOE value (per-attempt weekly average)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

NGS weekly

Registry id

ryoe

Team usage of the FTN play flags (motion, no-huddle, RPO, shotgun, play action, screens) vs the play-weighted league under the same filters. Association, not play-calling causation — the flags are not randomly assigned.

Denominator

Motion / No-Huddle / RPO / Shotgun per scrimmage play (rps %in% c('pass','run')); Play Action / Screen per dropback (rps == 'pass')

Min n shown

100

Shrinkage

none

Era caveat

No

Source

FTN charting

Registry id

tendency_usage_rate

Score = EPA the defense allows on the player's most-TARGETED route families vs league average, weighted by the player's TARGET share on each family (0.5 = league-neutral). Targets are the charted data — routes run are not tracked (ff_opportunity route counts are weekly aggregates and are not wired here). Letter grades curve the Score across the graded (100+ target) players: A = top 20%, B = next 20%, C = middle 20%, D = next 20%, F = bottom 20%.

Denominator

the receiver's charted-route TARGETS overlaid on the opponent's coverage-allowed EPA; graded pool = players with ≥100 targets

Min n shown

100

Shrinkage

reliability curve: sub-100-target scores pulled toward the DISPLAYED population's mean raw score (recomputed from the current filtered field before curving — not a constant 0.5) by min(targets/100, 1); letter grades only for ≥100-target players

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

matchup_grade

Targets per game in the pizza-chart metric tables (WR/TE and RB). The denominator is games the player APPEARED in — any offensive involvement on a play: targeted (receiver), carried (rusher), or dropped back (passer) — counted once per season-week. It is NOT games-with-a-target (which doubled the rate for players targeted in half their games) and not official games played: pbp has no participation log, so a zero-touch appearance cannot be counted.

Denominator

distinct season-weeks with any offensive involvement (target OR carry OR dropback) within the filtered sample (compute_player_games_appeared, R/07-utils-pizza.R)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

nflfastR

Registry id

targets_per_game

Percentile of a player's metric vs the qualifying position pool, via the pool's empirical CDF: P(pool ≤ value), so ties share credit. Lower-is-better metrics (INT-Worthy%, TTT, Fumble%, Drop%) use the ECDF of NEGATED values — P(pool ≥ value) — which is tie-symmetric: players tied at the best value all get the top percentile (the old 1 − ECDF form was the strict P(pool > value) and charged every tie).

Denominator

position pool at the qualifying volume (QB ≥100 plays, WR/TE ≥30 targets, RB ≥40 carries), roster positions as pool authority

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

derived

Registry id

pizza_percentile

The GM simulator's ledger: the sum of APY over the team's active contracts, plus dead money from simulated cuts. This is an APY-BASED ESTIMATE, not official cap space — real cap hits differ from APY because signing bonuses prorate over up to five years and offseason accounting counts only the top-51 charges, so summing APY exceeds the $301.2M cap for most cap-compliant teams (headroom = cap − commitments is then negative, and the share-of-cap gauge exceeds 100%). Cut/sign/trade moves stay internally consistent in APY units; cap-hit modeling (prorations, restructures) is deliberately deferred.

Denominator

counting stat, not a rate: sum of OTC APY ($M) over the selected team's active contracts + simulated dead money; share of cap divides by the $301.2M 2026 league cap

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

OTC

Registry id

apy_commitments

Estimated APY for a simulated free-agent signing. Anchored on the player's own most recent contract APY (the market's last real observation of him); players with no usable prior APY fall back to the position's median APY among recent (2023+) signings. Where the player has recent play-by-play EPA, his EPA percentile within the pool's position group scales the anchor by a bounded 0.6x–1.8x multiplier. An estimate — age, injury, scheme fit, and bidding wars are not modeled, and the anchor lags when the last deal is stale.

Denominator

the free-agent pool: each player's latest inactive contract (year_signed ≥ 2022) for players holding NO active contract; EPA percentile over the pool's position group (whole pool when the group has < 10 EPA-attached players; EPA gates: 50 pass / 20 target / 30 rush plays)

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

derived

Registry id

fa_market_value

Points from the actual Jimmy Johnson trade value chart, embedded for all 224 picks (3000 for pick 1, 590 for 32, 100 for 100, 2 for 224); picks 225+ continue the round-7 step (0.3/pick) floored at 1. Replaced (2026-07) an exponential approximation that ran 1.7x–53x high after round 1 and flattened the chart's early-pick premium. Player-for-pick verdicts map the player's APY to a pick equivalent and compare chart points; the JJ chart reflects 1990s trade norms, not modern surplus-value research.

Denominator

not a rate: chart points per pick (1–262); player trade value uses apy_to_pick_equivalent(APY) → pick → chart points

Min n shown

none (all n shown)

Shrinkage

none

Era caveat

No

Source

derived

Registry id

jj_pick_value

How far a defense's coverage identity sits from its season's league norm — the leave-one-out Mahalanobis distance of the identity vector (CLR of 10 smoothed coverage shares + logit man rate + logit blitz 5+ rate) from the season's play-weighted league centroid computed WITHOUT the team, under an OAS-shrunk covariance fit on within-season-centered defense-seasons 2022+ and refit without the scored team. Reported as rank/percentile among the season's 32 defenses only — the reference distribution supports no p-values. Distinctiveness measures difference from the league, NOT quality — a distinctive defense is not thereby a good one.

Denominator

not a rate: distance over the defense's eligible charted non-BLOWN dropbacks (n shown); percentile among the season's 32 defenses

Min n shown

none (all n shown)

Shrinkage

coverage shares via kd_smooth_coverage_mix k=15 (week -> defense-season -> league); man/blitz rates via eb_shrink k=15 toward the league rate

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

distinctiveness

The same leave-one-out Mahalanobis machinery as Defensive Distinctiveness, reported in three identity spaces: COVERAGE (the 12-dim scheme vector — identical to Distinctiveness), PERSONNEL (CLR of the 4 smoothed package shares base/nickel/dime/quarter by defensive-back count, plus CLR of the 3 front shares light/odd/even by defensive-line count), and COMBINED (both, 19 dims). Each block is scored separately and WITHIN season against that season's play-weighted league centroid computed without the team, under an OAS covariance refit without the scored row. Personnel is the one identity input that survives the 2022 NGS / 2023+ FTN charting break intact: 2022 charts 'DL/LB/DB' counts directly and 2023+ granular positions condense to the same counts, so no personnel class is era-absent. Reported as rank and percentile among the season's 32 defenses only. Distances from different blocks are in different metrics and are NOT comparable in absolute terms — percentiles are. Uniqueness measures difference from the league, NEVER quality: measured over the 128 defense-seasons 2022-25, uniqueness and EPA allowed per dropback are uncorrelated (Spearman rho = -0.01 combined, -0.06 coverage, +0.01 personnel; no p below 0.5).

Denominator

not a rate: coverage uses charted non-BLOWN dropbacks, personnel uses dropbacks with a parseable defense_personnel_condensed (100% of pass plays 2022-25), and the combined block is play-weighted by the thinner of the two; percentile among the season's 32 defenses

Min n shown

100

Shrinkage

every composition (coverage classes, personnel packages, fronts) is smoothed by the SAME kd_smooth_coverage_mix hierarchy k=15 with an alpha=0.5 Laplace-floored league prior; man/blitz rates via eb_shrink k=15; covariance by OAS shrinkage (rho ~0.12 coverage, ~0.04 personnel and combined)

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

identity_uniqueness

Jensen-Shannon divergence (log base 2, bounded 0-1) between week w's smoothed coverage mix and the exponentially decayed trailing mix of the team's PRIOR weeks (half-life 4 weeks, week w excluded; the first two observed weeks are not scored). Because both arms shrink toward the same priors, raw JSD is deflated in low-volume weeks — every week is therefore shown against a multinomial parametric-bootstrap null band (90th percentile of 500 no-change resamples at the true ns), and a week only reads as changed when it clears the band. Within-season only; descriptive — no persistence alerts.

Denominator

week-w charted non-BLOWN dropbacks vs the effective n of the EW-decayed trailing mix (both ns shown)

Min n shown

none (all n shown)

Shrinkage

both arms smoothed via kd_smooth_coverage_mix k=15 toward the defense-season then league mix

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

identity_change_jsd

Posterior probability from the frozen defense-archetype Gaussian mixture (mclust on ilr + logit identity vectors of all pooled defense-seasons, within-season centered; model/k selected by ICL; bootstrap-Jaccard stability gates: >= 0.75 named, 0.60-0.75 unnamed pattern, below dissolved to Mixed). Profiles are PROJECTED onto the frozen model — never re-clustered — so posteriors are deterministic. Archetypes describe style relative to the season's league norm, not quality; names are descriptive and unordered. Posterior magnitude is saturated by construction (audited 2026-08-05). The frozen fit has G = 2 and the bootstrap DISSOLVED one component (Jaccard 0.41), so 110 of 128 defense-seasons carry the single 'Mainstream' label. Both ICL and BIC prefer that 2-component fit to G = 3-6, which is the honest finding rather than a tuning artifact: this feature space holds one mainstream identity plus unstable fringe variation. The near-100% posteriors are arithmetically correct but saturate BY CONSTRUCTION — the posterior is 1/(1+exp(-gap)) in the two components' weighted log-density gap, and in 11 dimensions the median defense-season sits 6.9 nats (99.9%) from the rival component before any evidence specific to that defense is weighed; the same saturation persists at G = 3-6 (mean max-posterior 0.91-0.97). A posterior here means 'which side of the boundary', never 'how certain'. For a graded, non-degenerate read of how unusual a defense is, use identity_uniqueness.

Denominator

not a rate: posterior probabilities over the frozen mixture components (sum to 1); fit pool = defense-seasons 2022-25 (n = 128)

Min n shown

none (all n shown)

Shrinkage

inputs are the smoothed identity features (kd_smooth_coverage_mix k=15; eb_shrink k=15 for rates)

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

archetype_prob

Mean EPA allowed per dropback of the k=5 nearest defense-seasons by the same Mahalanobis identity metric — same charting era only, min-n gated, and always EXCLUDING the team itself (leave-one-out). A descriptive baseline: 'vs stylistically similar defenses', not opponent-adjusted, and similarity of style says nothing about quality — distinctiveness is not success.

Denominator

all dropbacks (rps == 'pass') faced by the k nearest same-era defense-seasons with >= 200 eligible dropbacks, self excluded

Min n shown

200

Shrinkage

none (plain mean over the neighbor defense-seasons)

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

similar_def_epa_loo

Jensen-Shannon divergence (log base 2, bounded 0-1) between the hierarchically smoothed coverage mixes immediately before and after a documented defensive play-caller change. The observed divergence is compared with the 90th percentile of 500 multinomial no-change resamples at the two eras' true sample sizes. A shift is descriptive, not a causal effect of the staffing change.

Denominator

charted non-BLOWN defensive dropbacks in the adjacent play-caller segments; both segments require at least 100 eligible dropbacks

Min n shown

100

Shrinkage

both era mixes use kd_smooth_coverage_mix k=15 toward that defense-season and the season league mix

Era caveat

Yes — affected by the 2022 (NGS participation) vs 2023+ (FTN) charting break; era notes appear in place.

Source

derived

Registry id

caller_era_shift_jsd

Observed situation-adjusted output after a disruption event (pressure, hit, sack, INT, strip-sack), relative to this QB's OWN baseline: mean situation-bucket EPA residual on post-event dropbacks minus the same QB's residual on his non-post-event dropbacks reweighted to the post-event situation distribution (difference-in-differences). Reflects selection and mean reversion; descriptive, not a causal bounce-back, never toughness/psychology. Reliability tiers per measured event counts: pressure/hit/sack are per-QB-season viable, INT per-QB only pooled 2022-25, strip-sack league-level only (never per-QB — median 2 per QB-season).

Denominator

genuine dropbacks (qb_dropback == 1; no_play, kneels, spikes, and two-point tries excluded) inside the selected response window — next dropback, rest of drive, next same-QB drive, or rest of game — same game and same passer only; truncated (empty) windows dropped from denominators, never scored 0

Min n shown

20

Shrinkage

eb_shrink k=25 toward the league DiD; 95% CI from a game-clustered bootstrap (B=500) on the unshrunk DiD

Era caveat

No

Source

derived

Registry id

after_event_epa_did

The same within-QB DiD computed after a situation-matched bad play that was NOT the event: non-event dropbacks with EPA below the QB's own median, importance-weighted by situation bucket to match the real event's situation distribution. Shown beside the event DiD so the event-specific increment separates from generic bad-moment reversion — if the event and placebo deltas match, the 'response' is ordinary mean reversion, not something the event caused. Reflects selection and mean reversion; descriptive, not a causal bounce-back, never toughness/psychology.

Denominator

same response-window dropbacks as the event DiD, with placebo events = situation-matched non-event dropbacks below the QB's median EPA; same guards (truncated windows dropped, turnover plays empty the rest-of-drive window)

Min n shown

20

Shrinkage

eb_shrink k=25 toward the league placebo DiD; game-clustered bootstrap CI (B=500)

Era caveat

No

Source

derived

Registry id

after_event_placebo

The set of dropbacks scored as the response to a disruption event, under seven sequencing guards: plays ordered by game_id + play_id (monotonicity asserted); no_play/penalty-nullified snaps are skipped, never counted as the response; kneels, spikes, and two-point tries excluded; 'next drive' means the next drive with the SAME offense AND the SAME passer (never naively fixed_drive + 1, which is usually the opponent); a turnover on the event play empties the rest-of-drive window; truncated windows are dropped from denominators, not scored 0; and a benched QB's window resumes on his return without bridging the backup's plays. Post-event numbers reflect selection and mean reversion; descriptive, not a causal bounce-back, never toughness/psychology.

Denominator

events with at least one same-game, same-passer response dropback in the window (next dropback / rest of drive / next same-QB drive / rest of game); dropped-window counts are reported

Min n shown

none (all n shown)

Shrinkage

none (window definition, not an estimate)

Era caveat

No

Source

derived

Registry id

event_response_window