{
  "series_id": "wr-target-share-stability",
  "run_id": "2026-09-06T055231Z-wr-target-share-stability-gh34015010795",
  "claims": [
    {
      "claim_id": "registration-design",
      "text": "The design was locked on 2026-09-04. It specified NFL wide receivers in 2018-2025 regular-season weekly statistics, observation-window-only WR eligibility, strictly disjoint 1-, 2-, 3-, 4-, 6-, and 8-team-game feature windows, next-four-team-game outcomes, and earlier-season-only fitting. Target share is summed player targets divided by all reported player targets for the team over the same games, including RB and TE targets and excluding untargeted pass attempts; the executed evaluation seasons were 2019-2025.",
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        "analysis.json#outcome_definition"
      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "comparator-definition",
      "text": "The combined comparator uses the player's prior-season share for his last dated prior-season team and that team's target denominator when usable; otherwise it uses a training-only earlier-season WR mean. Paired improvement is comparator MAE minus observed-share MAE, so positive values favor observed share.",
      "kind": "source",
      "evidence_paths": [
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      "status": "supported"
    },
    {
      "claim_id": "input-provenance",
      "text": "Provenance identifies nflverse contributor data as the source of 2018-2025 weekly player statistics and the schedule file. Each listed source has approved rights status and a CC BY 4.0 license, and the production manifest reports complete files with verified approved hashes; the provenance notes that underlying NFL data remain subject to their owners' terms.",
      "kind": "source",
      "evidence_paths": [
        "provenance.json#[source_name=nflverse 2018 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2019 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2020 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2021 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2022 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2023 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2024 weekly player statistics]",
        "provenance.json#[source_name=nflverse 2025 weekly player statistics]",
        "provenance.json#[source_name=nflverse NFL schedules]",
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      ],
      "source_urls": [
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2018.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2019.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2020.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2021.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2022.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2023.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2024.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/stats_player/stats_player_week_2025.csv",
        "https://github.com/nflverse/nflverse-data/releases/download/schedules/games.csv"
      ],
      "status": "supported"
    },
    {
      "claim_id": "execution-integrity",
      "text": "The accepted execution reports approved production inputs, verified hashes, complete required files, reconciled canonical schedule and player-statistic keys, passed baseline, leakage, temporal, sensitivity, uncertainty, and withholding checks, and a published status with no withholding reasons.",
      "kind": "source",
      "evidence_paths": [
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        "analysis.json#publication_status"
      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "row-reconciliation",
      "text": "The execution reconciled 147,226 raw weekly-statistic rows: 140,750 were accepted canonical regular-season rows, 135,363 were analytically used, and 11,863 were excluded from all estimators. It used 2,127 completed regular-season games from the reconciled schedule.",
      "kind": "numeric",
      "evidence_paths": [
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        "analysis.json#schedule_reconciliation"
      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "team-window-reconciliation",
      "text": "All 1,536 candidate team-windows were analyzed. Recorded drops were zero for incomplete season-team windows, zero denominators, unresolved team-game joins, and non-disjoint team windows; non-disjoint player-window observation drops were also zero.",
      "kind": "numeric",
      "evidence_paths": [
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      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "result-window-1",
      "text": "For the pooled rolling 2019-2025 NFL wide-receiver evaluation, using the first 1 completed regular-season team game to forecast target share over the immediately following four team games, 1,013 eligible player-windows from 369 players had observed-share MAE 6.01 percentage points (95% pointwise player-cluster bootstrap interval 5.57 to 6.39) versus 5.62 (5.30 to 5.94) for the prior-season/earlier-season-WR-mean-fallback comparator. Paired comparator-minus-observed improvement was -0.39 points (-0.76 to -0.01); the deterministic interval fact classifies this interval as negative and excluding zero. The outcome divides player targets by all reported team-player targets over those four games.",
      "kind": "numeric",
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        "deterministic-numeric-facts.json#intervals[label=analysis.windows.1.improvement_over_prior_ci_pp]"
      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "result-window-2",
      "text": "For the pooled rolling 2019-2025 NFL wide-receiver evaluation, using the first 2 completed regular-season team games to forecast target share over the immediately following four team games, 1,145 eligible player-windows from 416 players had observed-share MAE 4.91 percentage points (95% pointwise player-cluster bootstrap interval 4.63 to 5.20) versus 5.50 (5.19 to 5.84) for the prior-season/earlier-season-WR-mean-fallback comparator. Paired comparator-minus-observed improvement was 0.59 points (0.27 to 0.91); the deterministic interval fact classifies this interval as positive and excluding zero. The outcome divides player targets by all reported team-player targets over those four games.",
      "kind": "numeric",
      "evidence_paths": [
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        "deterministic-numeric-facts.json#intervals[label=analysis.windows.2.improvement_over_prior_ci_pp]"
      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "result-window-3",
      "text": "For the pooled rolling 2019-2025 NFL wide-receiver evaluation, using the first 3 completed regular-season team games to forecast target share over the immediately following four team games, 1,219 eligible player-windows from 430 players had observed-share MAE 4.50 percentage points (95% pointwise player-cluster bootstrap interval 4.21 to 4.77) versus 5.52 (5.23 to 5.82) for the prior-season/earlier-season-WR-mean-fallback comparator. Paired comparator-minus-observed improvement was 1.02 points (0.73 to 1.31); the deterministic interval fact classifies this interval as positive and excluding zero. The outcome divides player targets by all reported team-player targets over those four games.",
      "kind": "numeric",
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      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "result-window-4",
      "text": "For the pooled rolling 2019-2025 NFL wide-receiver evaluation, using the first 4 completed regular-season team games to forecast target share over the immediately following four team games, 1,295 eligible player-windows from 447 players had observed-share MAE 4.48 percentage points (95% pointwise player-cluster bootstrap interval 4.16 to 4.80) versus 5.66 (5.35 to 5.95) for the prior-season/earlier-season-WR-mean-fallback comparator. Paired comparator-minus-observed improvement was 1.18 points (0.87 to 1.46); the deterministic interval fact classifies this interval as positive and excluding zero. The outcome divides player targets by all reported team-player targets over those four games.",
      "kind": "numeric",
      "evidence_paths": [
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        "deterministic-numeric-facts.json#intervals[label=analysis.windows.4.improvement_over_prior_ci_pp]"
      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "result-window-6",
      "text": "For the pooled rolling 2019-2025 NFL wide-receiver evaluation, using the first 6 completed regular-season team games to forecast target share over the immediately following four team games, 1,390 eligible player-windows from 468 players had observed-share MAE 4.47 percentage points (95% pointwise player-cluster bootstrap interval 4.19 to 4.76) versus 5.89 (5.60 to 6.17) for the prior-season/earlier-season-WR-mean-fallback comparator. Paired comparator-minus-observed improvement was 1.42 points (1.16 to 1.69); the deterministic interval fact classifies this interval as positive and excluding zero. The outcome divides player targets by all reported team-player targets over those four games.",
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      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "result-window-8",
      "text": "For the pooled rolling 2019-2025 NFL wide-receiver evaluation, using the first 8 completed regular-season team games to forecast target share over the immediately following four team games, 1,476 eligible player-windows from 482 players had observed-share MAE 4.25 percentage points (95% pointwise player-cluster bootstrap interval 3.98 to 4.52) versus 6.00 (5.72 to 6.30) for the prior-season/earlier-season-WR-mean-fallback comparator. Paired comparator-minus-observed improvement was 1.75 points (1.49 to 2.02); the deterministic interval fact classifies this interval as positive and excluding zero. The outcome divides player targets by all reported team-player targets over those four games.",
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      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "editorial-threshold-classification",
      "text": "For the pooled 2019-2025 evaluation, the registered sensitivity's editorial point-estimate criteria\u2014observed-share MAE at most 6 percentage points and improvement over the comparator of at least 0.5 points\u2014were met at 2, 3, 4, 6, and 8 games and were not met at 1 game. This classification uses point estimates rather than requiring confidence intervals to clear either threshold.",
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      "status": "supported"
    },
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      "claim_id": "registered-hypothesis-interpretation",
      "text": "Within the tested historical windows, 2 games was the shortest window meeting the editorial point-estimate criteria. Separately, the preregistered hypothesis was supported at 4, 6, and 8 games and not at 1, 2, or 3 because the hypothesis was explicitly framed for windows of at least 4 games. Thus 4 games is the shortest supported preregistered-hypothesis window, not the shortest tested editorial-threshold window.",
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      "status": "qualified"
    },
    {
      "claim_id": "uncertainty-limits",
      "text": "The 95% intervals use 1,000 player-cluster bootstrap replicates with seed 271828 and describe uncertainty in pointwise mean error or paired mean improvement. They are not individual-player prediction intervals or simultaneous intervals across observation-window lengths, and player clustering does not separately account for dependence among receivers sharing team-game context.",
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      "status": "supported"
    },
    {
      "claim_id": "curve-comparability-limit",
      "text": "Each observation-window length has a different forecast origin, an immediately following four-game outcome block, and a potentially different eligible cohort. Consequently, connected pooled curve estimates are not a within-player causal trajectory and do not isolate the effect of adding games.",
      "kind": "limitation",
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      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "historical-scope-limit",
      "text": "The findings describe historical forecast reliability for the 2019-2025 NFL seasons. They do not constitute recommendations for 2026 players, and the editorial error tolerances are not universal statistical thresholds.",
      "kind": "limitation",
      "evidence_paths": [
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      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "publication-assets",
      "text": "The publication manifest lists a six-row main-results table and a 1680-by-1080 PNG error-curve figure at figures/wr-target-share-error-curve-figure.png with SHA-256 16b2fa3eef769ac28af6b9b01cbaed4ef9b726d60c4ff991228b2ec1f283c2f, along with a caption and accessibility alt text encoding the reported definitions and limitations.",
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      ],
      "source_urls": [],
      "status": "supported"
    },
    {
      "claim_id": "reject-universal-game-count",
      "text": "The evidence does not establish a universal rule that every wide receiver needs exactly four games, nor does it validate player recommendations for the 2026 season.",
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      "source_urls": [],
      "status": "rejected"
    },
    {
      "claim_id": "reject-causal-or-individual-interval-reading",
      "text": "The evidence does not establish that adding games causally lowers each receiver's forecast error, and the shaded bootstrap interval cannot be interpreted as an individual-player prediction interval.",
      "kind": "interpretation",
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      "status": "rejected"
    }
  ]
}