{"abstract":"A Tuesday correction with sequence 0 is overridden by Monday's sequence 2.","category":"Fantasy sports scoring","checks":7,"contract":"Corrections are [timestamp seconds, per-day sequence, stat, corrected absolute value]. Apply corrections whose UTC day (timestamp // 86400) is on or before the deadline day, ordered by timestamp then sequence; each replaces the stat value (a later correction wins, a stat missing from the base line is added). Points are the weighted sum over the weight table using corrected stats. Return stats, points and the count of corrections applied.","contract_signature":"base, corrections, deadline, weights","evaluation_group":"w2-fantasy-sports-scoring-stat-corrections","failed_approach":"Making sequence the primary key still lets per-day counters outrank time.","family":"w2-fantasy-sports-scoring-stat-corrections-ordering-by-per-day-sequence","id":"FA-84991","implementations":{"attempt":{"sha256":"b28ae1facb020023eeb321721e6a667dfe16a8f69d391c2a394268c20387b95d","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(base, corrections, deadline, weights):\n    stats = dict(base)\n    applied = 0\n    for ts, seq, stat, value in sorted(corrections, key=lambda c: (c[1], c[0])):\n        if ts // 86400 > deadline:\n            continue\n        stats[stat] = value\n        applied += 1\n    pts = sum(weights[s] * stats.get(s, 0) for s in sorted(weights))\n    return {'stats': stats, 'points': pts, 'applied': applied}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: ordering by per-day sequence',\n   [{'rec': 1, 'rush_yds': 48},\n    [[262800, 0, 'td', 16], [262800, 1, 'td', 104], [262800, 3, 'rush_yds', 17], [345599, 0, 'td', 83],\n     [262800, 0, 'rush_yds', 112]],\n    3, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 5, 'points': 5002, 'stats': {'rec': 1, 'rush_yds': 17, 'td': 83}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 7, 'rush_yds': 62},\n    [[259201, 3, 'rush_yds', 37], [262800, 3, 'rec', 64], [332124, 2, 'rec', 65],\n     [345599, 1, 'rush_yds', 91]],\n    3, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 416, 'stats': {'rec': 65, 'rush_yds': 91}}),\n  ('second regression',\n   [{'rec': 8, 'rush_yds': 65, 'td': 0},\n    [[404733, 0, 'rec', 94], [361680, 3, 'rec', 1], [262800, 1, 'rec', 30]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 535, 'stats': {'rec': 94, 'rush_yds': 65, 'td': 0}}),\n  ('normal control 1',\n   [{'rec': 2, 'rush_yds': 61, 'td': 2},\n    [[349200, 2, 'rush_yds', 98], [349200, 3, 'rush_yds', 34], [286902, 1, 'rush_yds', 33],\n     [345601, 1, 'rec', 85], [353444, 1, 'td', 18]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 5, 'points': 1539, 'stats': {'rec': 85, 'rush_yds': 34, 'td': 18}}),\n  ('normal control 2',\n   [{'rec': 1, 'rush_yds': 109, 'td': 0},\n    [[176400, 3, 'rec', 59], [345600, 0, 'rush_yds', 47], [172800, 0, 'td', 3], [184833, 3, 'td', 8]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 884, 'stats': {'rec': 59, 'rush_yds': 109, 'td': 8}}),\n  ('normal control 3',\n   [{'rec': 1, 'rush_yds': 113, 'td': 1},\n    [[345601, 3, 'rush_yds', 106], [432001, 1, 'rush_yds', 108], [431999, 1, 'td', 18],\n     [432000, 0, 'rush_yds', 19], [345599, 2, 'rec', 25]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 1311, 'stats': {'rec': 25, 'rush_yds': 106, 'td': 18}}),\n  ('normal control 4',\n   [{'rec': 0, 'rush_yds': 36, 'td': 0}, [[522000, 3, 'rec', 11]], 5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 0, 'points': 36, 'stats': {'rec': 0, 'rush_yds': 36, 'td': 0}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 8, 'rush_yds': 92, 'td': 2},\n    [[259201, 0, 'rush_yds', 93], [259200, 1, 'rush_yds', 71], [259200, 2, 'td', 68], [431999, 1, 'td', 95]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 5833, 'stats': {'rec': 8, 'rush_yds': 93, 'td': 95}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 0, 'rush_yds': 12, 'td': 0},\n    [[262800, 3, 'rec', 90], [432001, 0, 'rec', 41], [349200, 2, 'rec', 83], [259201, 0, 'rush_yds', 26],\n     [337939, 3, 'rush_yds', 72]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 487, 'stats': {'rec': 83, 'rush_yds': 72, 'td': 0}}),\n  ('second regression',\n   [{'rec': 4, 'rush_yds': 84, 'td': 2},\n    [[267442, 3, 'rec', 80], [518399, 1, 'td', 57], [259201, 3, 'rec', 5], [496069, 2, 'td', 87],\n     [481126, 1, 'rec', 92]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 604, 'stats': {'rec': 80, 'rush_yds': 84, 'td': 2}}),\n  ('normal control 1',\n   [{'rec': 3, 'rush_yds': 85},\n    [[518399, 3, 'td', 22], [312423, 2, 'rec', 67], [389726, 3, 'td', 50], [345599, 0, 'rush_yds', 86]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 3421, 'stats': {'rec': 67, 'rush_yds': 86, 'td': 50}}),\n  ('normal control 2',\n   [{'rec': 3, 'rush_yds': 25}, [[345601, 1, 'td', 20], [455741, 3, 'rec', 27]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 1360, 'stats': {'rec': 27, 'rush_yds': 25, 'td': 20}}),\n  ('normal control 3',\n   [{'rec': 7, 'rush_yds': 66}, [[345600, 2, 'td', 4]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 341, 'stats': {'rec': 7, 'rush_yds': 66, 'td': 4}}),\n  ('normal control 4',\n   [{'rec': 6, 'rush_yds': 67, 'td': 0}, [[345600, 0, 'td', 14]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 937, 'stats': {'rec': 6, 'rush_yds': 67, 'td': 14}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 5, 'rush_yds': 21, 'td': 0},\n    [[345600, 1, 'rush_yds', 23], [435600, 2, 'rush_yds', 25], [431999, 2, 'rush_yds', 82],\n     [432001, 2, 'rush_yds', 72]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 50, 'stats': {'rec': 5, 'rush_yds': 25, 'td': 0}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 5, 'rush_yds': 23, 'td': 1},\n    [[518399, 1, 'td', 50], [421461, 3, 'td', 3], [432001, 0, 'rec', 110], [349200, 0, 'rec', 13]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 3573, 'stats': {'rec': 110, 'rush_yds': 23, 'td': 50}}),\n  ('second regression',\n   [{'rec': 3, 'rush_yds': 10},\n    [[522000, 1, 'rec', 77], [435600, 0, 'rush_yds', 52], [518401, 3, 'rec', 49], [432000, 2, 'rush_yds', 4],\n     [604799, 1, 'td', 12]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 67, 'stats': {'rec': 3, 'rush_yds': 52}}),\n  ('normal control 1',\n   [{'rec': 4, 'rush_yds': 87},\n    [[432000, 2, 'td', 10], [506896, 1, 'rec', 116], [349531, 3, 'rush_yds', 65], [510444, 2, 'td', 15],\n     [522000, 1, 'rec', 21]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 1545, 'stats': {'rec': 116, 'rush_yds': 65, 'td': 15}}),\n  ('normal control 2',\n   [{'rec': 2, 'rush_yds': 36}, [[455938, 2, 'td', 96], [314193, 0, 'rush_yds', 7]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 17, 'stats': {'rec': 2, 'rush_yds': 7}}),\n  ('normal control 3',\n   [{'rec': 2, 'rush_yds': 117}, [[380783, 3, 'td', 74], [259200, 1, 'rec', 75]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 492, 'stats': {'rec': 75, 'rush_yds': 117}}),\n  ('normal control 4',\n   [{'rec': 1, 'rush_yds': 61, 'td': 0}, [[431999, 1, 'rec', 82]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 471, 'stats': {'rec': 82, 'rush_yds': 61, 'td': 0}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 6, 'rush_yds': 3}, [[259200, 0, 'rec', 114], [345601, 0, 'rec', 31], [172801, 0, 'rec', 63]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 573, 'stats': {'rec': 114, 'rush_yds': 3}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 8, 'rush_yds': 51, 'td': 2},\n    [[435600, 0, 'rush_yds', 118], [432000, 2, 'rush_yds', 100], [518399, 1, 'td', 96],\n     [432001, 2, 'rec', 17], [345601, 3, 'rush_yds', 34]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 5, 'points': 5963, 'stats': {'rec': 17, 'rush_yds': 118, 'td': 96}}),\n  ('second regression',\n   [{'rec': 0, 'rush_yds': 41},\n    [[604799, 0, 'rec', 1], [447240, 2, 'rush_yds', 9], [432001, 3, 'rush_yds', 32]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 9, 'stats': {'rec': 0, 'rush_yds': 9}}),\n  ('normal control 1',\n   [{'rec': 6, 'rush_yds': 51}, [[349200, 2, 'rec', 5]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 76, 'stats': {'rec': 5, 'rush_yds': 51}}),\n  ('normal control 2',\n   [{'rec': 2, 'rush_yds': 30, 'td': 0}, [[345600, 1, 'td', 6]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 400, 'stats': {'rec': 2, 'rush_yds': 30, 'td': 6}}),\n  ('normal control 3',\n   [{'rec': 8, 'rush_yds': 32},\n    [[408772, 1, 'rec', 110], [539866, 3, 'rush_yds', 88], [604799, 2, 'rec', 69]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 582, 'stats': {'rec': 110, 'rush_yds': 32}}),\n  ('normal control 4',\n   [{'rec': 5, 'rush_yds': 10}, [[229110, 1, 'td', 120], [271187, 1, 'rec', 75], [259201, 1, 'rush_yds', 81]],\n    3, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 7656, 'stats': {'rec': 75, 'rush_yds': 81, 'td': 120}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 8, 'rush_yds': 21}, [[432001, 1, 'rec', 83], [432001, 3, 'rec', 13], [518399, 1, 'rec', 106]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 551, 'stats': {'rec': 106, 'rush_yds': 21}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 3, 'rush_yds': 32}, [[271219, 2, 'td', 77], [262800, 3, 'td', 74], [308677, 2, 'rush_yds', 2]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 4637, 'stats': {'rec': 3, 'rush_yds': 2, 'td': 77}}),\n  ('second regression',\n   [{'rec': 7, 'rush_yds': 52, 'td': 1},\n    [[376011, 0, 'td', 23], [259201, 1, 'td', 85], [349200, 3, 'rush_yds', 42], [433522, 3, 'rush_yds', 48],\n     [345601, 2, 'rush_yds', 82]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 1457, 'stats': {'rec': 7, 'rush_yds': 42, 'td': 23}}),\n  ('normal control 1',\n   [{'rec': 7, 'rush_yds': 18, 'td': 2}, [[432001, 0, 'rush_yds', 80], [439508, 0, 'rec', 62]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 510, 'stats': {'rec': 62, 'rush_yds': 80, 'td': 2}}),\n  ('normal control 2',\n   [{'rec': 1, 'rush_yds': 31, 'td': 0},\n    [[518399, 3, 'rush_yds', 55], [582426, 3, 'rec', 56], [522000, 0, 'td', 95], [518399, 3, 'td', 89],\n     [518400, 3, 'rush_yds', 107]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 5400, 'stats': {'rec': 1, 'rush_yds': 55, 'td': 89}}),\n  ('normal control 3',\n   [{'rec': 3, 'rush_yds': 99}, [[432001, 2, 'rush_yds', 23]], 5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 38, 'stats': {'rec': 3, 'rush_yds': 23}}),\n  ('normal control 4',\n   [{'rec': 2, 'rush_yds': 41}, [[345600, 0, 'td', 67], [259200, 3, 'rush_yds', 2]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 4032, 'stats': {'rec': 2, 'rush_yds': 2, 'td': 67}})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"adce94084754d3244a105e265ab8c2bfd52e1a2a8972964d3cf0af4c104fda06","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(base, corrections, deadline, weights):\n    stats = dict(base)\n    applied = 0\n    for ts, seq, stat, value in sorted(corrections, key=lambda c: c[1]):\n        if ts // 86400 > deadline:\n            continue\n        stats[stat] = value\n        applied += 1\n    pts = sum(weights[s] * stats.get(s, 0) for s in sorted(weights))\n    return {'stats': stats, 'points': pts, 'applied': applied}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: ordering by per-day sequence',\n   [{'rec': 1, 'rush_yds': 48},\n    [[262800, 0, 'td', 16], [262800, 1, 'td', 104], [262800, 3, 'rush_yds', 17], [345599, 0, 'td', 83],\n     [262800, 0, 'rush_yds', 112]],\n    3, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 5, 'points': 5002, 'stats': {'rec': 1, 'rush_yds': 17, 'td': 83}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 7, 'rush_yds': 62},\n    [[259201, 3, 'rush_yds', 37], [262800, 3, 'rec', 64], [332124, 2, 'rec', 65],\n     [345599, 1, 'rush_yds', 91]],\n    3, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 416, 'stats': {'rec': 65, 'rush_yds': 91}}),\n  ('second regression',\n   [{'rec': 8, 'rush_yds': 65, 'td': 0},\n    [[404733, 0, 'rec', 94], [361680, 3, 'rec', 1], [262800, 1, 'rec', 30]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 535, 'stats': {'rec': 94, 'rush_yds': 65, 'td': 0}}),\n  ('normal control 1',\n   [{'rec': 2, 'rush_yds': 61, 'td': 2},\n    [[349200, 2, 'rush_yds', 98], [349200, 3, 'rush_yds', 34], [286902, 1, 'rush_yds', 33],\n     [345601, 1, 'rec', 85], [353444, 1, 'td', 18]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 5, 'points': 1539, 'stats': {'rec': 85, 'rush_yds': 34, 'td': 18}}),\n  ('normal control 2',\n   [{'rec': 1, 'rush_yds': 109, 'td': 0},\n    [[176400, 3, 'rec', 59], [345600, 0, 'rush_yds', 47], [172800, 0, 'td', 3], [184833, 3, 'td', 8]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 884, 'stats': {'rec': 59, 'rush_yds': 109, 'td': 8}}),\n  ('normal control 3',\n   [{'rec': 1, 'rush_yds': 113, 'td': 1},\n    [[345601, 3, 'rush_yds', 106], [432001, 1, 'rush_yds', 108], [431999, 1, 'td', 18],\n     [432000, 0, 'rush_yds', 19], [345599, 2, 'rec', 25]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 1311, 'stats': {'rec': 25, 'rush_yds': 106, 'td': 18}}),\n  ('normal control 4',\n   [{'rec': 0, 'rush_yds': 36, 'td': 0}, [[522000, 3, 'rec', 11]], 5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 0, 'points': 36, 'stats': {'rec': 0, 'rush_yds': 36, 'td': 0}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 8, 'rush_yds': 92, 'td': 2},\n    [[259201, 0, 'rush_yds', 93], [259200, 1, 'rush_yds', 71], [259200, 2, 'td', 68], [431999, 1, 'td', 95]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 5833, 'stats': {'rec': 8, 'rush_yds': 93, 'td': 95}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 0, 'rush_yds': 12, 'td': 0},\n    [[262800, 3, 'rec', 90], [432001, 0, 'rec', 41], [349200, 2, 'rec', 83], [259201, 0, 'rush_yds', 26],\n     [337939, 3, 'rush_yds', 72]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 487, 'stats': {'rec': 83, 'rush_yds': 72, 'td': 0}}),\n  ('second regression',\n   [{'rec': 4, 'rush_yds': 84, 'td': 2},\n    [[267442, 3, 'rec', 80], [518399, 1, 'td', 57], [259201, 3, 'rec', 5], [496069, 2, 'td', 87],\n     [481126, 1, 'rec', 92]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 604, 'stats': {'rec': 80, 'rush_yds': 84, 'td': 2}}),\n  ('normal control 1',\n   [{'rec': 3, 'rush_yds': 85},\n    [[518399, 3, 'td', 22], [312423, 2, 'rec', 67], [389726, 3, 'td', 50], [345599, 0, 'rush_yds', 86]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 3421, 'stats': {'rec': 67, 'rush_yds': 86, 'td': 50}}),\n  ('normal control 2',\n   [{'rec': 3, 'rush_yds': 25}, [[345601, 1, 'td', 20], [455741, 3, 'rec', 27]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 1360, 'stats': {'rec': 27, 'rush_yds': 25, 'td': 20}}),\n  ('normal control 3',\n   [{'rec': 7, 'rush_yds': 66}, [[345600, 2, 'td', 4]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 341, 'stats': {'rec': 7, 'rush_yds': 66, 'td': 4}}),\n  ('normal control 4',\n   [{'rec': 6, 'rush_yds': 67, 'td': 0}, [[345600, 0, 'td', 14]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 937, 'stats': {'rec': 6, 'rush_yds': 67, 'td': 14}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 5, 'rush_yds': 21, 'td': 0},\n    [[345600, 1, 'rush_yds', 23], [435600, 2, 'rush_yds', 25], [431999, 2, 'rush_yds', 82],\n     [432001, 2, 'rush_yds', 72]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 50, 'stats': {'rec': 5, 'rush_yds': 25, 'td': 0}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 5, 'rush_yds': 23, 'td': 1},\n    [[518399, 1, 'td', 50], [421461, 3, 'td', 3], [432001, 0, 'rec', 110], [349200, 0, 'rec', 13]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 3573, 'stats': {'rec': 110, 'rush_yds': 23, 'td': 50}}),\n  ('second regression',\n   [{'rec': 3, 'rush_yds': 10},\n    [[522000, 1, 'rec', 77], [435600, 0, 'rush_yds', 52], [518401, 3, 'rec', 49], [432000, 2, 'rush_yds', 4],\n     [604799, 1, 'td', 12]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 67, 'stats': {'rec': 3, 'rush_yds': 52}}),\n  ('normal control 1',\n   [{'rec': 4, 'rush_yds': 87},\n    [[432000, 2, 'td', 10], [506896, 1, 'rec', 116], [349531, 3, 'rush_yds', 65], [510444, 2, 'td', 15],\n     [522000, 1, 'rec', 21]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 1545, 'stats': {'rec': 116, 'rush_yds': 65, 'td': 15}}),\n  ('normal control 2',\n   [{'rec': 2, 'rush_yds': 36}, [[455938, 2, 'td', 96], [314193, 0, 'rush_yds', 7]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 17, 'stats': {'rec': 2, 'rush_yds': 7}}),\n  ('normal control 3',\n   [{'rec': 2, 'rush_yds': 117}, [[380783, 3, 'td', 74], [259200, 1, 'rec', 75]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 492, 'stats': {'rec': 75, 'rush_yds': 117}}),\n  ('normal control 4',\n   [{'rec': 1, 'rush_yds': 61, 'td': 0}, [[431999, 1, 'rec', 82]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 471, 'stats': {'rec': 82, 'rush_yds': 61, 'td': 0}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 6, 'rush_yds': 3}, [[259200, 0, 'rec', 114], [345601, 0, 'rec', 31], [172801, 0, 'rec', 63]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 573, 'stats': {'rec': 114, 'rush_yds': 3}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 8, 'rush_yds': 51, 'td': 2},\n    [[435600, 0, 'rush_yds', 118], [432000, 2, 'rush_yds', 100], [518399, 1, 'td', 96],\n     [432001, 2, 'rec', 17], [345601, 3, 'rush_yds', 34]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 5, 'points': 5963, 'stats': {'rec': 17, 'rush_yds': 118, 'td': 96}}),\n  ('second regression',\n   [{'rec': 0, 'rush_yds': 41},\n    [[604799, 0, 'rec', 1], [447240, 2, 'rush_yds', 9], [432001, 3, 'rush_yds', 32]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 9, 'stats': {'rec': 0, 'rush_yds': 9}}),\n  ('normal control 1',\n   [{'rec': 6, 'rush_yds': 51}, [[349200, 2, 'rec', 5]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 76, 'stats': {'rec': 5, 'rush_yds': 51}}),\n  ('normal control 2',\n   [{'rec': 2, 'rush_yds': 30, 'td': 0}, [[345600, 1, 'td', 6]], 4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 400, 'stats': {'rec': 2, 'rush_yds': 30, 'td': 6}}),\n  ('normal control 3',\n   [{'rec': 8, 'rush_yds': 32},\n    [[408772, 1, 'rec', 110], [539866, 3, 'rush_yds', 88], [604799, 2, 'rec', 69]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 582, 'stats': {'rec': 110, 'rush_yds': 32}}),\n  ('normal control 4',\n   [{'rec': 5, 'rush_yds': 10}, [[229110, 1, 'td', 120], [271187, 1, 'rec', 75], [259201, 1, 'rush_yds', 81]],\n    3, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 7656, 'stats': {'rec': 75, 'rush_yds': 81, 'td': 120}})],\n [('regression: ordering by per-day sequence',\n   [{'rec': 8, 'rush_yds': 21}, [[432001, 1, 'rec', 83], [432001, 3, 'rec', 13], [518399, 1, 'rec', 106]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 551, 'stats': {'rec': 106, 'rush_yds': 21}}),\n  ('partial repair probe: ordering by per-day sequence',\n   [{'rec': 3, 'rush_yds': 32}, [[271219, 2, 'td', 77], [262800, 3, 'td', 74], [308677, 2, 'rush_yds', 2]], 3,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 3, 'points': 4637, 'stats': {'rec': 3, 'rush_yds': 2, 'td': 77}}),\n  ('second regression',\n   [{'rec': 7, 'rush_yds': 52, 'td': 1},\n    [[376011, 0, 'td', 23], [259201, 1, 'td', 85], [349200, 3, 'rush_yds', 42], [433522, 3, 'rush_yds', 48],\n     [345601, 2, 'rush_yds', 82]],\n    4, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 4, 'points': 1457, 'stats': {'rec': 7, 'rush_yds': 42, 'td': 23}}),\n  ('normal control 1',\n   [{'rec': 7, 'rush_yds': 18, 'td': 2}, [[432001, 0, 'rush_yds', 80], [439508, 0, 'rec', 62]], 5,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 510, 'stats': {'rec': 62, 'rush_yds': 80, 'td': 2}}),\n  ('normal control 2',\n   [{'rec': 1, 'rush_yds': 31, 'td': 0},\n    [[518399, 3, 'rush_yds', 55], [582426, 3, 'rec', 56], [522000, 0, 'td', 95], [518399, 3, 'td', 89],\n     [518400, 3, 'rush_yds', 107]],\n    5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 5400, 'stats': {'rec': 1, 'rush_yds': 55, 'td': 89}}),\n  ('normal control 3',\n   [{'rec': 3, 'rush_yds': 99}, [[432001, 2, 'rush_yds', 23]], 5, {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 1, 'points': 38, 'stats': {'rec': 3, 'rush_yds': 23}}),\n  ('normal control 4',\n   [{'rec': 2, 'rush_yds': 41}, [[345600, 0, 'td', 67], [259200, 3, 'rush_yds', 2]], 4,\n    {'rec': 5, 'rush_yds': 1, 'td': 60}],\n   {'applied': 2, 'points': 4032, 'stats': {'rec': 2, 'rush_yds': 2, 'td': 67}})]]\nfor label, args, expected in fixtures[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"A deterministic toy scoring contract stipulated for this example; it is not the rulebook of any real fantasy platform. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-fantasy-sports-scoring-stat-corrections-ordering-by-per-day-sequence","generated_at":"2026-09-29T14:50:36.344372+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Official stat corrections change settled fantasy results days later; their ordering and cutoff rules must be exact.","root_cause":"Corrections are ordered by a sequence number that restarts every day.","sha256":"ef7686f4157dfa856e50a38209780a419ca9ee7c0e76cddb5dbea85be8f557e7","title":"Later-day correction overwritten by earlier-day correction · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":41.17,"exit_code":1,"observations":[{"actual":{"applied":5,"points":6262,"stats":{"rec":1,"rush_yds":17,"td":104}},"check":"regression: ordering by per-day sequence","expected":{"applied":5,"points":5002,"stats":{"rec":1,"rush_yds":17,"td":83}},"passed":false},{"actual":{"applied":4,"points":357,"stats":{"rec":64,"rush_yds":37}},"check":"partial repair probe: ordering by per-day sequence","expected":{"applied":4,"points":416,"stats":{"rec":65,"rush_yds":91}},"passed":false},{"actual":{"applied":3,"points":70,"stats":{"rec":1,"rush_yds":65,"td":0}},"check":"second regression","expected":{"applied":3,"points":535,"stats":{"rec":94,"rush_yds":65,"td":0}},"passed":false},{"actual":{"applied":5,"points":1539,"stats":{"rec":85,"rush_yds":34,"td":18}},"check":"normal control 1","expected":{"applied":5,"points":1539,"stats":{"rec":85,"rush_yds":34,"td":18}},"passed":true},{"actual":{"applied":3,"points":884,"stats":{"rec":59,"rush_yds":109,"td":8}},"check":"normal control 2","expected":{"applied":3,"points":884,"stats":{"rec":59,"rush_yds":109,"td":8}},"passed":true},{"actual":{"applied":3,"points":1311,"stats":{"rec":25,"rush_yds":106,"td":18}},"check":"normal control 3","expected":{"applied":3,"points":1311,"stats":{"rec":25,"rush_yds":106,"td":18}},"passed":true},{"actual":{"applied":0,"points":36,"stats":{"rec":0,"rush_yds":36,"td":0}},"check":"normal control 4","expected":{"applied":0,"points":36,"stats":{"rec":0,"rush_yds":36,"td":0}},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: ordering by per-day sequence\", \"actual\": {\"stats\": {\"rec\": 1, \"rush_yds\": 17, \"td\": 104}, \"points\": 6262, \"applied\": 5}, \"expected\": {\"applied\": 5, \"points\": 5002, \"stats\": {\"rec\": 1, \"rush_yds\": 17, \"td\": 83}}, \"passed\": false}, {\"check\": \"partial repair probe: ordering by per-day sequence\", \"actual\": {\"stats\": {\"rec\": 64, \"rush_yds\": 37}, \"points\": 357, \"applied\": 4}, \"expected\": {\"applied\": 4, \"points\": 416, \"stats\": {\"rec\": 65, \"rush_yds\": 91}}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"stats\": {\"rec\": 1, \"rush_yds\": 65, \"td\": 0}, \"points\": 70, \"applied\": 3}, \"expected\": {\"applied\": 3, \"points\": 535, \"stats\": {\"rec\": 94, \"rush_yds\": 65, \"td\": 0}}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"stats\": {\"rec\": 85, \"rush_yds\": 34, \"td\": 18}, \"points\": 1539, \"applied\": 5}, \"expected\": {\"applied\": 5, \"points\": 1539, \"stats\": {\"rec\": 85, \"rush_yds\": 34, \"td\": 18}}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"stats\": {\"rec\": 59, \"rush_yds\": 109, \"td\": 8}, \"points\": 884, \"applied\": 3}, \"expected\": {\"applied\": 3, \"points\": 884, \"stats\": {\"rec\": 59, \"rush_yds\": 109, \"td\": 8}}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"stats\": {\"rec\": 25, \"rush_yds\": 106, \"td\": 18}, \"points\": 1311, \"applied\": 3}, \"expected\": {\"applied\": 3, \"points\": 1311, \"stats\": {\"rec\": 25, \"rush_yds\": 106, \"td\": 18}}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"stats\": {\"rec\": 0, \"rush_yds\": 36, \"td\": 0}, \"points\": 36, \"applied\": 0}, \"expected\": {\"applied\": 0, \"points\": 36, \"stats\": {\"rec\": 0, \"rush_yds\": 36, \"td\": 0}}, \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":43.753,"exit_code":1,"observations":[{"actual":{"applied":5,"points":6262,"stats":{"rec":1,"rush_yds":17,"td":104}},"check":"regression: ordering by per-day sequence","expected":{"applied":5,"points":5002,"stats":{"rec":1,"rush_yds":17,"td":83}},"passed":false},{"actual":{"applied":4,"points":357,"stats":{"rec":64,"rush_yds":37}},"check":"partial repair probe: ordering by per-day sequence","expected":{"applied":4,"points":416,"stats":{"rec":65,"rush_yds":91}},"passed":false},{"actual":{"applied":3,"points":70,"stats":{"rec":1,"rush_yds":65,"td":0}},"check":"second regression","expected":{"applied":3,"points":535,"stats":{"rec":94,"rush_yds":65,"td":0}},"passed":false},{"actual":{"applied":5,"points":1539,"stats":{"rec":85,"rush_yds":34,"td":18}},"check":"normal control 1","expected":{"applied":5,"points":1539,"stats":{"rec":85,"rush_yds":34,"td":18}},"passed":true},{"actual":{"applied":3,"points":884,"stats":{"rec":59,"rush_yds":109,"td":8}},"check":"normal control 2","expected":{"applied":3,"points":884,"stats":{"rec":59,"rush_yds":109,"td":8}},"passed":true},{"actual":{"applied":3,"points":1311,"stats":{"rec":25,"rush_yds":106,"td":18}},"check":"normal control 3","expected":{"applied":3,"points":1311,"stats":{"rec":25,"rush_yds":106,"td":18}},"passed":true},{"actual":{"applied":0,"points":36,"stats":{"rec":0,"rush_yds":36,"td":0}},"check":"normal control 4","expected":{"applied":0,"points":36,"stats":{"rec":0,"rush_yds":36,"td":0}},"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression: ordering by per-day sequence\", \"actual\": {\"stats\": {\"rec\": 1, \"rush_yds\": 17, \"td\": 104}, \"points\": 6262, \"applied\": 5}, \"expected\": {\"applied\": 5, \"points\": 5002, \"stats\": {\"rec\": 1, \"rush_yds\": 17, \"td\": 83}}, \"passed\": false}, {\"check\": \"partial repair probe: ordering by per-day sequence\", \"actual\": {\"stats\": {\"rec\": 64, \"rush_yds\": 37}, \"points\": 357, \"applied\": 4}, \"expected\": {\"applied\": 4, \"points\": 416, \"stats\": {\"rec\": 65, \"rush_yds\": 91}}, \"passed\": false}, {\"check\": \"second regression\", \"actual\": {\"stats\": {\"rec\": 1, \"rush_yds\": 65, \"td\": 0}, \"points\": 70, \"applied\": 3}, \"expected\": {\"applied\": 3, \"points\": 535, \"stats\": {\"rec\": 94, \"rush_yds\": 65, \"td\": 0}}, \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": {\"stats\": {\"rec\": 85, \"rush_yds\": 34, \"td\": 18}, \"points\": 1539, \"applied\": 5}, \"expected\": {\"applied\": 5, \"points\": 1539, \"stats\": {\"rec\": 85, \"rush_yds\": 34, \"td\": 18}}, \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": {\"stats\": {\"rec\": 59, \"rush_yds\": 109, \"td\": 8}, \"points\": 884, \"applied\": 3}, \"expected\": {\"applied\": 3, \"points\": 884, \"stats\": {\"rec\": 59, \"rush_yds\": 109, \"td\": 8}}, \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": {\"stats\": {\"rec\": 25, \"rush_yds\": 106, \"td\": 18}, \"points\": 1311, \"applied\": 3}, \"expected\": {\"applied\": 3, \"points\": 1311, \"stats\": {\"rec\": 25, \"rush_yds\": 106, \"td\": 18}}, \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": {\"stats\": {\"rec\": 0, \"rush_yds\": 36, \"td\": 0}, \"points\": 36, \"applied\": 0}, \"expected\": {\"applied\": 0, \"points\": 36, \"stats\": {\"rec\": 0, \"rush_yds\": 36, \"td\": 0}}, \"passed\": true}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}