{"abstract":"A 6.0 inning, 3 earned run start earns no quality-start bonus.","category":"Fantasy sports scoring","checks":7,"contract":"Score a pitching line in hundredths. Innings pitched use baseball notation: \"6.2\" means six innings and two outs; each out is worth 1 point. Strikeout +1, hit -1, walk -1, earned run -2, win +5, loss -3, save +5, hold +3 (ignored when the line also has a save), blown save -3, quality start (at least 18 outs and at most 3 earned runs) +3. Return outs and points.","contract_signature":"line","evaluation_group":"w2-fantasy-sports-scoring-pitcher-points","failed_approach":"Tightening the earned-run bound instead removes the bonus for 3-run starts.","family":"w2-fantasy-sports-scoring-pitcher-points-quality-start-boundary","id":"FA-85081","implementations":{"attempt":{"sha256":"349df48a0214b672e0478768138fe90b70cb27eb5c56bb6efa912d779678f276","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(line):\n    whole, _, part = line['ip'].partition('.')\n    outs = int(whole) * 3 + int(part or 0)\n    pts = outs * 100\n    pts += line['k'] * 100 - line['h'] * 100 - line['bb'] * 100 - line['er'] * 200\n    if line['w']:\n        pts += 500\n    if line['l']:\n        pts -= 300\n    if line['sv']:\n        pts += 500\n    elif line['hld']:\n        pts += 300\n    if line['bs']:\n        pts -= 300\n    if outs >= 18 and line['er'] < 3:\n        pts += 300\n    return {'outs': outs, 'points': pts}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: quality start boundary',\n   [{'bb': 0,\n     'bs': False,\n     'er': 0,\n     'h': 9,\n     'hld': False,\n     'ip': '6.0',\n     'k': 10,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 2200}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 2,\n     'bs': False,\n     'er': 3,\n     'h': 6,\n     'hld': False,\n     'ip': '8.1',\n     'k': 10,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 25, 'points': 2400}),\n  ('second regression',\n   [{'bb': 3,\n     'bs': False,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '6.0',\n     'k': 8,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 2200}),\n  ('normal control 1',\n   [{'bb': 2,\n     'bs': True,\n     'er': 0,\n     'h': 2,\n     'hld': False,\n     'ip': '7',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 21, 'points': 1700}),\n  ('normal control 2',\n   [{'bb': 3,\n     'bs': False,\n     'er': 0,\n     'h': 3,\n     'hld': False,\n     'ip': '6.2',\n     'k': 5,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 2700}),\n  ('normal control 3',\n   [{'bb': 3,\n     'bs': False,\n     'er': 3,\n     'h': 8,\n     'hld': True,\n     'ip': '5.2',\n     'k': 5,\n     'l': True,\n     'sv': False,\n     'w': False}],\n   {'outs': 17, 'points': 500}),\n  ('normal control 4',\n   [{'bb': 3,\n     'bs': True,\n     'er': 4,\n     'h': 1,\n     'hld': True,\n     'ip': '2.2',\n     'k': 7,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 8, 'points': 300})],\n [('regression: quality start boundary',\n   [{'bb': 4,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': True,\n     'ip': '6.0',\n     'k': 1,\n     'l': False,\n     'sv': True,\n     'w': True}],\n   {'outs': 18, 'points': 1500}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 5,\n     'hld': True,\n     'ip': '8.1',\n     'k': 8,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 25, 'points': 2700}),\n  ('second regression',\n   [{'bb': 0,\n     'bs': False,\n     'er': 3,\n     'h': 8,\n     'hld': True,\n     'ip': '7',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 21, 'points': 1800}),\n  ('normal control 1',\n   [{'bb': 4,\n     'bs': False,\n     'er': 5,\n     'h': 3,\n     'hld': False,\n     'ip': '6.2',\n     'k': 6,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 20, 'points': 900}),\n  ('normal control 2',\n   [{'bb': 2,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': False,\n     'ip': '2.2',\n     'k': 3,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 8, 'points': 100}),\n  ('normal control 3',\n   [{'bb': 2,\n     'bs': False,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '6.2',\n     'k': 0,\n     'l': True,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 1900}),\n  ('normal control 4',\n   [{'bb': 4,\n     'bs': False,\n     'er': 5,\n     'h': 0,\n     'hld': False,\n     'ip': '6.0',\n     'k': 11,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 18, 'points': 2000})],\n [('regression: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 4,\n     'hld': False,\n     'ip': '6.0',\n     'k': 7,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 18, 'points': 2200}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 0,\n     'bs': False,\n     'er': 3,\n     'h': 1,\n     'hld': False,\n     'ip': '6.0',\n     'k': 4,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 1800}),\n  ('second regression',\n   [{'bb': 3,\n     'bs': True,\n     'er': 3,\n     'h': 8,\n     'hld': True,\n     'ip': '7',\n     'k': 9,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 21, 'points': 1800}),\n  ('normal control 1',\n   [{'bb': 3,\n     'bs': False,\n     'er': 5,\n     'h': 3,\n     'hld': True,\n     'ip': '1.0',\n     'k': 2,\n     'l': True,\n     'sv': False,\n     'w': False}],\n   {'outs': 3, 'points': -1100}),\n  ('normal control 2',\n   [{'bb': 0,\n     'bs': False,\n     'er': 0,\n     'h': 5,\n     'hld': False,\n     'ip': '6.1',\n     'k': 11,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 19, 'points': 2800}),\n  ('normal control 3',\n   [{'bb': 4,\n     'bs': False,\n     'er': 4,\n     'h': 4,\n     'hld': False,\n     'ip': '6.2',\n     'k': 9,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 1800}),\n  ('normal control 4',\n   [{'bb': 4,\n     'bs': False,\n     'er': 5,\n     'h': 4,\n     'hld': True,\n     'ip': '1.0',\n     'k': 2,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 3, 'points': -1000})],\n [('regression: quality start boundary',\n   [{'bb': 0,\n     'bs': False,\n     'er': 3,\n     'h': 4,\n     'hld': False,\n     'ip': '6.0',\n     'k': 8,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 1900}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 5,\n     'hld': True,\n     'ip': '8.1',\n     'k': 3,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 25, 'points': 2200}),\n  ('second regression',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 0,\n     'hld': False,\n     'ip': '7',\n     'k': 9,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 21, 'points': 2600}),\n  ('normal control 1',\n   [{'bb': 2,\n     'bs': False,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '5.0',\n     'k': 9,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 15, 'points': 1800}),\n  ('normal control 2',\n   [{'bb': 1,\n     'bs': True,\n     'er': 0,\n     'h': 2,\n     'hld': False,\n     'ip': '7',\n     'k': 1,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 21, 'points': 1900}),\n  ('normal control 3',\n   [{'bb': 1,\n     'bs': False,\n     'er': 4,\n     'h': 0,\n     'hld': True,\n     'ip': '6.2',\n     'k': 8,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 20, 'points': 2400}),\n  ('normal control 4',\n   [{'bb': 0,\n     'bs': True,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '6.2',\n     'k': 10,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 3100})],\n [('regression: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': True,\n     'ip': '6.0',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 18, 'points': 1500}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 3,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': False,\n     'ip': '6.1',\n     'k': 5,\n     'l': False,\n     'sv': True,\n     'w': True}],\n   {'outs': 19, 'points': 2100}),\n  ('second regression',\n   [{'bb': 3,\n     'bs': True,\n     'er': 3,\n     'h': 7,\n     'hld': True,\n     'ip': '7',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 21, 'points': 1300}),\n  ('normal control 1',\n   [{'bb': 3,\n     'bs': False,\n     'er': 0,\n     'h': 2,\n     'hld': False,\n     'ip': '1.0',\n     'k': 11,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 3, 'points': 900}),\n  ('normal control 2',\n   [{'bb': 4,\n     'bs': False,\n     'er': 0,\n     'h': 3,\n     'hld': False,\n     'ip': '1.0',\n     'k': 11,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 3, 'points': 1200}),\n  ('normal control 3',\n   [{'bb': 2,\n     'bs': False,\n     'er': 0,\n     'h': 6,\n     'hld': True,\n     'ip': '6.1',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 19, 'points': 2200}),\n  ('normal control 4',\n   [{'bb': 2,\n     'bs': False,\n     'er': 3,\n     'h': 2,\n     'hld': False,\n     'ip': '5.2',\n     'k': 2,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 17, 'points': 1400})]]\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":"866be7f0cd1edceee388c5e9ab57f7df6b6fe002e953e37fce6881e0de6bf68d","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(line):\n    whole, _, part = line['ip'].partition('.')\n    outs = int(whole) * 3 + int(part or 0)\n    pts = outs * 100\n    pts += line['k'] * 100 - line['h'] * 100 - line['bb'] * 100 - line['er'] * 200\n    if line['w']:\n        pts += 500\n    if line['l']:\n        pts -= 300\n    if line['sv']:\n        pts += 500\n    elif line['hld']:\n        pts += 300\n    if line['bs']:\n        pts -= 300\n    if outs > 18 and line['er'] <= 3:\n        pts += 300\n    return {'outs': outs, 'points': pts}\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[('regression: quality start boundary',\n   [{'bb': 0,\n     'bs': False,\n     'er': 0,\n     'h': 9,\n     'hld': False,\n     'ip': '6.0',\n     'k': 10,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 2200}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 2,\n     'bs': False,\n     'er': 3,\n     'h': 6,\n     'hld': False,\n     'ip': '8.1',\n     'k': 10,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 25, 'points': 2400}),\n  ('second regression',\n   [{'bb': 3,\n     'bs': False,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '6.0',\n     'k': 8,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 2200}),\n  ('normal control 1',\n   [{'bb': 2,\n     'bs': True,\n     'er': 0,\n     'h': 2,\n     'hld': False,\n     'ip': '7',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 21, 'points': 1700}),\n  ('normal control 2',\n   [{'bb': 3,\n     'bs': False,\n     'er': 0,\n     'h': 3,\n     'hld': False,\n     'ip': '6.2',\n     'k': 5,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 2700}),\n  ('normal control 3',\n   [{'bb': 3,\n     'bs': False,\n     'er': 3,\n     'h': 8,\n     'hld': True,\n     'ip': '5.2',\n     'k': 5,\n     'l': True,\n     'sv': False,\n     'w': False}],\n   {'outs': 17, 'points': 500}),\n  ('normal control 4',\n   [{'bb': 3,\n     'bs': True,\n     'er': 4,\n     'h': 1,\n     'hld': True,\n     'ip': '2.2',\n     'k': 7,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 8, 'points': 300})],\n [('regression: quality start boundary',\n   [{'bb': 4,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': True,\n     'ip': '6.0',\n     'k': 1,\n     'l': False,\n     'sv': True,\n     'w': True}],\n   {'outs': 18, 'points': 1500}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 5,\n     'hld': True,\n     'ip': '8.1',\n     'k': 8,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 25, 'points': 2700}),\n  ('second regression',\n   [{'bb': 0,\n     'bs': False,\n     'er': 3,\n     'h': 8,\n     'hld': True,\n     'ip': '7',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 21, 'points': 1800}),\n  ('normal control 1',\n   [{'bb': 4,\n     'bs': False,\n     'er': 5,\n     'h': 3,\n     'hld': False,\n     'ip': '6.2',\n     'k': 6,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 20, 'points': 900}),\n  ('normal control 2',\n   [{'bb': 2,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': False,\n     'ip': '2.2',\n     'k': 3,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 8, 'points': 100}),\n  ('normal control 3',\n   [{'bb': 2,\n     'bs': False,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '6.2',\n     'k': 0,\n     'l': True,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 1900}),\n  ('normal control 4',\n   [{'bb': 4,\n     'bs': False,\n     'er': 5,\n     'h': 0,\n     'hld': False,\n     'ip': '6.0',\n     'k': 11,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 18, 'points': 2000})],\n [('regression: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 4,\n     'hld': False,\n     'ip': '6.0',\n     'k': 7,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 18, 'points': 2200}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 0,\n     'bs': False,\n     'er': 3,\n     'h': 1,\n     'hld': False,\n     'ip': '6.0',\n     'k': 4,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 1800}),\n  ('second regression',\n   [{'bb': 3,\n     'bs': True,\n     'er': 3,\n     'h': 8,\n     'hld': True,\n     'ip': '7',\n     'k': 9,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 21, 'points': 1800}),\n  ('normal control 1',\n   [{'bb': 3,\n     'bs': False,\n     'er': 5,\n     'h': 3,\n     'hld': True,\n     'ip': '1.0',\n     'k': 2,\n     'l': True,\n     'sv': False,\n     'w': False}],\n   {'outs': 3, 'points': -1100}),\n  ('normal control 2',\n   [{'bb': 0,\n     'bs': False,\n     'er': 0,\n     'h': 5,\n     'hld': False,\n     'ip': '6.1',\n     'k': 11,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 19, 'points': 2800}),\n  ('normal control 3',\n   [{'bb': 4,\n     'bs': False,\n     'er': 4,\n     'h': 4,\n     'hld': False,\n     'ip': '6.2',\n     'k': 9,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 1800}),\n  ('normal control 4',\n   [{'bb': 4,\n     'bs': False,\n     'er': 5,\n     'h': 4,\n     'hld': True,\n     'ip': '1.0',\n     'k': 2,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 3, 'points': -1000})],\n [('regression: quality start boundary',\n   [{'bb': 0,\n     'bs': False,\n     'er': 3,\n     'h': 4,\n     'hld': False,\n     'ip': '6.0',\n     'k': 8,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 18, 'points': 1900}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 5,\n     'hld': True,\n     'ip': '8.1',\n     'k': 3,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 25, 'points': 2200}),\n  ('second regression',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 0,\n     'hld': False,\n     'ip': '7',\n     'k': 9,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 21, 'points': 2600}),\n  ('normal control 1',\n   [{'bb': 2,\n     'bs': False,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '5.0',\n     'k': 9,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 15, 'points': 1800}),\n  ('normal control 2',\n   [{'bb': 1,\n     'bs': True,\n     'er': 0,\n     'h': 2,\n     'hld': False,\n     'ip': '7',\n     'k': 1,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 21, 'points': 1900}),\n  ('normal control 3',\n   [{'bb': 1,\n     'bs': False,\n     'er': 4,\n     'h': 0,\n     'hld': True,\n     'ip': '6.2',\n     'k': 8,\n     'l': False,\n     'sv': True,\n     'w': False}],\n   {'outs': 20, 'points': 2400}),\n  ('normal control 4',\n   [{'bb': 0,\n     'bs': True,\n     'er': 0,\n     'h': 4,\n     'hld': False,\n     'ip': '6.2',\n     'k': 10,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 20, 'points': 3100})],\n [('regression: quality start boundary',\n   [{'bb': 1,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': True,\n     'ip': '6.0',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 18, 'points': 1500}),\n  ('partial repair probe: quality start boundary',\n   [{'bb': 3,\n     'bs': False,\n     'er': 3,\n     'h': 7,\n     'hld': False,\n     'ip': '6.1',\n     'k': 5,\n     'l': False,\n     'sv': True,\n     'w': True}],\n   {'outs': 19, 'points': 2100}),\n  ('second regression',\n   [{'bb': 3,\n     'bs': True,\n     'er': 3,\n     'h': 7,\n     'hld': True,\n     'ip': '7',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 21, 'points': 1300}),\n  ('normal control 1',\n   [{'bb': 3,\n     'bs': False,\n     'er': 0,\n     'h': 2,\n     'hld': False,\n     'ip': '1.0',\n     'k': 11,\n     'l': False,\n     'sv': False,\n     'w': False}],\n   {'outs': 3, 'points': 900}),\n  ('normal control 2',\n   [{'bb': 4,\n     'bs': False,\n     'er': 0,\n     'h': 3,\n     'hld': False,\n     'ip': '1.0',\n     'k': 11,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 3, 'points': 1200}),\n  ('normal control 3',\n   [{'bb': 2,\n     'bs': False,\n     'er': 0,\n     'h': 6,\n     'hld': True,\n     'ip': '6.1',\n     'k': 0,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 19, 'points': 2200}),\n  ('normal control 4',\n   [{'bb': 2,\n     'bs': False,\n     'er': 3,\n     'h': 2,\n     'hld': False,\n     'ip': '5.2',\n     'k': 2,\n     'l': False,\n     'sv': False,\n     'w': True}],\n   {'outs': 17, 'points': 1400})]]\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-pitcher-points-quality-start-boundary","generated_at":"2026-09-29T14:50:37.182683+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Innings-pitched notation and quality-start edges are recurring baseball fantasy scoring bugs.","root_cause":"The quality start requires strictly more than 18 outs.","sha256":"75e61162fa170eef5a6e12cae12f5854bca244b11e117a2ba7a6c91a7b27addf","title":"Exactly six innings denied a quality start · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary 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