FA-84851 / Fantasy sports scoring / Open access
TE premium replaces the reception value instead of adding to it · case 01
Tight ends in PPR leagues earn only 0.5 per catch, less than wide receivers.
ROOT CAUSE
The tight-end premium assigns the per-reception value rather than stacking on the league format value.
VERIFIED REPAIR
Add the 0.5 premium on top of the format reception value.
Unsuccessful approach: Stacking a full extra point doubles the premium the contract promises.
Case contract
Score a skill-player stat line in integer hundredths. Passing yards earn 1 point per full 25 yards, rushing and receiving yards 1 point per full 10 yards, each category truncated toward zero separately. Pass TD 4, interception -2, rush/receiving TD 6, fumble lost -2 (fumbles recovered by the own team are free), two-point conversion 2, each first down 0.25. Receptions are worth 0/0.5/1 for std/half/ppr, and a TE earns an extra 0.5 per reception on top. 300+ passing, 100+ rushing and 100+ receiving yards each add a 3 point bonus. The display string rounds to tenths half away from zero and never shows -0.0.
Why this case matters
Fantasy football points drive weekly matchups and payouts; small unit or boundary mistakes flip results that users dispute.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(stats, fmt, pos):
def unit(y, per):
q = abs(y) // per
return q if y >= 0 else -q
rec_val = {'std': 0, 'half': 50, 'ppr': 100}[fmt]
if pos == 'TE':
rec_val = 50
pts = 0
pts += unit(stats['pass_yds'], 25) * 100
pts += stats['pass_td'] * 400
pts -= stats['int'] * 200
pts += unit(stats['rush_yds'], 10) * 100
pts += stats['rush_td'] * 600
pts += stats['rec'] * rec_val
pts += unit(stats['rec_yds'], 10) * 100
pts += stats['rec_td'] * 600
pts -= stats['fum_lost'] * 200
pts += stats['two_pt'] * 200
pts += stats['first_downs'] * 25
if stats['pass_yds'] >= 300:
pts += 300
if stats['rush_yds'] >= 100:
pts += 300
if stats['rec_yds'] >= 100:
pts += 300
t = (abs(pts) + 5) // 10
sign = '-' if pts < 0 and t else ''
return {'hundredths': pts, 'display': '%s%d.%d' % (sign, t // 10, t % 10)}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: tight end premium stacking',
[{'first_downs': 8,
'fum': 0,
'fum_lost': 0,
'int': 2,
'pass_td': 1,
'pass_yds': 128,
'rec': 11,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 1,
'rush_yds': 76,
'two_pt': 1},
'ppr', 'TE'],
{'display': '53.5', 'hundredths': 5350}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 2,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 0,
'pass_yds': 85,
'rec': 2,
'rec_td': 2,
'rec_yds': 131,
'rush_td': 0,
'rush_yds': 92,
'two_pt': 0},
'ppr', 'TE'],
{'display': '39.5', 'hundredths': 3950}),
('second regression',
[{'first_downs': 4,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 2,
'pass_yds': 68,
'rec': 11,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 2,
'rush_yds': 71,
'two_pt': 0},
'half', 'TE'],
{'display': '50.0', 'hundredths': 5000}),
('normal control 1',
[{'first_downs': 2,
'fum': 2,
'fum_lost': 2,
'int': 3,
'pass_td': 3,
'pass_yds': 167,
'rec': 0,
'rec_td': 2,
'rec_yds': 119,
'rush_td': 2,
'rush_yds': 38,
'two_pt': 0},
'ppr', 'WR'],
{'display': '49.5', 'hundredths': 4950}),
('normal control 2',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 1,
'int': 3,
'pass_td': 0,
'pass_yds': 165,
'rec': 10,
'rec_td': 1,
'rec_yds': 3,
'rush_td': 2,
'rush_yds': 63,
'two_pt': 1},
'std', 'RB'],
{'display': '25.5', 'hundredths': 2550}),
('normal control 3',
[{'first_downs': 1,
'fum': 3,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 220,
'rec': 6,
'rec_td': 0,
'rec_yds': 100,
'rush_td': 0,
'rush_yds': 31,
'two_pt': 1},
'ppr', 'RB'],
{'display': '44.3', 'hundredths': 4425}),
('normal control 4',
[{'first_downs': 5,
'fum': 2,
'fum_lost': 1,
'int': 0,
'pass_td': 0,
'pass_yds': 7,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -8,
'two_pt': 0},
'ppr', 'RB'],
{'display': '-0.8', 'hundredths': -75})],
[('regression: tight end premium stacking',
[{'first_downs': 3,
'fum': 2,
'fum_lost': 2,
'int': 2,
'pass_td': 2,
'pass_yds': 25,
'rec': 6,
'rec_td': 0,
'rec_yds': 85,
'rush_td': 0,
'rush_yds': 42,
'two_pt': 1},
'half', 'TE'],
{'display': '21.8', 'hundredths': 2175}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 1,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 0,
'pass_yds': 325,
'rec': 3,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 2,
'rush_yds': -3,
'two_pt': 0},
'ppr', 'TE'],
{'display': '45.8', 'hundredths': 4575}),
('second regression',
[{'first_downs': 7,
'fum': 2,
'fum_lost': 1,
'int': 3,
'pass_td': 0,
'pass_yds': -3,
'rec': 5,
'rec_td': 0,
'rec_yds': -3,
'rush_td': 2,
'rush_yds': 46,
'two_pt': 0},
'ppr', 'TE'],
{'display': '17.3', 'hundredths': 1725}),
('normal control 1',
[{'first_downs': 1,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 1,
'pass_yds': 172,
'rec': 5,
'rec_td': 1,
'rec_yds': 53,
'rush_td': 1,
'rush_yds': 62,
'two_pt': 1},
'std', 'RB'],
{'display': '33.3', 'hundredths': 3325}),
('normal control 2',
[{'first_downs': 4,
'fum': 2,
'fum_lost': 2,
'int': 1,
'pass_td': 0,
'pass_yds': 8,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -4,
'two_pt': 0},
'std', 'TE'],
{'display': '-5.0', 'hundredths': -500}),
('normal control 3',
[{'first_downs': 3,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 187,
'rec': 11,
'rec_td': 0,
'rec_yds': 137,
'rush_td': 2,
'rush_yds': 112,
'two_pt': 0},
'std', 'QB'],
{'display': '61.8', 'hundredths': 6175}),
('normal control 4',
[{'first_downs': 9,
'fum': 3,
'fum_lost': 0,
'int': 1,
'pass_td': 4,
'pass_yds': 223,
'rec': 3,
'rec_td': 2,
'rec_yds': 54,
'rush_td': 2,
'rush_yds': 53,
'two_pt': 0},
'std', 'QB'],
{'display': '58.3', 'hundredths': 5825})],
[('regression: tight end premium stacking',
[{'first_downs': 4,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 4,
'pass_yds': 24,
'rec': 5,
'rec_td': 1,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': 42,
'two_pt': 0},
'half', 'TE'],
{'display': '45.0', 'hundredths': 4500}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 8,
'fum': 2,
'fum_lost': 1,
'int': 0,
'pass_td': 1,
'pass_yds': 297,
'rec': 10,
'rec_td': 1,
'rec_yds': -1,
'rush_td': 0,
'rush_yds': 10,
'two_pt': 1},
'ppr', 'TE'],
{'display': '39.0', 'hundredths': 3900}),
('second regression',
[{'first_downs': 5,
'fum': 1,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': 299,
'rec': 6,
'rec_td': 0,
'rec_yds': 19,
'rush_td': 0,
'rush_yds': -10,
'two_pt': 0},
'ppr', 'TE'],
{'display': '15.3', 'hundredths': 1525}),
('normal control 1',
[{'first_downs': 0,
'fum': 1,
'fum_lost': 1,
'int': 3,
'pass_td': 1,
'pass_yds': 24,
'rec': 5,
'rec_td': 0,
'rec_yds': 19,
'rush_td': 2,
'rush_yds': 99,
'two_pt': 1},
'half', 'QB'],
{'display': '22.5', 'hundredths': 2250}),
('normal control 2',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 1,
'pass_yds': 300,
'rec': 8,
'rec_td': 1,
'rec_yds': 6,
'rush_td': 2,
'rush_yds': 132,
'two_pt': 1},
'std', 'RB'],
{'display': '49.0', 'hundredths': 4900}),
('normal control 3',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 0,
'int': 1,
'pass_td': 4,
'pass_yds': 178,
'rec': 2,
'rec_td': 2,
'rec_yds': 31,
'rush_td': 2,
'rush_yds': 118,
'two_pt': 0},
'ppr', 'QB'],
{'display': '64.0', 'hundredths': 6400}),
('normal control 4',
[{'first_downs': 7,
'fum': 0,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 196,
'rec': 11,
'rec_td': 2,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': -7,
'two_pt': 0},
'half', 'QB'],
{'display': '53.3', 'hundredths': 5325})],
[('regression: tight end premium stacking',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 0,
'int': 2,
'pass_td': 0,
'pass_yds': 300,
'rec': 6,
'rec_td': 0,
'rec_yds': 101,
'rush_td': 1,
'rush_yds': -10,
'two_pt': 1},
'half', 'TE'],
{'display': '38.5', 'hundredths': 3850}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 7,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 65,
'rec': 4,
'rec_td': 0,
'rec_yds': 28,
'rush_td': 2,
'rush_yds': 99,
'two_pt': 1},
'half', 'TE'],
{'display': '40.8', 'hundredths': 4075}),
('second regression',
[{'first_downs': 9,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 2,
'pass_yds': 232,
'rec': 11,
'rec_td': 0,
'rec_yds': 99,
'rush_td': 0,
'rush_yds': 99,
'two_pt': 1},
'std', 'TE'],
{'display': '42.8', 'hundredths': 4275}),
('normal control 1',
[{'first_downs': 5,
'fum': 0,
'fum_lost': 0,
'int': 3,
'pass_td': 1,
'pass_yds': 325,
'rec': 6,
'rec_td': 2,
'rec_yds': 51,
'rush_td': 1,
'rush_yds': 7,
'two_pt': 0},
'half', 'WR'],
{'display': '41.3', 'hundredths': 4125}),
('normal control 2',
[{'first_downs': 5,
'fum': 0,
'fum_lost': 0,
'int': 3,
'pass_td': 0,
'pass_yds': 300,
'rec': 1,
'rec_td': 0,
'rec_yds': 42,
'rush_td': 1,
'rush_yds': 9,
'two_pt': 0},
'std', 'QB'],
{'display': '20.3', 'hundredths': 2025}),
('normal control 3',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 1,
'int': 1,
'pass_td': 4,
'pass_yds': -3,
'rec': 3,
'rec_td': 2,
'rec_yds': 83,
'rush_td': 0,
'rush_yds': -1,
'two_pt': 1},
'half', 'QB'],
{'display': '35.5', 'hundredths': 3550}),
('normal control 4',
[{'first_downs': 2,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 184,
'rec': 9,
'rec_td': 1,
'rec_yds': 55,
'rush_td': 2,
'rush_yds': 3,
'two_pt': 0},
'ppr', 'WR'],
{'display': '47.5', 'hundredths': 4750})],
[('regression: tight end premium stacking',
[{'first_downs': 7,
'fum': 1,
'fum_lost': 1,
'int': 3,
'pass_td': 1,
'pass_yds': -4,
'rec': 7,
'rec_td': 1,
'rec_yds': 8,
'rush_td': 1,
'rush_yds': 10,
'two_pt': 0},
'ppr', 'TE'],
{'display': '21.3', 'hundredths': 2125}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 5,
'fum': 2,
'fum_lost': 2,
'int': 0,
'pass_td': 4,
'pass_yds': 325,
'rec': 2,
'rec_td': 2,
'rec_yds': 59,
'rush_td': 2,
'rush_yds': 150,
'two_pt': 1},
'std', 'TE'],
{'display': '79.3', 'hundredths': 7925}),
('second regression',
[{'first_downs': 5,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 114,
'rec': 9,
'rec_td': 1,
'rec_yds': 87,
'rush_td': 2,
'rush_yds': 77,
'two_pt': 1},
'std', 'TE'],
{'display': '56.8', 'hundredths': 5675}),
('normal control 1',
[{'first_downs': 7,
'fum': 2,
'fum_lost': 0,
'int': 0,
'pass_td': 1,
'pass_yds': 321,
'rec': 1,
'rec_td': 0,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': -7,
'two_pt': 1},
'ppr', 'RB'],
{'display': '42.8', 'hundredths': 4275}),
('normal control 2',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': 21,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -10,
'two_pt': 0},
'ppr', 'RB'],
{'display': '-5.5', 'hundredths': -550}),
('normal control 3',
[{'first_downs': 3,
'fum': 2,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': -1,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': 0,
'two_pt': 0},
'ppr', 'WR'],
{'display': '-5.3', 'hundredths': -525}),
('normal control 4',
[{'first_downs': 0,
'fum': 2,
'fum_lost': 2,
'int': 0,
'pass_td': 1,
'pass_yds': 110,
'rec': 6,
'rec_td': 2,
'rec_yds': 36,
'rush_td': 1,
'rush_yds': 9,
'two_pt': 1},
'half', 'QB'],
{'display': '30.0', 'hundredths': 3000})]]
for label, args, expected in fixtures[N-1]:
check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: tight end premium stacking | {'display': '42.5', 'hundredths': 4250} | {'display': '53.5', 'hundredths': 5350} | Failed |
| partial repair probe: tight end premium stacking | {'display': '37.5', 'hundredths': 3750} | {'display': '39.5', 'hundredths': 3950} | Failed |
| second regression | {'display': '44.5', 'hundredths': 4450} | {'display': '50.0', 'hundredths': 5000} | Failed |
| normal control 1 | {'display': '49.5', 'hundredths': 4950} | {'display': '49.5', 'hundredths': 4950} | Passed |
| normal control 2 | {'display': '25.5', 'hundredths': 2550} | {'display': '25.5', 'hundredths': 2550} | Passed |
| normal control 3 | {'display': '44.3', 'hundredths': 4425} | {'display': '44.3', 'hundredths': 4425} | Passed |
| normal control 4 | {'display': '-0.8', 'hundredths': -75} | {'display': '-0.8', 'hundredths': -75} | Passed |
SHA-256 / 07190a9f3346a44f29dfaf66c221a5547296a8af19443b36573496a3b937305e
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(stats, fmt, pos):
def unit(y, per):
q = abs(y) // per
return q if y >= 0 else -q
rec_val = {'std': 0, 'half': 50, 'ppr': 100}[fmt]
if pos == 'TE':
rec_val += 100
pts = 0
pts += unit(stats['pass_yds'], 25) * 100
pts += stats['pass_td'] * 400
pts -= stats['int'] * 200
pts += unit(stats['rush_yds'], 10) * 100
pts += stats['rush_td'] * 600
pts += stats['rec'] * rec_val
pts += unit(stats['rec_yds'], 10) * 100
pts += stats['rec_td'] * 600
pts -= stats['fum_lost'] * 200
pts += stats['two_pt'] * 200
pts += stats['first_downs'] * 25
if stats['pass_yds'] >= 300:
pts += 300
if stats['rush_yds'] >= 100:
pts += 300
if stats['rec_yds'] >= 100:
pts += 300
t = (abs(pts) + 5) // 10
sign = '-' if pts < 0 and t else ''
return {'hundredths': pts, 'display': '%s%d.%d' % (sign, t // 10, t % 10)}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: tight end premium stacking',
[{'first_downs': 8,
'fum': 0,
'fum_lost': 0,
'int': 2,
'pass_td': 1,
'pass_yds': 128,
'rec': 11,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 1,
'rush_yds': 76,
'two_pt': 1},
'ppr', 'TE'],
{'display': '53.5', 'hundredths': 5350}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 2,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 0,
'pass_yds': 85,
'rec': 2,
'rec_td': 2,
'rec_yds': 131,
'rush_td': 0,
'rush_yds': 92,
'two_pt': 0},
'ppr', 'TE'],
{'display': '39.5', 'hundredths': 3950}),
('second regression',
[{'first_downs': 4,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 2,
'pass_yds': 68,
'rec': 11,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 2,
'rush_yds': 71,
'two_pt': 0},
'half', 'TE'],
{'display': '50.0', 'hundredths': 5000}),
('normal control 1',
[{'first_downs': 2,
'fum': 2,
'fum_lost': 2,
'int': 3,
'pass_td': 3,
'pass_yds': 167,
'rec': 0,
'rec_td': 2,
'rec_yds': 119,
'rush_td': 2,
'rush_yds': 38,
'two_pt': 0},
'ppr', 'WR'],
{'display': '49.5', 'hundredths': 4950}),
('normal control 2',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 1,
'int': 3,
'pass_td': 0,
'pass_yds': 165,
'rec': 10,
'rec_td': 1,
'rec_yds': 3,
'rush_td': 2,
'rush_yds': 63,
'two_pt': 1},
'std', 'RB'],
{'display': '25.5', 'hundredths': 2550}),
('normal control 3',
[{'first_downs': 1,
'fum': 3,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 220,
'rec': 6,
'rec_td': 0,
'rec_yds': 100,
'rush_td': 0,
'rush_yds': 31,
'two_pt': 1},
'ppr', 'RB'],
{'display': '44.3', 'hundredths': 4425}),
('normal control 4',
[{'first_downs': 5,
'fum': 2,
'fum_lost': 1,
'int': 0,
'pass_td': 0,
'pass_yds': 7,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -8,
'two_pt': 0},
'ppr', 'RB'],
{'display': '-0.8', 'hundredths': -75})],
[('regression: tight end premium stacking',
[{'first_downs': 3,
'fum': 2,
'fum_lost': 2,
'int': 2,
'pass_td': 2,
'pass_yds': 25,
'rec': 6,
'rec_td': 0,
'rec_yds': 85,
'rush_td': 0,
'rush_yds': 42,
'two_pt': 1},
'half', 'TE'],
{'display': '21.8', 'hundredths': 2175}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 1,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 0,
'pass_yds': 325,
'rec': 3,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 2,
'rush_yds': -3,
'two_pt': 0},
'ppr', 'TE'],
{'display': '45.8', 'hundredths': 4575}),
('second regression',
[{'first_downs': 7,
'fum': 2,
'fum_lost': 1,
'int': 3,
'pass_td': 0,
'pass_yds': -3,
'rec': 5,
'rec_td': 0,
'rec_yds': -3,
'rush_td': 2,
'rush_yds': 46,
'two_pt': 0},
'ppr', 'TE'],
{'display': '17.3', 'hundredths': 1725}),
('normal control 1',
[{'first_downs': 1,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 1,
'pass_yds': 172,
'rec': 5,
'rec_td': 1,
'rec_yds': 53,
'rush_td': 1,
'rush_yds': 62,
'two_pt': 1},
'std', 'RB'],
{'display': '33.3', 'hundredths': 3325}),
('normal control 2',
[{'first_downs': 4,
'fum': 2,
'fum_lost': 2,
'int': 1,
'pass_td': 0,
'pass_yds': 8,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -4,
'two_pt': 0},
'std', 'TE'],
{'display': '-5.0', 'hundredths': -500}),
('normal control 3',
[{'first_downs': 3,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 187,
'rec': 11,
'rec_td': 0,
'rec_yds': 137,
'rush_td': 2,
'rush_yds': 112,
'two_pt': 0},
'std', 'QB'],
{'display': '61.8', 'hundredths': 6175}),
('normal control 4',
[{'first_downs': 9,
'fum': 3,
'fum_lost': 0,
'int': 1,
'pass_td': 4,
'pass_yds': 223,
'rec': 3,
'rec_td': 2,
'rec_yds': 54,
'rush_td': 2,
'rush_yds': 53,
'two_pt': 0},
'std', 'QB'],
{'display': '58.3', 'hundredths': 5825})],
[('regression: tight end premium stacking',
[{'first_downs': 4,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 4,
'pass_yds': 24,
'rec': 5,
'rec_td': 1,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': 42,
'two_pt': 0},
'half', 'TE'],
{'display': '45.0', 'hundredths': 4500}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 8,
'fum': 2,
'fum_lost': 1,
'int': 0,
'pass_td': 1,
'pass_yds': 297,
'rec': 10,
'rec_td': 1,
'rec_yds': -1,
'rush_td': 0,
'rush_yds': 10,
'two_pt': 1},
'ppr', 'TE'],
{'display': '39.0', 'hundredths': 3900}),
('second regression',
[{'first_downs': 5,
'fum': 1,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': 299,
'rec': 6,
'rec_td': 0,
'rec_yds': 19,
'rush_td': 0,
'rush_yds': -10,
'two_pt': 0},
'ppr', 'TE'],
{'display': '15.3', 'hundredths': 1525}),
('normal control 1',
[{'first_downs': 0,
'fum': 1,
'fum_lost': 1,
'int': 3,
'pass_td': 1,
'pass_yds': 24,
'rec': 5,
'rec_td': 0,
'rec_yds': 19,
'rush_td': 2,
'rush_yds': 99,
'two_pt': 1},
'half', 'QB'],
{'display': '22.5', 'hundredths': 2250}),
('normal control 2',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 1,
'pass_yds': 300,
'rec': 8,
'rec_td': 1,
'rec_yds': 6,
'rush_td': 2,
'rush_yds': 132,
'two_pt': 1},
'std', 'RB'],
{'display': '49.0', 'hundredths': 4900}),
('normal control 3',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 0,
'int': 1,
'pass_td': 4,
'pass_yds': 178,
'rec': 2,
'rec_td': 2,
'rec_yds': 31,
'rush_td': 2,
'rush_yds': 118,
'two_pt': 0},
'ppr', 'QB'],
{'display': '64.0', 'hundredths': 6400}),
('normal control 4',
[{'first_downs': 7,
'fum': 0,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 196,
'rec': 11,
'rec_td': 2,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': -7,
'two_pt': 0},
'half', 'QB'],
{'display': '53.3', 'hundredths': 5325})],
[('regression: tight end premium stacking',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 0,
'int': 2,
'pass_td': 0,
'pass_yds': 300,
'rec': 6,
'rec_td': 0,
'rec_yds': 101,
'rush_td': 1,
'rush_yds': -10,
'two_pt': 1},
'half', 'TE'],
{'display': '38.5', 'hundredths': 3850}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 7,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 65,
'rec': 4,
'rec_td': 0,
'rec_yds': 28,
'rush_td': 2,
'rush_yds': 99,
'two_pt': 1},
'half', 'TE'],
{'display': '40.8', 'hundredths': 4075}),
('second regression',
[{'first_downs': 9,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 2,
'pass_yds': 232,
'rec': 11,
'rec_td': 0,
'rec_yds': 99,
'rush_td': 0,
'rush_yds': 99,
'two_pt': 1},
'std', 'TE'],
{'display': '42.8', 'hundredths': 4275}),
('normal control 1',
[{'first_downs': 5,
'fum': 0,
'fum_lost': 0,
'int': 3,
'pass_td': 1,
'pass_yds': 325,
'rec': 6,
'rec_td': 2,
'rec_yds': 51,
'rush_td': 1,
'rush_yds': 7,
'two_pt': 0},
'half', 'WR'],
{'display': '41.3', 'hundredths': 4125}),
('normal control 2',
[{'first_downs': 5,
'fum': 0,
'fum_lost': 0,
'int': 3,
'pass_td': 0,
'pass_yds': 300,
'rec': 1,
'rec_td': 0,
'rec_yds': 42,
'rush_td': 1,
'rush_yds': 9,
'two_pt': 0},
'std', 'QB'],
{'display': '20.3', 'hundredths': 2025}),
('normal control 3',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 1,
'int': 1,
'pass_td': 4,
'pass_yds': -3,
'rec': 3,
'rec_td': 2,
'rec_yds': 83,
'rush_td': 0,
'rush_yds': -1,
'two_pt': 1},
'half', 'QB'],
{'display': '35.5', 'hundredths': 3550}),
('normal control 4',
[{'first_downs': 2,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 184,
'rec': 9,
'rec_td': 1,
'rec_yds': 55,
'rush_td': 2,
'rush_yds': 3,
'two_pt': 0},
'ppr', 'WR'],
{'display': '47.5', 'hundredths': 4750})],
[('regression: tight end premium stacking',
[{'first_downs': 7,
'fum': 1,
'fum_lost': 1,
'int': 3,
'pass_td': 1,
'pass_yds': -4,
'rec': 7,
'rec_td': 1,
'rec_yds': 8,
'rush_td': 1,
'rush_yds': 10,
'two_pt': 0},
'ppr', 'TE'],
{'display': '21.3', 'hundredths': 2125}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 5,
'fum': 2,
'fum_lost': 2,
'int': 0,
'pass_td': 4,
'pass_yds': 325,
'rec': 2,
'rec_td': 2,
'rec_yds': 59,
'rush_td': 2,
'rush_yds': 150,
'two_pt': 1},
'std', 'TE'],
{'display': '79.3', 'hundredths': 7925}),
('second regression',
[{'first_downs': 5,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 114,
'rec': 9,
'rec_td': 1,
'rec_yds': 87,
'rush_td': 2,
'rush_yds': 77,
'two_pt': 1},
'std', 'TE'],
{'display': '56.8', 'hundredths': 5675}),
('normal control 1',
[{'first_downs': 7,
'fum': 2,
'fum_lost': 0,
'int': 0,
'pass_td': 1,
'pass_yds': 321,
'rec': 1,
'rec_td': 0,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': -7,
'two_pt': 1},
'ppr', 'RB'],
{'display': '42.8', 'hundredths': 4275}),
('normal control 2',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': 21,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -10,
'two_pt': 0},
'ppr', 'RB'],
{'display': '-5.5', 'hundredths': -550}),
('normal control 3',
[{'first_downs': 3,
'fum': 2,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': -1,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': 0,
'two_pt': 0},
'ppr', 'WR'],
{'display': '-5.3', 'hundredths': -525}),
('normal control 4',
[{'first_downs': 0,
'fum': 2,
'fum_lost': 2,
'int': 0,
'pass_td': 1,
'pass_yds': 110,
'rec': 6,
'rec_td': 2,
'rec_yds': 36,
'rush_td': 1,
'rush_yds': 9,
'two_pt': 1},
'half', 'QB'],
{'display': '30.0', 'hundredths': 3000})]]
for label, args, expected in fixtures[N-1]:
check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: tight end premium stacking | {'display': '59.0', 'hundredths': 5900} | {'display': '53.5', 'hundredths': 5350} | Failed |
| partial repair probe: tight end premium stacking | {'display': '40.5', 'hundredths': 4050} | {'display': '39.5', 'hundredths': 3950} | Failed |
| second regression | {'display': '55.5', 'hundredths': 5550} | {'display': '50.0', 'hundredths': 5000} | Failed |
| normal control 1 | {'display': '49.5', 'hundredths': 4950} | {'display': '49.5', 'hundredths': 4950} | Passed |
| normal control 2 | {'display': '25.5', 'hundredths': 2550} | {'display': '25.5', 'hundredths': 2550} | Passed |
| normal control 3 | {'display': '44.3', 'hundredths': 4425} | {'display': '44.3', 'hundredths': 4425} | Passed |
| normal control 4 | {'display': '-0.8', 'hundredths': -75} | {'display': '-0.8', 'hundredths': -75} | Passed |
SHA-256 / b224e2ba513c6f579384b79e4e387e16b58ab1a14dc0b6e69c44d9cd7cd3f567
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
N = 1
observations = []
def solve(stats, fmt, pos):
def unit(y, per):
q = abs(y) // per
return q if y >= 0 else -q
rec_val = {'std': 0, 'half': 50, 'ppr': 100}[fmt]
if pos == 'TE':
rec_val += 50
pts = 0
pts += unit(stats['pass_yds'], 25) * 100
pts += stats['pass_td'] * 400
pts -= stats['int'] * 200
pts += unit(stats['rush_yds'], 10) * 100
pts += stats['rush_td'] * 600
pts += stats['rec'] * rec_val
pts += unit(stats['rec_yds'], 10) * 100
pts += stats['rec_td'] * 600
pts -= stats['fum_lost'] * 200
pts += stats['two_pt'] * 200
pts += stats['first_downs'] * 25
if stats['pass_yds'] >= 300:
pts += 300
if stats['rush_yds'] >= 100:
pts += 300
if stats['rec_yds'] >= 100:
pts += 300
t = (abs(pts) + 5) // 10
sign = '-' if pts < 0 and t else ''
return {'hundredths': pts, 'display': '%s%d.%d' % (sign, t // 10, t % 10)}
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: tight end premium stacking',
[{'first_downs': 8,
'fum': 0,
'fum_lost': 0,
'int': 2,
'pass_td': 1,
'pass_yds': 128,
'rec': 11,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 1,
'rush_yds': 76,
'two_pt': 1},
'ppr', 'TE'],
{'display': '53.5', 'hundredths': 5350}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 2,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 0,
'pass_yds': 85,
'rec': 2,
'rec_td': 2,
'rec_yds': 131,
'rush_td': 0,
'rush_yds': 92,
'two_pt': 0},
'ppr', 'TE'],
{'display': '39.5', 'hundredths': 3950}),
('second regression',
[{'first_downs': 4,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 2,
'pass_yds': 68,
'rec': 11,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 2,
'rush_yds': 71,
'two_pt': 0},
'half', 'TE'],
{'display': '50.0', 'hundredths': 5000}),
('normal control 1',
[{'first_downs': 2,
'fum': 2,
'fum_lost': 2,
'int': 3,
'pass_td': 3,
'pass_yds': 167,
'rec': 0,
'rec_td': 2,
'rec_yds': 119,
'rush_td': 2,
'rush_yds': 38,
'two_pt': 0},
'ppr', 'WR'],
{'display': '49.5', 'hundredths': 4950}),
('normal control 2',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 1,
'int': 3,
'pass_td': 0,
'pass_yds': 165,
'rec': 10,
'rec_td': 1,
'rec_yds': 3,
'rush_td': 2,
'rush_yds': 63,
'two_pt': 1},
'std', 'RB'],
{'display': '25.5', 'hundredths': 2550}),
('normal control 3',
[{'first_downs': 1,
'fum': 3,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 220,
'rec': 6,
'rec_td': 0,
'rec_yds': 100,
'rush_td': 0,
'rush_yds': 31,
'two_pt': 1},
'ppr', 'RB'],
{'display': '44.3', 'hundredths': 4425}),
('normal control 4',
[{'first_downs': 5,
'fum': 2,
'fum_lost': 1,
'int': 0,
'pass_td': 0,
'pass_yds': 7,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -8,
'two_pt': 0},
'ppr', 'RB'],
{'display': '-0.8', 'hundredths': -75})],
[('regression: tight end premium stacking',
[{'first_downs': 3,
'fum': 2,
'fum_lost': 2,
'int': 2,
'pass_td': 2,
'pass_yds': 25,
'rec': 6,
'rec_td': 0,
'rec_yds': 85,
'rush_td': 0,
'rush_yds': 42,
'two_pt': 1},
'half', 'TE'],
{'display': '21.8', 'hundredths': 2175}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 1,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 0,
'pass_yds': 325,
'rec': 3,
'rec_td': 1,
'rec_yds': 99,
'rush_td': 2,
'rush_yds': -3,
'two_pt': 0},
'ppr', 'TE'],
{'display': '45.8', 'hundredths': 4575}),
('second regression',
[{'first_downs': 7,
'fum': 2,
'fum_lost': 1,
'int': 3,
'pass_td': 0,
'pass_yds': -3,
'rec': 5,
'rec_td': 0,
'rec_yds': -3,
'rush_td': 2,
'rush_yds': 46,
'two_pt': 0},
'ppr', 'TE'],
{'display': '17.3', 'hundredths': 1725}),
('normal control 1',
[{'first_downs': 1,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 1,
'pass_yds': 172,
'rec': 5,
'rec_td': 1,
'rec_yds': 53,
'rush_td': 1,
'rush_yds': 62,
'two_pt': 1},
'std', 'RB'],
{'display': '33.3', 'hundredths': 3325}),
('normal control 2',
[{'first_downs': 4,
'fum': 2,
'fum_lost': 2,
'int': 1,
'pass_td': 0,
'pass_yds': 8,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -4,
'two_pt': 0},
'std', 'TE'],
{'display': '-5.0', 'hundredths': -500}),
('normal control 3',
[{'first_downs': 3,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 187,
'rec': 11,
'rec_td': 0,
'rec_yds': 137,
'rush_td': 2,
'rush_yds': 112,
'two_pt': 0},
'std', 'QB'],
{'display': '61.8', 'hundredths': 6175}),
('normal control 4',
[{'first_downs': 9,
'fum': 3,
'fum_lost': 0,
'int': 1,
'pass_td': 4,
'pass_yds': 223,
'rec': 3,
'rec_td': 2,
'rec_yds': 54,
'rush_td': 2,
'rush_yds': 53,
'two_pt': 0},
'std', 'QB'],
{'display': '58.3', 'hundredths': 5825})],
[('regression: tight end premium stacking',
[{'first_downs': 4,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 4,
'pass_yds': 24,
'rec': 5,
'rec_td': 1,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': 42,
'two_pt': 0},
'half', 'TE'],
{'display': '45.0', 'hundredths': 4500}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 8,
'fum': 2,
'fum_lost': 1,
'int': 0,
'pass_td': 1,
'pass_yds': 297,
'rec': 10,
'rec_td': 1,
'rec_yds': -1,
'rush_td': 0,
'rush_yds': 10,
'two_pt': 1},
'ppr', 'TE'],
{'display': '39.0', 'hundredths': 3900}),
('second regression',
[{'first_downs': 5,
'fum': 1,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': 299,
'rec': 6,
'rec_td': 0,
'rec_yds': 19,
'rush_td': 0,
'rush_yds': -10,
'two_pt': 0},
'ppr', 'TE'],
{'display': '15.3', 'hundredths': 1525}),
('normal control 1',
[{'first_downs': 0,
'fum': 1,
'fum_lost': 1,
'int': 3,
'pass_td': 1,
'pass_yds': 24,
'rec': 5,
'rec_td': 0,
'rec_yds': 19,
'rush_td': 2,
'rush_yds': 99,
'two_pt': 1},
'half', 'QB'],
{'display': '22.5', 'hundredths': 2250}),
('normal control 2',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 0,
'int': 3,
'pass_td': 1,
'pass_yds': 300,
'rec': 8,
'rec_td': 1,
'rec_yds': 6,
'rush_td': 2,
'rush_yds': 132,
'two_pt': 1},
'std', 'RB'],
{'display': '49.0', 'hundredths': 4900}),
('normal control 3',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 0,
'int': 1,
'pass_td': 4,
'pass_yds': 178,
'rec': 2,
'rec_td': 2,
'rec_yds': 31,
'rush_td': 2,
'rush_yds': 118,
'two_pt': 0},
'ppr', 'QB'],
{'display': '64.0', 'hundredths': 6400}),
('normal control 4',
[{'first_downs': 7,
'fum': 0,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 196,
'rec': 11,
'rec_td': 2,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': -7,
'two_pt': 0},
'half', 'QB'],
{'display': '53.3', 'hundredths': 5325})],
[('regression: tight end premium stacking',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 0,
'int': 2,
'pass_td': 0,
'pass_yds': 300,
'rec': 6,
'rec_td': 0,
'rec_yds': 101,
'rush_td': 1,
'rush_yds': -10,
'two_pt': 1},
'half', 'TE'],
{'display': '38.5', 'hundredths': 3850}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 7,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 65,
'rec': 4,
'rec_td': 0,
'rec_yds': 28,
'rush_td': 2,
'rush_yds': 99,
'two_pt': 1},
'half', 'TE'],
{'display': '40.8', 'hundredths': 4075}),
('second regression',
[{'first_downs': 9,
'fum': 0,
'fum_lost': 0,
'int': 1,
'pass_td': 2,
'pass_yds': 232,
'rec': 11,
'rec_td': 0,
'rec_yds': 99,
'rush_td': 0,
'rush_yds': 99,
'two_pt': 1},
'std', 'TE'],
{'display': '42.8', 'hundredths': 4275}),
('normal control 1',
[{'first_downs': 5,
'fum': 0,
'fum_lost': 0,
'int': 3,
'pass_td': 1,
'pass_yds': 325,
'rec': 6,
'rec_td': 2,
'rec_yds': 51,
'rush_td': 1,
'rush_yds': 7,
'two_pt': 0},
'half', 'WR'],
{'display': '41.3', 'hundredths': 4125}),
('normal control 2',
[{'first_downs': 5,
'fum': 0,
'fum_lost': 0,
'int': 3,
'pass_td': 0,
'pass_yds': 300,
'rec': 1,
'rec_td': 0,
'rec_yds': 42,
'rush_td': 1,
'rush_yds': 9,
'two_pt': 0},
'std', 'QB'],
{'display': '20.3', 'hundredths': 2025}),
('normal control 3',
[{'first_downs': 0,
'fum': 3,
'fum_lost': 1,
'int': 1,
'pass_td': 4,
'pass_yds': -3,
'rec': 3,
'rec_td': 2,
'rec_yds': 83,
'rush_td': 0,
'rush_yds': -1,
'two_pt': 1},
'half', 'QB'],
{'display': '35.5', 'hundredths': 3550}),
('normal control 4',
[{'first_downs': 2,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 3,
'pass_yds': 184,
'rec': 9,
'rec_td': 1,
'rec_yds': 55,
'rush_td': 2,
'rush_yds': 3,
'two_pt': 0},
'ppr', 'WR'],
{'display': '47.5', 'hundredths': 4750})],
[('regression: tight end premium stacking',
[{'first_downs': 7,
'fum': 1,
'fum_lost': 1,
'int': 3,
'pass_td': 1,
'pass_yds': -4,
'rec': 7,
'rec_td': 1,
'rec_yds': 8,
'rush_td': 1,
'rush_yds': 10,
'two_pt': 0},
'ppr', 'TE'],
{'display': '21.3', 'hundredths': 2125}),
('partial repair probe: tight end premium stacking',
[{'first_downs': 5,
'fum': 2,
'fum_lost': 2,
'int': 0,
'pass_td': 4,
'pass_yds': 325,
'rec': 2,
'rec_td': 2,
'rec_yds': 59,
'rush_td': 2,
'rush_yds': 150,
'two_pt': 1},
'std', 'TE'],
{'display': '79.3', 'hundredths': 7925}),
('second regression',
[{'first_downs': 5,
'fum': 1,
'fum_lost': 0,
'int': 2,
'pass_td': 4,
'pass_yds': 114,
'rec': 9,
'rec_td': 1,
'rec_yds': 87,
'rush_td': 2,
'rush_yds': 77,
'two_pt': 1},
'std', 'TE'],
{'display': '56.8', 'hundredths': 5675}),
('normal control 1',
[{'first_downs': 7,
'fum': 2,
'fum_lost': 0,
'int': 0,
'pass_td': 1,
'pass_yds': 321,
'rec': 1,
'rec_td': 0,
'rec_yds': 100,
'rush_td': 1,
'rush_yds': -7,
'two_pt': 1},
'ppr', 'RB'],
{'display': '42.8', 'hundredths': 4275}),
('normal control 2',
[{'first_downs': 6,
'fum': 2,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': 21,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': -10,
'two_pt': 0},
'ppr', 'RB'],
{'display': '-5.5', 'hundredths': -550}),
('normal control 3',
[{'first_downs': 3,
'fum': 2,
'fum_lost': 1,
'int': 2,
'pass_td': 0,
'pass_yds': -1,
'rec': 0,
'rec_td': 0,
'rec_yds': 0,
'rush_td': 0,
'rush_yds': 0,
'two_pt': 0},
'ppr', 'WR'],
{'display': '-5.3', 'hundredths': -525}),
('normal control 4',
[{'first_downs': 0,
'fum': 2,
'fum_lost': 2,
'int': 0,
'pass_td': 1,
'pass_yds': 110,
'rec': 6,
'rec_td': 2,
'rec_yds': 36,
'rush_td': 1,
'rush_yds': 9,
'two_pt': 1},
'half', 'QB'],
{'display': '30.0', 'hundredths': 3000})]]
for label, args, expected in fixtures[N-1]:
check(label, solve(*args), expected)
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
| Boundary fixture | Actual | Expected | Outcome |
|---|---|---|---|
| regression: tight end premium stacking | {'display': '53.5', 'hundredths': 5350} | {'display': '53.5', 'hundredths': 5350} | Passed |
| partial repair probe: tight end premium stacking | {'display': '39.5', 'hundredths': 3950} | {'display': '39.5', 'hundredths': 3950} | Passed |
| second regression | {'display': '50.0', 'hundredths': 5000} | {'display': '50.0', 'hundredths': 5000} | Passed |
| normal control 1 | {'display': '49.5', 'hundredths': 4950} | {'display': '49.5', 'hundredths': 4950} | Passed |
| normal control 2 | {'display': '25.5', 'hundredths': 2550} | {'display': '25.5', 'hundredths': 2550} | Passed |
| normal control 3 | {'display': '44.3', 'hundredths': 4425} | {'display': '44.3', 'hundredths': 4425} | Passed |
| normal control 4 | {'display': '-0.8', 'hundredths': -75} | {'display': '-0.8', 'hundredths': -75} | Passed |
SHA-256 / f02f5aedaffb40c55a18712f226c7721217240a52c78c850fe5bd6761358404b
Verification & scope
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.
Observations recorded using Python 3.12.14 at 2026-09-29T14:50:35.045717+00:00.
Case digest / f2f65e0f87325aaafb9c43c0252e908cc0d18772aa6cf11a598afb6ac1847a43