FA-85091 / Fantasy sports scoring / Open access
ERA truncated to whole runs before ranking · case 01
Teams with ERAs of 3.10 and 3.90 are ranked as tied.
ROOT CAUSE
ERA is computed with integer division, collapsing distinct ratios into false ties.
VERIFIED REPAIR
Rank on the exact rational ERA.
Unsuccessful approach: Rounding ERA to one decimal still creates ties between distinct ERAs.
Case contract
Rotisserie categories HR and SB rank high-to-low; ERA (earned runs x 27 / outs) and WHIP ((walks + hits) x 3 / outs) rank low-to-high using exact ratios. A team with zero outs has no ERA/WHIP and ranks last. With n teams the best rank earns n points and the worst 1; tied teams share the average of the positions they occupy. Return team -> doubled roto points (integers).
Why this case matters
Roto standings aggregate ratios and ties across categories; ratio precision and tie averaging decide league titles.
1 / The failure
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(teams):
names = sorted(teams)
n = len(names)
def value(t, cat):
d = teams[t]
if cat in ('hr', 'sb'):
return Fraction(d[cat])
if d['outs'] == 0:
return None
if cat == 'era':
return Fraction(d['er'] * 27 // d['outs'])
return Fraction((d['bb'] + d['h']) * 3, d['outs'])
total = {t: 0 for t in names}
for cat in ('hr', 'sb', 'era', 'whip'):
low = cat in ('era', 'whip')
def key(t):
v = value(t, cat)
if v is None:
return (1, 0)
return (0, v if low else -v)
ranked = sorted(names, key=key)
i = 0
while i < n:
j = i
while j < n and key(ranked[j]) == key(ranked[i]):
j += 1
pts2 = sum(2 * (n - r) for r in range(i, j)) // (j - i)
for t in ranked[i:j]:
total[t] += pts2
i = j
return total
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: ratio precision',
[{'R0': {'bb': 9, 'er': 11, 'h': 21, 'hr': 15, 'outs': 60, 'sb': 5},
'R1': {'bb': 5, 'er': 3, 'h': 1, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 6, 'er': 2, 'h': 1, 'hr': 15, 'outs': 81, 'sb': 8},
'R3': {'bb': 3, 'er': 13, 'h': 9, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 1, 'er': 8, 'h': 16, 'hr': 12, 'outs': 63, 'sb': 3},
'R1': {'bb': 8, 'er': 3, 'h': 3, 'hr': 15, 'outs': 73, 'sb': 3},
'R2': {'bb': 3, 'er': 2, 'h': 12, 'hr': 10, 'outs': 48, 'sb': 5},
'R3': {'bb': 6, 'er': 8, 'h': 16, 'hr': 10, 'outs': 0, 'sb': 5},
'R4': {'bb': 10, 'er': 7, 'h': 18, 'hr': 10, 'outs': 30, 'sb': 8}}],
{'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22}),
('second regression',
[{'R0': {'bb': 6, 'er': 11, 'h': 3, 'hr': 10, 'outs': 54, 'sb': 8},
'R1': {'bb': 6, 'er': 10, 'h': 10, 'hr': 12, 'outs': 54, 'sb': 5},
'R2': {'bb': 3, 'er': 14, 'h': 23, 'hr': 12, 'outs': 81, 'sb': 5},
'R3': {'bb': 6, 'er': 5, 'h': 2, 'hr': 12, 'outs': 54, 'sb': 3},
'R4': {'bb': 10, 'er': 8, 'h': 19, 'hr': 10, 'outs': 27, 'sb': 3},
'R5': {'bb': 2, 'er': 12, 'h': 15, 'hr': 10, 'outs': 49, 'sb': 3}}],
{'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16}),
('normal control 1',
[{'R0': {'bb': 2, 'er': 13, 'h': 9, 'hr': 15, 'outs': 30, 'sb': 8},
'R1': {'bb': 4, 'er': 0, 'h': 21, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 5, 'er': 5, 'h': 6, 'hr': 10, 'outs': 81, 'sb': 3},
'R3': {'bb': 4, 'er': 4, 'h': 3, 'hr': 10, 'outs': 0, 'sb': 5}}],
{'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13}),
('normal control 2',
[{'R0': {'bb': 9, 'er': 12, 'h': 18, 'hr': 15, 'outs': 48, 'sb': 8},
'R1': {'bb': 0, 'er': 9, 'h': 0, 'hr': 15, 'outs': 81, 'sb': 3},
'R2': {'bb': 8, 'er': 11, 'h': 11, 'hr': 12, 'outs': 0, 'sb': 3},
'R3': {'bb': 8, 'er': 1, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 3},
'R4': {'bb': 10, 'er': 8, 'h': 24, 'hr': 12, 'outs': 30, 'sb': 5},
'R5': {'bb': 6, 'er': 5, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 8}}],
{'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22}),
('normal control 3',
[{'R0': {'bb': 4, 'er': 7, 'h': 3, 'hr': 10, 'outs': 0, 'sb': 5},
'R1': {'bb': 8, 'er': 2, 'h': 6, 'hr': 15, 'outs': 0, 'sb': 8},
'R2': {'bb': 3, 'er': 12, 'h': 24, 'hr': 10, 'outs': 81, 'sb': 8},
'R3': {'bb': 6, 'er': 0, 'h': 15, 'hr': 12, 'outs': 0, 'sb': 5},
'R4': {'bb': 7, 'er': 12, 'h': 2, 'hr': 12, 'outs': 27, 'sb': 3}}],
{'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26}),
('normal control 4',
[{'R0': {'bb': 0, 'er': 2, 'h': 12, 'hr': 10, 'outs': 54, 'sb': 5},
'R1': {'bb': 5, 'er': 12, 'h': 23, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 3, 'er': 9, 'h': 23, 'hr': 15, 'outs': 0, 'sb': 3},
'R3': {'bb': 3, 'er': 10, 'h': 25, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19})],
[('regression: ratio precision',
[{'R0': {'bb': 8, 'er': 6, 'h': 7, 'hr': 12, 'outs': 90, 'sb': 5},
'R1': {'bb': 6, 'er': 2, 'h': 14, 'hr': 12, 'outs': 81, 'sb': 3},
'R2': {'bb': 9, 'er': 7, 'h': 13, 'hr': 12, 'outs': 81, 'sb': 5},
'R3': {'bb': 5, 'er': 1, 'h': 0, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 21, 'R1': 19, 'R2': 14, 'R3': 26}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 6, 'er': 8, 'h': 14, 'hr': 15, 'outs': 71, 'sb': 5},
'R1': {'bb': 3, 'er': 5, 'h': 24, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 8, 'er': 6, 'h': 9, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 10, 'er': 10, 'h': 16, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 1, 'er': 13, 'h': 24, 'hr': 12, 'outs': 27, 'sb': 5}}],
{'R0': 34, 'R1': 17, 'R2': 29, 'R3': 22, 'R4': 18}),
('second regression',
[{'R0': {'bb': 6, 'er': 5, 'h': 23, 'hr': 12, 'outs': 27, 'sb': 8},
'R1': {'bb': 1, 'er': 6, 'h': 16, 'hr': 15, 'outs': 27, 'sb': 5},
'R2': {'bb': 10, 'er': 7, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 8},
'R3': {'bb': 10, 'er': 1, 'h': 12, 'hr': 15, 'outs': 83, 'sb': 8},
'R4': {'bb': 8, 'er': 10, 'h': 5, 'hr': 10, 'outs': 30, 'sb': 5}}],
{'R0': 23, 'R1': 24, 'R2': 21, 'R3': 37, 'R4': 15}),
('normal control 1',
[{'R0': {'bb': 2, 'er': 13, 'h': 11, 'hr': 12, 'outs': 0, 'sb': 5},
'R1': {'bb': 10, 'er': 7, 'h': 4, 'hr': 12, 'outs': 81, 'sb': 3},
'R2': {'bb': 8, 'er': 3, 'h': 20, 'hr': 10, 'outs': 18, 'sb': 5},
'R3': {'bb': 9, 'er': 0, 'h': 20, 'hr': 10, 'outs': 81, 'sb': 3},
'R4': {'bb': 3, 'er': 14, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 8},
'R5': {'bb': 7, 'er': 0, 'h': 4, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 22, 'R1': 32, 'R2': 22, 'R3': 27, 'R4': 26, 'R5': 39}),
('normal control 2',
[{'R0': {'bb': 5, 'er': 8, 'h': 7, 'hr': 10, 'outs': 36, 'sb': 5},
'R1': {'bb': 1, 'er': 1, 'h': 20, 'hr': 10, 'outs': 54, 'sb': 8},
'R2': {'bb': 5, 'er': 9, 'h': 11, 'hr': 10, 'outs': 0, 'sb': 5},
'R3': {'bb': 9, 'er': 14, 'h': 22, 'hr': 15, 'outs': 21, 'sb': 8}}],
{'R0': 21, 'R1': 25, 'R2': 11, 'R3': 23}),
('normal control 3',
[{'R0': {'bb': 8, 'er': 1, 'h': 8, 'hr': 10, 'outs': 30, 'sb': 8},
'R1': {'bb': 9, 'er': 10, 'h': 12, 'hr': 12, 'outs': 12, 'sb': 5},
'R2': {'bb': 10, 'er': 4, 'h': 3, 'hr': 12, 'outs': 30, 'sb': 3},
'R3': {'bb': 5, 'er': 4, 'h': 14, 'hr': 10, 'outs': 16, 'sb': 5},
'R4': {'bb': 6, 'er': 6, 'h': 22, 'hr': 15, 'outs': 30, 'sb': 8},
'R5': {'bb': 1, 'er': 12, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 34, 'R1': 18, 'R2': 30, 'R3': 17, 'R4': 35, 'R5': 34}),
('normal control 4',
[{'R0': {'bb': 1, 'er': 6, 'h': 24, 'hr': 12, 'outs': 0, 'sb': 8},
'R1': {'bb': 3, 'er': 0, 'h': 4, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 2, 'er': 4, 'h': 22, 'hr': 15, 'outs': 0, 'sb': 3},
'R3': {'bb': 10, 'er': 9, 'h': 0, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 19, 'R1': 21, 'R2': 16, 'R3': 24})],
[('regression: ratio precision',
[{'R0': {'bb': 8, 'er': 7, 'h': 22, 'hr': 12, 'outs': 81, 'sb': 3},
'R1': {'bb': 8, 'er': 6, 'h': 24, 'hr': 12, 'outs': 81, 'sb': 5},
'R2': {'bb': 3, 'er': 11, 'h': 17, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 3, 'er': 9, 'h': 8, 'hr': 12, 'outs': 35, 'sb': 8}}],
{'R0': 18, 'R1': 20, 'R2': 20, 'R3': 22}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 2, 'er': 9, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 8},
'R1': {'bb': 2, 'er': 6, 'h': 1, 'hr': 15, 'outs': 0, 'sb': 5},
'R2': {'bb': 9, 'er': 9, 'h': 4, 'hr': 12, 'outs': 82, 'sb': 5},
'R3': {'bb': 1, 'er': 6, 'h': 10, 'hr': 10, 'outs': 27, 'sb': 3},
'R4': {'bb': 8, 'er': 11, 'h': 6, 'hr': 12, 'outs': 27, 'sb': 8},
'R5': {'bb': 1, 'er': 14, 'h': 16, 'hr': 15, 'outs': 54, 'sb': 8}}],
{'R0': 38, 'R1': 20, 'R2': 33, 'R3': 18, 'R4': 24, 'R5': 35}),
('second regression',
[{'R0': {'bb': 2, 'er': 11, 'h': 11, 'hr': 12, 'outs': 81, 'sb': 8},
'R1': {'bb': 0, 'er': 7, 'h': 2, 'hr': 15, 'outs': 54, 'sb': 3},
'R2': {'bb': 6, 'er': 5, 'h': 9, 'hr': 12, 'outs': 30, 'sb': 5}}],
{'R0': 17, 'R1': 20, 'R2': 11}),
('normal control 1',
[{'R0': {'bb': 1, 'er': 12, 'h': 5, 'hr': 12, 'outs': 4, 'sb': 8},
'R1': {'bb': 10, 'er': 5, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 3},
'R2': {'bb': 7, 'er': 5, 'h': 12, 'hr': 12, 'outs': 0, 'sb': 3},
'R3': {'bb': 9, 'er': 1, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 5},
'R4': {'bb': 8, 'er': 4, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 5},
'R5': {'bb': 6, 'er': 8, 'h': 13, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 34, 'R1': 29, 'R2': 17, 'R3': 38, 'R4': 22, 'R5': 28}),
('normal control 2',
[{'R0': {'bb': 0, 'er': 8, 'h': 20, 'hr': 12, 'outs': 8, 'sb': 5},
'R1': {'bb': 2, 'er': 11, 'h': 15, 'hr': 12, 'outs': 27, 'sb': 5},
'R2': {'bb': 4, 'er': 4, 'h': 3, 'hr': 12, 'outs': 81, 'sb': 3},
'R3': {'bb': 7, 'er': 1, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 3},
'R4': {'bb': 4, 'er': 6, 'h': 3, 'hr': 12, 'outs': 0, 'sb': 8},
'R5': {'bb': 9, 'er': 14, 'h': 18, 'hr': 12, 'outs': 27, 'sb': 3}}],
{'R0': 24, 'R1': 32, 'R2': 33, 'R3': 33, 'R4': 23, 'R5': 23}),
('normal control 3',
[{'R0': {'bb': 4, 'er': 14, 'h': 19, 'hr': 12, 'outs': 30, 'sb': 5},
'R1': {'bb': 3, 'er': 3, 'h': 13, 'hr': 12, 'outs': 27, 'sb': 8},
'R2': {'bb': 0, 'er': 7, 'h': 20, 'hr': 10, 'outs': 33, 'sb': 5},
'R3': {'bb': 5, 'er': 7, 'h': 17, 'hr': 10, 'outs': 27, 'sb': 8},
'R4': {'bb': 7, 'er': 11, 'h': 17, 'hr': 12, 'outs': 20, 'sb': 3}}],
{'R0': 23, 'R1': 37, 'R2': 24, 'R3': 22, 'R4': 14}),
('normal control 4',
[{'R0': {'bb': 9, 'er': 4, 'h': 14, 'hr': 10, 'outs': 0, 'sb': 8},
'R1': {'bb': 2, 'er': 0, 'h': 6, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 6, 'er': 5, 'h': 2, 'hr': 12, 'outs': 30, 'sb': 3},
'R3': {'bb': 4, 'er': 11, 'h': 19, 'hr': 12, 'outs': 81, 'sb': 3}}],
{'R0': 15, 'R1': 21, 'R2': 22, 'R3': 22})],
[('regression: ratio precision',
[{'R0': {'bb': 4, 'er': 2, 'h': 19, 'hr': 15, 'outs': 65, 'sb': 5},
'R1': {'bb': 0, 'er': 12, 'h': 21, 'hr': 10, 'outs': 54, 'sb': 3},
'R2': {'bb': 4, 'er': 2, 'h': 7, 'hr': 15, 'outs': 27, 'sb': 3},
'R3': {'bb': 5, 'er': 5, 'h': 23, 'hr': 15, 'outs': 54, 'sb': 5},
'R4': {'bb': 2, 'er': 9, 'h': 3, 'hr': 12, 'outs': 9, 'sb': 3}}],
{'R0': 37, 'R1': 18, 'R2': 26, 'R3': 27, 'R4': 12}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 1, 'er': 5, 'h': 0, 'hr': 10, 'outs': 81, 'sb': 5},
'R1': {'bb': 4, 'er': 8, 'h': 15, 'hr': 15, 'outs': 0, 'sb': 3},
'R2': {'bb': 6, 'er': 1, 'h': 13, 'hr': 12, 'outs': 27, 'sb': 5},
'R3': {'bb': 1, 'er': 8, 'h': 7, 'hr': 12, 'outs': 54, 'sb': 5},
'R4': {'bb': 6, 'er': 7, 'h': 4, 'hr': 12, 'outs': 40, 'sb': 3},
'R5': {'bb': 6, 'er': 14, 'h': 1, 'hr': 12, 'outs': 81, 'sb': 8}}],
{'R0': 32, 'R1': 19, 'R2': 31, 'R3': 31, 'R4': 20, 'R5': 35}),
('second regression',
[{'R0': {'bb': 0, 'er': 1, 'h': 0, 'hr': 12, 'outs': 27, 'sb': 5},
'R1': {'bb': 9, 'er': 5, 'h': 25, 'hr': 15, 'outs': 81, 'sb': 5},
'R2': {'bb': 1, 'er': 12, 'h': 23, 'hr': 15, 'outs': 0, 'sb': 8}}],
{'R0': 17, 'R1': 16, 'R2': 15}),
('normal control 1',
[{'R0': {'bb': 9, 'er': 14, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 3},
'R1': {'bb': 10, 'er': 7, 'h': 19, 'hr': 12, 'outs': 0, 'sb': 5},
'R2': {'bb': 9, 'er': 14, 'h': 1, 'hr': 12, 'outs': 54, 'sb': 5}}],
{'R0': 14, 'R1': 13, 'R2': 21}),
('normal control 2',
[{'R0': {'bb': 8, 'er': 3, 'h': 21, 'hr': 12, 'outs': 81, 'sb': 5},
'R1': {'bb': 3, 'er': 11, 'h': 25, 'hr': 10, 'outs': 50, 'sb': 5},
'R2': {'bb': 7, 'er': 0, 'h': 12, 'hr': 12, 'outs': 54, 'sb': 5},
'R3': {'bb': 2, 'er': 4, 'h': 24, 'hr': 12, 'outs': 0, 'sb': 3},
'R4': {'bb': 4, 'er': 14, 'h': 16, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 29, 'R1': 21, 'R2': 33, 'R3': 14, 'R4': 23}),
('normal control 3',
[{'R0': {'bb': 0, 'er': 1, 'h': 13, 'hr': 15, 'outs': 55, 'sb': 5},
'R1': {'bb': 10, 'er': 1, 'h': 16, 'hr': 10, 'outs': 27, 'sb': 3},
'R2': {'bb': 3, 'er': 5, 'h': 5, 'hr': 10, 'outs': 54, 'sb': 8},
'R3': {'bb': 2, 'er': 7, 'h': 18, 'hr': 12, 'outs': 27, 'sb': 5}}],
{'R0': 27, 'R1': 13, 'R2': 23, 'R3': 17}),
('normal control 4',
[{'R0': {'bb': 8, 'er': 11, 'h': 20, 'hr': 15, 'outs': 30, 'sb': 8},
'R1': {'bb': 5, 'er': 3, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 7, 'er': 13, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 5}}],
{'R0': 20, 'R1': 18, 'R2': 10})],
[('regression: ratio precision',
[{'R0': {'bb': 9, 'er': 5, 'h': 21, 'hr': 10, 'outs': 81, 'sb': 8},
'R1': {'bb': 6, 'er': 7, 'h': 15, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 6, 'er': 6, 'h': 25, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 3, 'er': 4, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 6, 'er': 6, 'h': 17, 'hr': 15, 'outs': 30, 'sb': 8}}],
{'R0': 31, 'R1': 16, 'R2': 25, 'R3': 24, 'R4': 24}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 2, 'er': 14, 'h': 3, 'hr': 15, 'outs': 86, 'sb': 5},
'R1': {'bb': 1, 'er': 6, 'h': 5, 'hr': 12, 'outs': 54, 'sb': 5},
'R2': {'bb': 8, 'er': 9, 'h': 8, 'hr': 15, 'outs': 82, 'sb': 5},
'R3': {'bb': 7, 'er': 1, 'h': 9, 'hr': 12, 'outs': 81, 'sb': 5},
'R4': {'bb': 7, 'er': 14, 'h': 20, 'hr': 12, 'outs': 18, 'sb': 5}}],
{'R0': 29, 'R1': 24, 'R2': 29, 'R3': 24, 'R4': 14}),
('second regression',
[{'R0': {'bb': 0, 'er': 12, 'h': 12, 'hr': 12, 'outs': 30, 'sb': 5},
'R1': {'bb': 5, 'er': 14, 'h': 15, 'hr': 12, 'outs': 32, 'sb': 5},
'R2': {'bb': 10, 'er': 0, 'h': 7, 'hr': 10, 'outs': 30, 'sb': 5},
'R3': {'bb': 9, 'er': 1, 'h': 21, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 8, 'er': 7, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 5},
'R5': {'bb': 1, 'er': 1, 'h': 9, 'hr': 10, 'outs': 81, 'sb': 3}}],
{'R0': 29, 'R1': 23, 'R2': 29, 'R3': 27, 'R4': 33, 'R5': 27}),
('normal control 1',
[{'R0': {'bb': 10, 'er': 6, 'h': 21, 'hr': 10, 'outs': 0, 'sb': 3},
'R1': {'bb': 5, 'er': 10, 'h': 16, 'hr': 15, 'outs': 54, 'sb': 5},
'R2': {'bb': 3, 'er': 9, 'h': 24, 'hr': 15, 'outs': 27, 'sb': 3}}],
{'R0': 9, 'R1': 23, 'R2': 16}),
('normal control 2',
[{'R0': {'bb': 8, 'er': 14, 'h': 6, 'hr': 15, 'outs': 27, 'sb': 5},
'R1': {'bb': 9, 'er': 8, 'h': 20, 'hr': 15, 'outs': 0, 'sb': 8},
'R2': {'bb': 1, 'er': 10, 'h': 1, 'hr': 12, 'outs': 78, 'sb': 3}}],
{'R0': 17, 'R1': 15, 'R2': 16}),
('normal control 3',
[{'R0': {'bb': 2, 'er': 13, 'h': 0, 'hr': 15, 'outs': 81, 'sb': 8},
'R1': {'bb': 2, 'er': 0, 'h': 12, 'hr': 12, 'outs': 16, 'sb': 3},
'R2': {'bb': 2, 'er': 3, 'h': 8, 'hr': 12, 'outs': 0, 'sb': 5}}],
{'R0': 22, 'R1': 15, 'R2': 11}),
('normal control 4',
[{'R0': {'bb': 7, 'er': 2, 'h': 22, 'hr': 12, 'outs': 0, 'sb': 5},
'R1': {'bb': 9, 'er': 11, 'h': 25, 'hr': 10, 'outs': 30, 'sb': 5},
'R2': {'bb': 2, 'er': 5, 'h': 0, 'hr': 10, 'outs': 81, 'sb': 3},
'R3': {'bb': 7, 'er': 3, 'h': 13, 'hr': 12, 'outs': 30, 'sb': 3},
'R4': {'bb': 2, 'er': 14, 'h': 5, 'hr': 15, 'outs': 10, 'sb': 3},
'R5': {'bb': 4, 'er': 8, 'h': 0, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 21, 'R1': 22, 'R2': 31, 'R3': 30, 'R4': 26, 'R5': 38})]]
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: ratio precision | {'R0': 16, 'R1': 17, 'R2': 31, 'R3': 16} | {'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17} | Failed |
| partial repair probe: ratio precision | {'R0': 25, 'R1': 32, 'R2': 26, 'R3': 15, 'R4': 22} | {'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22} | Failed |
| second regression | {'R0': 33, 'R1': 34, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16} | {'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16} | Failed |
| normal control 1 | {'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13} | {'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13} | Passed |
| normal control 2 | {'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22} | {'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22} | Passed |
| normal control 3 | {'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26} | {'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26} | Passed |
| normal control 4 | {'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19} | {'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19} | Passed |
SHA-256 / ede4aa265034881841da432d05719697955bf212b9ac6ca0c38217c08952a2f4
2 / The unsuccessful fix
Exit 1"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(teams):
names = sorted(teams)
n = len(names)
def value(t, cat):
d = teams[t]
if cat in ('hr', 'sb'):
return Fraction(d[cat])
if d['outs'] == 0:
return None
if cat == 'era':
return Fraction(round(d['er'] * 27 / d['outs'], 1))
return Fraction((d['bb'] + d['h']) * 3, d['outs'])
total = {t: 0 for t in names}
for cat in ('hr', 'sb', 'era', 'whip'):
low = cat in ('era', 'whip')
def key(t):
v = value(t, cat)
if v is None:
return (1, 0)
return (0, v if low else -v)
ranked = sorted(names, key=key)
i = 0
while i < n:
j = i
while j < n and key(ranked[j]) == key(ranked[i]):
j += 1
pts2 = sum(2 * (n - r) for r in range(i, j)) // (j - i)
for t in ranked[i:j]:
total[t] += pts2
i = j
return total
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: ratio precision',
[{'R0': {'bb': 9, 'er': 11, 'h': 21, 'hr': 15, 'outs': 60, 'sb': 5},
'R1': {'bb': 5, 'er': 3, 'h': 1, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 6, 'er': 2, 'h': 1, 'hr': 15, 'outs': 81, 'sb': 8},
'R3': {'bb': 3, 'er': 13, 'h': 9, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 1, 'er': 8, 'h': 16, 'hr': 12, 'outs': 63, 'sb': 3},
'R1': {'bb': 8, 'er': 3, 'h': 3, 'hr': 15, 'outs': 73, 'sb': 3},
'R2': {'bb': 3, 'er': 2, 'h': 12, 'hr': 10, 'outs': 48, 'sb': 5},
'R3': {'bb': 6, 'er': 8, 'h': 16, 'hr': 10, 'outs': 0, 'sb': 5},
'R4': {'bb': 10, 'er': 7, 'h': 18, 'hr': 10, 'outs': 30, 'sb': 8}}],
{'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22}),
('second regression',
[{'R0': {'bb': 6, 'er': 11, 'h': 3, 'hr': 10, 'outs': 54, 'sb': 8},
'R1': {'bb': 6, 'er': 10, 'h': 10, 'hr': 12, 'outs': 54, 'sb': 5},
'R2': {'bb': 3, 'er': 14, 'h': 23, 'hr': 12, 'outs': 81, 'sb': 5},
'R3': {'bb': 6, 'er': 5, 'h': 2, 'hr': 12, 'outs': 54, 'sb': 3},
'R4': {'bb': 10, 'er': 8, 'h': 19, 'hr': 10, 'outs': 27, 'sb': 3},
'R5': {'bb': 2, 'er': 12, 'h': 15, 'hr': 10, 'outs': 49, 'sb': 3}}],
{'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16}),
('normal control 1',
[{'R0': {'bb': 2, 'er': 13, 'h': 9, 'hr': 15, 'outs': 30, 'sb': 8},
'R1': {'bb': 4, 'er': 0, 'h': 21, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 5, 'er': 5, 'h': 6, 'hr': 10, 'outs': 81, 'sb': 3},
'R3': {'bb': 4, 'er': 4, 'h': 3, 'hr': 10, 'outs': 0, 'sb': 5}}],
{'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13}),
('normal control 2',
[{'R0': {'bb': 9, 'er': 12, 'h': 18, 'hr': 15, 'outs': 48, 'sb': 8},
'R1': {'bb': 0, 'er': 9, 'h': 0, 'hr': 15, 'outs': 81, 'sb': 3},
'R2': {'bb': 8, 'er': 11, 'h': 11, 'hr': 12, 'outs': 0, 'sb': 3},
'R3': {'bb': 8, 'er': 1, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 3},
'R4': {'bb': 10, 'er': 8, 'h': 24, 'hr': 12, 'outs': 30, 'sb': 5},
'R5': {'bb': 6, 'er': 5, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 8}}],
{'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22}),
('normal control 3',
[{'R0': {'bb': 4, 'er': 7, 'h': 3, 'hr': 10, 'outs': 0, 'sb': 5},
'R1': {'bb': 8, 'er': 2, 'h': 6, 'hr': 15, 'outs': 0, 'sb': 8},
'R2': {'bb': 3, 'er': 12, 'h': 24, 'hr': 10, 'outs': 81, 'sb': 8},
'R3': {'bb': 6, 'er': 0, 'h': 15, 'hr': 12, 'outs': 0, 'sb': 5},
'R4': {'bb': 7, 'er': 12, 'h': 2, 'hr': 12, 'outs': 27, 'sb': 3}}],
{'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26}),
('normal control 4',
[{'R0': {'bb': 0, 'er': 2, 'h': 12, 'hr': 10, 'outs': 54, 'sb': 5},
'R1': {'bb': 5, 'er': 12, 'h': 23, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 3, 'er': 9, 'h': 23, 'hr': 15, 'outs': 0, 'sb': 3},
'R3': {'bb': 3, 'er': 10, 'h': 25, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19})],
[('regression: ratio precision',
[{'R0': {'bb': 8, 'er': 6, 'h': 7, 'hr': 12, 'outs': 90, 'sb': 5},
'R1': {'bb': 6, 'er': 2, 'h': 14, 'hr': 12, 'outs': 81, 'sb': 3},
'R2': {'bb': 9, 'er': 7, 'h': 13, 'hr': 12, 'outs': 81, 'sb': 5},
'R3': {'bb': 5, 'er': 1, 'h': 0, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 21, 'R1': 19, 'R2': 14, 'R3': 26}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 6, 'er': 8, 'h': 14, 'hr': 15, 'outs': 71, 'sb': 5},
'R1': {'bb': 3, 'er': 5, 'h': 24, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 8, 'er': 6, 'h': 9, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 10, 'er': 10, 'h': 16, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 1, 'er': 13, 'h': 24, 'hr': 12, 'outs': 27, 'sb': 5}}],
{'R0': 34, 'R1': 17, 'R2': 29, 'R3': 22, 'R4': 18}),
('second regression',
[{'R0': {'bb': 6, 'er': 5, 'h': 23, 'hr': 12, 'outs': 27, 'sb': 8},
'R1': {'bb': 1, 'er': 6, 'h': 16, 'hr': 15, 'outs': 27, 'sb': 5},
'R2': {'bb': 10, 'er': 7, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 8},
'R3': {'bb': 10, 'er': 1, 'h': 12, 'hr': 15, 'outs': 83, 'sb': 8},
'R4': {'bb': 8, 'er': 10, 'h': 5, 'hr': 10, 'outs': 30, 'sb': 5}}],
{'R0': 23, 'R1': 24, 'R2': 21, 'R3': 37, 'R4': 15}),
('normal control 1',
[{'R0': {'bb': 2, 'er': 13, 'h': 11, 'hr': 12, 'outs': 0, 'sb': 5},
'R1': {'bb': 10, 'er': 7, 'h': 4, 'hr': 12, 'outs': 81, 'sb': 3},
'R2': {'bb': 8, 'er': 3, 'h': 20, 'hr': 10, 'outs': 18, 'sb': 5},
'R3': {'bb': 9, 'er': 0, 'h': 20, 'hr': 10, 'outs': 81, 'sb': 3},
'R4': {'bb': 3, 'er': 14, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 8},
'R5': {'bb': 7, 'er': 0, 'h': 4, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 22, 'R1': 32, 'R2': 22, 'R3': 27, 'R4': 26, 'R5': 39}),
('normal control 2',
[{'R0': {'bb': 5, 'er': 8, 'h': 7, 'hr': 10, 'outs': 36, 'sb': 5},
'R1': {'bb': 1, 'er': 1, 'h': 20, 'hr': 10, 'outs': 54, 'sb': 8},
'R2': {'bb': 5, 'er': 9, 'h': 11, 'hr': 10, 'outs': 0, 'sb': 5},
'R3': {'bb': 9, 'er': 14, 'h': 22, 'hr': 15, 'outs': 21, 'sb': 8}}],
{'R0': 21, 'R1': 25, 'R2': 11, 'R3': 23}),
('normal control 3',
[{'R0': {'bb': 8, 'er': 1, 'h': 8, 'hr': 10, 'outs': 30, 'sb': 8},
'R1': {'bb': 9, 'er': 10, 'h': 12, 'hr': 12, 'outs': 12, 'sb': 5},
'R2': {'bb': 10, 'er': 4, 'h': 3, 'hr': 12, 'outs': 30, 'sb': 3},
'R3': {'bb': 5, 'er': 4, 'h': 14, 'hr': 10, 'outs': 16, 'sb': 5},
'R4': {'bb': 6, 'er': 6, 'h': 22, 'hr': 15, 'outs': 30, 'sb': 8},
'R5': {'bb': 1, 'er': 12, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 34, 'R1': 18, 'R2': 30, 'R3': 17, 'R4': 35, 'R5': 34}),
('normal control 4',
[{'R0': {'bb': 1, 'er': 6, 'h': 24, 'hr': 12, 'outs': 0, 'sb': 8},
'R1': {'bb': 3, 'er': 0, 'h': 4, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 2, 'er': 4, 'h': 22, 'hr': 15, 'outs': 0, 'sb': 3},
'R3': {'bb': 10, 'er': 9, 'h': 0, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 19, 'R1': 21, 'R2': 16, 'R3': 24})],
[('regression: ratio precision',
[{'R0': {'bb': 8, 'er': 7, 'h': 22, 'hr': 12, 'outs': 81, 'sb': 3},
'R1': {'bb': 8, 'er': 6, 'h': 24, 'hr': 12, 'outs': 81, 'sb': 5},
'R2': {'bb': 3, 'er': 11, 'h': 17, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 3, 'er': 9, 'h': 8, 'hr': 12, 'outs': 35, 'sb': 8}}],
{'R0': 18, 'R1': 20, 'R2': 20, 'R3': 22}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 2, 'er': 9, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 8},
'R1': {'bb': 2, 'er': 6, 'h': 1, 'hr': 15, 'outs': 0, 'sb': 5},
'R2': {'bb': 9, 'er': 9, 'h': 4, 'hr': 12, 'outs': 82, 'sb': 5},
'R3': {'bb': 1, 'er': 6, 'h': 10, 'hr': 10, 'outs': 27, 'sb': 3},
'R4': {'bb': 8, 'er': 11, 'h': 6, 'hr': 12, 'outs': 27, 'sb': 8},
'R5': {'bb': 1, 'er': 14, 'h': 16, 'hr': 15, 'outs': 54, 'sb': 8}}],
{'R0': 38, 'R1': 20, 'R2': 33, 'R3': 18, 'R4': 24, 'R5': 35}),
('second regression',
[{'R0': {'bb': 2, 'er': 11, 'h': 11, 'hr': 12, 'outs': 81, 'sb': 8},
'R1': {'bb': 0, 'er': 7, 'h': 2, 'hr': 15, 'outs': 54, 'sb': 3},
'R2': {'bb': 6, 'er': 5, 'h': 9, 'hr': 12, 'outs': 30, 'sb': 5}}],
{'R0': 17, 'R1': 20, 'R2': 11}),
('normal control 1',
[{'R0': {'bb': 1, 'er': 12, 'h': 5, 'hr': 12, 'outs': 4, 'sb': 8},
'R1': {'bb': 10, 'er': 5, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 3},
'R2': {'bb': 7, 'er': 5, 'h': 12, 'hr': 12, 'outs': 0, 'sb': 3},
'R3': {'bb': 9, 'er': 1, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 5},
'R4': {'bb': 8, 'er': 4, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 5},
'R5': {'bb': 6, 'er': 8, 'h': 13, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 34, 'R1': 29, 'R2': 17, 'R3': 38, 'R4': 22, 'R5': 28}),
('normal control 2',
[{'R0': {'bb': 0, 'er': 8, 'h': 20, 'hr': 12, 'outs': 8, 'sb': 5},
'R1': {'bb': 2, 'er': 11, 'h': 15, 'hr': 12, 'outs': 27, 'sb': 5},
'R2': {'bb': 4, 'er': 4, 'h': 3, 'hr': 12, 'outs': 81, 'sb': 3},
'R3': {'bb': 7, 'er': 1, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 3},
'R4': {'bb': 4, 'er': 6, 'h': 3, 'hr': 12, 'outs': 0, 'sb': 8},
'R5': {'bb': 9, 'er': 14, 'h': 18, 'hr': 12, 'outs': 27, 'sb': 3}}],
{'R0': 24, 'R1': 32, 'R2': 33, 'R3': 33, 'R4': 23, 'R5': 23}),
('normal control 3',
[{'R0': {'bb': 4, 'er': 14, 'h': 19, 'hr': 12, 'outs': 30, 'sb': 5},
'R1': {'bb': 3, 'er': 3, 'h': 13, 'hr': 12, 'outs': 27, 'sb': 8},
'R2': {'bb': 0, 'er': 7, 'h': 20, 'hr': 10, 'outs': 33, 'sb': 5},
'R3': {'bb': 5, 'er': 7, 'h': 17, 'hr': 10, 'outs': 27, 'sb': 8},
'R4': {'bb': 7, 'er': 11, 'h': 17, 'hr': 12, 'outs': 20, 'sb': 3}}],
{'R0': 23, 'R1': 37, 'R2': 24, 'R3': 22, 'R4': 14}),
('normal control 4',
[{'R0': {'bb': 9, 'er': 4, 'h': 14, 'hr': 10, 'outs': 0, 'sb': 8},
'R1': {'bb': 2, 'er': 0, 'h': 6, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 6, 'er': 5, 'h': 2, 'hr': 12, 'outs': 30, 'sb': 3},
'R3': {'bb': 4, 'er': 11, 'h': 19, 'hr': 12, 'outs': 81, 'sb': 3}}],
{'R0': 15, 'R1': 21, 'R2': 22, 'R3': 22})],
[('regression: ratio precision',
[{'R0': {'bb': 4, 'er': 2, 'h': 19, 'hr': 15, 'outs': 65, 'sb': 5},
'R1': {'bb': 0, 'er': 12, 'h': 21, 'hr': 10, 'outs': 54, 'sb': 3},
'R2': {'bb': 4, 'er': 2, 'h': 7, 'hr': 15, 'outs': 27, 'sb': 3},
'R3': {'bb': 5, 'er': 5, 'h': 23, 'hr': 15, 'outs': 54, 'sb': 5},
'R4': {'bb': 2, 'er': 9, 'h': 3, 'hr': 12, 'outs': 9, 'sb': 3}}],
{'R0': 37, 'R1': 18, 'R2': 26, 'R3': 27, 'R4': 12}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 1, 'er': 5, 'h': 0, 'hr': 10, 'outs': 81, 'sb': 5},
'R1': {'bb': 4, 'er': 8, 'h': 15, 'hr': 15, 'outs': 0, 'sb': 3},
'R2': {'bb': 6, 'er': 1, 'h': 13, 'hr': 12, 'outs': 27, 'sb': 5},
'R3': {'bb': 1, 'er': 8, 'h': 7, 'hr': 12, 'outs': 54, 'sb': 5},
'R4': {'bb': 6, 'er': 7, 'h': 4, 'hr': 12, 'outs': 40, 'sb': 3},
'R5': {'bb': 6, 'er': 14, 'h': 1, 'hr': 12, 'outs': 81, 'sb': 8}}],
{'R0': 32, 'R1': 19, 'R2': 31, 'R3': 31, 'R4': 20, 'R5': 35}),
('second regression',
[{'R0': {'bb': 0, 'er': 1, 'h': 0, 'hr': 12, 'outs': 27, 'sb': 5},
'R1': {'bb': 9, 'er': 5, 'h': 25, 'hr': 15, 'outs': 81, 'sb': 5},
'R2': {'bb': 1, 'er': 12, 'h': 23, 'hr': 15, 'outs': 0, 'sb': 8}}],
{'R0': 17, 'R1': 16, 'R2': 15}),
('normal control 1',
[{'R0': {'bb': 9, 'er': 14, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 3},
'R1': {'bb': 10, 'er': 7, 'h': 19, 'hr': 12, 'outs': 0, 'sb': 5},
'R2': {'bb': 9, 'er': 14, 'h': 1, 'hr': 12, 'outs': 54, 'sb': 5}}],
{'R0': 14, 'R1': 13, 'R2': 21}),
('normal control 2',
[{'R0': {'bb': 8, 'er': 3, 'h': 21, 'hr': 12, 'outs': 81, 'sb': 5},
'R1': {'bb': 3, 'er': 11, 'h': 25, 'hr': 10, 'outs': 50, 'sb': 5},
'R2': {'bb': 7, 'er': 0, 'h': 12, 'hr': 12, 'outs': 54, 'sb': 5},
'R3': {'bb': 2, 'er': 4, 'h': 24, 'hr': 12, 'outs': 0, 'sb': 3},
'R4': {'bb': 4, 'er': 14, 'h': 16, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 29, 'R1': 21, 'R2': 33, 'R3': 14, 'R4': 23}),
('normal control 3',
[{'R0': {'bb': 0, 'er': 1, 'h': 13, 'hr': 15, 'outs': 55, 'sb': 5},
'R1': {'bb': 10, 'er': 1, 'h': 16, 'hr': 10, 'outs': 27, 'sb': 3},
'R2': {'bb': 3, 'er': 5, 'h': 5, 'hr': 10, 'outs': 54, 'sb': 8},
'R3': {'bb': 2, 'er': 7, 'h': 18, 'hr': 12, 'outs': 27, 'sb': 5}}],
{'R0': 27, 'R1': 13, 'R2': 23, 'R3': 17}),
('normal control 4',
[{'R0': {'bb': 8, 'er': 11, 'h': 20, 'hr': 15, 'outs': 30, 'sb': 8},
'R1': {'bb': 5, 'er': 3, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 7, 'er': 13, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 5}}],
{'R0': 20, 'R1': 18, 'R2': 10})],
[('regression: ratio precision',
[{'R0': {'bb': 9, 'er': 5, 'h': 21, 'hr': 10, 'outs': 81, 'sb': 8},
'R1': {'bb': 6, 'er': 7, 'h': 15, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 6, 'er': 6, 'h': 25, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 3, 'er': 4, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 6, 'er': 6, 'h': 17, 'hr': 15, 'outs': 30, 'sb': 8}}],
{'R0': 31, 'R1': 16, 'R2': 25, 'R3': 24, 'R4': 24}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 2, 'er': 14, 'h': 3, 'hr': 15, 'outs': 86, 'sb': 5},
'R1': {'bb': 1, 'er': 6, 'h': 5, 'hr': 12, 'outs': 54, 'sb': 5},
'R2': {'bb': 8, 'er': 9, 'h': 8, 'hr': 15, 'outs': 82, 'sb': 5},
'R3': {'bb': 7, 'er': 1, 'h': 9, 'hr': 12, 'outs': 81, 'sb': 5},
'R4': {'bb': 7, 'er': 14, 'h': 20, 'hr': 12, 'outs': 18, 'sb': 5}}],
{'R0': 29, 'R1': 24, 'R2': 29, 'R3': 24, 'R4': 14}),
('second regression',
[{'R0': {'bb': 0, 'er': 12, 'h': 12, 'hr': 12, 'outs': 30, 'sb': 5},
'R1': {'bb': 5, 'er': 14, 'h': 15, 'hr': 12, 'outs': 32, 'sb': 5},
'R2': {'bb': 10, 'er': 0, 'h': 7, 'hr': 10, 'outs': 30, 'sb': 5},
'R3': {'bb': 9, 'er': 1, 'h': 21, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 8, 'er': 7, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 5},
'R5': {'bb': 1, 'er': 1, 'h': 9, 'hr': 10, 'outs': 81, 'sb': 3}}],
{'R0': 29, 'R1': 23, 'R2': 29, 'R3': 27, 'R4': 33, 'R5': 27}),
('normal control 1',
[{'R0': {'bb': 10, 'er': 6, 'h': 21, 'hr': 10, 'outs': 0, 'sb': 3},
'R1': {'bb': 5, 'er': 10, 'h': 16, 'hr': 15, 'outs': 54, 'sb': 5},
'R2': {'bb': 3, 'er': 9, 'h': 24, 'hr': 15, 'outs': 27, 'sb': 3}}],
{'R0': 9, 'R1': 23, 'R2': 16}),
('normal control 2',
[{'R0': {'bb': 8, 'er': 14, 'h': 6, 'hr': 15, 'outs': 27, 'sb': 5},
'R1': {'bb': 9, 'er': 8, 'h': 20, 'hr': 15, 'outs': 0, 'sb': 8},
'R2': {'bb': 1, 'er': 10, 'h': 1, 'hr': 12, 'outs': 78, 'sb': 3}}],
{'R0': 17, 'R1': 15, 'R2': 16}),
('normal control 3',
[{'R0': {'bb': 2, 'er': 13, 'h': 0, 'hr': 15, 'outs': 81, 'sb': 8},
'R1': {'bb': 2, 'er': 0, 'h': 12, 'hr': 12, 'outs': 16, 'sb': 3},
'R2': {'bb': 2, 'er': 3, 'h': 8, 'hr': 12, 'outs': 0, 'sb': 5}}],
{'R0': 22, 'R1': 15, 'R2': 11}),
('normal control 4',
[{'R0': {'bb': 7, 'er': 2, 'h': 22, 'hr': 12, 'outs': 0, 'sb': 5},
'R1': {'bb': 9, 'er': 11, 'h': 25, 'hr': 10, 'outs': 30, 'sb': 5},
'R2': {'bb': 2, 'er': 5, 'h': 0, 'hr': 10, 'outs': 81, 'sb': 3},
'R3': {'bb': 7, 'er': 3, 'h': 13, 'hr': 12, 'outs': 30, 'sb': 3},
'R4': {'bb': 2, 'er': 14, 'h': 5, 'hr': 15, 'outs': 10, 'sb': 3},
'R5': {'bb': 4, 'er': 8, 'h': 0, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 21, 'R1': 22, 'R2': 31, 'R3': 30, 'R4': 26, 'R5': 38})]]
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: ratio precision | {'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17} | {'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17} | Passed |
| partial repair probe: ratio precision | {'R0': 25, 'R1': 32, 'R2': 26, 'R3': 15, 'R4': 22} | {'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22} | Failed |
| second regression | {'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16} | {'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16} | Passed |
| normal control 1 | {'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13} | {'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13} | Passed |
| normal control 2 | {'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22} | {'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22} | Passed |
| normal control 3 | {'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26} | {'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26} | Passed |
| normal control 4 | {'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19} | {'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19} | Passed |
SHA-256 / 5acfdf6917d4767f584f29e784096fa61529fdd20c96a81263040435ab9947fe
3 / The verified repair
Exit 0"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
N = 1
observations = []
def solve(teams):
names = sorted(teams)
n = len(names)
def value(t, cat):
d = teams[t]
if cat in ('hr', 'sb'):
return Fraction(d[cat])
if d['outs'] == 0:
return None
if cat == 'era':
return Fraction(d['er'] * 27, d['outs'])
return Fraction((d['bb'] + d['h']) * 3, d['outs'])
total = {t: 0 for t in names}
for cat in ('hr', 'sb', 'era', 'whip'):
low = cat in ('era', 'whip')
def key(t):
v = value(t, cat)
if v is None:
return (1, 0)
return (0, v if low else -v)
ranked = sorted(names, key=key)
i = 0
while i < n:
j = i
while j < n and key(ranked[j]) == key(ranked[i]):
j += 1
pts2 = sum(2 * (n - r) for r in range(i, j)) // (j - i)
for t in ranked[i:j]:
total[t] += pts2
i = j
return total
def check(label, actual, expected):
observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: ratio precision',
[{'R0': {'bb': 9, 'er': 11, 'h': 21, 'hr': 15, 'outs': 60, 'sb': 5},
'R1': {'bb': 5, 'er': 3, 'h': 1, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 6, 'er': 2, 'h': 1, 'hr': 15, 'outs': 81, 'sb': 8},
'R3': {'bb': 3, 'er': 13, 'h': 9, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 1, 'er': 8, 'h': 16, 'hr': 12, 'outs': 63, 'sb': 3},
'R1': {'bb': 8, 'er': 3, 'h': 3, 'hr': 15, 'outs': 73, 'sb': 3},
'R2': {'bb': 3, 'er': 2, 'h': 12, 'hr': 10, 'outs': 48, 'sb': 5},
'R3': {'bb': 6, 'er': 8, 'h': 16, 'hr': 10, 'outs': 0, 'sb': 5},
'R4': {'bb': 10, 'er': 7, 'h': 18, 'hr': 10, 'outs': 30, 'sb': 8}}],
{'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22}),
('second regression',
[{'R0': {'bb': 6, 'er': 11, 'h': 3, 'hr': 10, 'outs': 54, 'sb': 8},
'R1': {'bb': 6, 'er': 10, 'h': 10, 'hr': 12, 'outs': 54, 'sb': 5},
'R2': {'bb': 3, 'er': 14, 'h': 23, 'hr': 12, 'outs': 81, 'sb': 5},
'R3': {'bb': 6, 'er': 5, 'h': 2, 'hr': 12, 'outs': 54, 'sb': 3},
'R4': {'bb': 10, 'er': 8, 'h': 19, 'hr': 10, 'outs': 27, 'sb': 3},
'R5': {'bb': 2, 'er': 12, 'h': 15, 'hr': 10, 'outs': 49, 'sb': 3}}],
{'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16}),
('normal control 1',
[{'R0': {'bb': 2, 'er': 13, 'h': 9, 'hr': 15, 'outs': 30, 'sb': 8},
'R1': {'bb': 4, 'er': 0, 'h': 21, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 5, 'er': 5, 'h': 6, 'hr': 10, 'outs': 81, 'sb': 3},
'R3': {'bb': 4, 'er': 4, 'h': 3, 'hr': 10, 'outs': 0, 'sb': 5}}],
{'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13}),
('normal control 2',
[{'R0': {'bb': 9, 'er': 12, 'h': 18, 'hr': 15, 'outs': 48, 'sb': 8},
'R1': {'bb': 0, 'er': 9, 'h': 0, 'hr': 15, 'outs': 81, 'sb': 3},
'R2': {'bb': 8, 'er': 11, 'h': 11, 'hr': 12, 'outs': 0, 'sb': 3},
'R3': {'bb': 8, 'er': 1, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 3},
'R4': {'bb': 10, 'er': 8, 'h': 24, 'hr': 12, 'outs': 30, 'sb': 5},
'R5': {'bb': 6, 'er': 5, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 8}}],
{'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22}),
('normal control 3',
[{'R0': {'bb': 4, 'er': 7, 'h': 3, 'hr': 10, 'outs': 0, 'sb': 5},
'R1': {'bb': 8, 'er': 2, 'h': 6, 'hr': 15, 'outs': 0, 'sb': 8},
'R2': {'bb': 3, 'er': 12, 'h': 24, 'hr': 10, 'outs': 81, 'sb': 8},
'R3': {'bb': 6, 'er': 0, 'h': 15, 'hr': 12, 'outs': 0, 'sb': 5},
'R4': {'bb': 7, 'er': 12, 'h': 2, 'hr': 12, 'outs': 27, 'sb': 3}}],
{'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26}),
('normal control 4',
[{'R0': {'bb': 0, 'er': 2, 'h': 12, 'hr': 10, 'outs': 54, 'sb': 5},
'R1': {'bb': 5, 'er': 12, 'h': 23, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 3, 'er': 9, 'h': 23, 'hr': 15, 'outs': 0, 'sb': 3},
'R3': {'bb': 3, 'er': 10, 'h': 25, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19})],
[('regression: ratio precision',
[{'R0': {'bb': 8, 'er': 6, 'h': 7, 'hr': 12, 'outs': 90, 'sb': 5},
'R1': {'bb': 6, 'er': 2, 'h': 14, 'hr': 12, 'outs': 81, 'sb': 3},
'R2': {'bb': 9, 'er': 7, 'h': 13, 'hr': 12, 'outs': 81, 'sb': 5},
'R3': {'bb': 5, 'er': 1, 'h': 0, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 21, 'R1': 19, 'R2': 14, 'R3': 26}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 6, 'er': 8, 'h': 14, 'hr': 15, 'outs': 71, 'sb': 5},
'R1': {'bb': 3, 'er': 5, 'h': 24, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 8, 'er': 6, 'h': 9, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 10, 'er': 10, 'h': 16, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 1, 'er': 13, 'h': 24, 'hr': 12, 'outs': 27, 'sb': 5}}],
{'R0': 34, 'R1': 17, 'R2': 29, 'R3': 22, 'R4': 18}),
('second regression',
[{'R0': {'bb': 6, 'er': 5, 'h': 23, 'hr': 12, 'outs': 27, 'sb': 8},
'R1': {'bb': 1, 'er': 6, 'h': 16, 'hr': 15, 'outs': 27, 'sb': 5},
'R2': {'bb': 10, 'er': 7, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 8},
'R3': {'bb': 10, 'er': 1, 'h': 12, 'hr': 15, 'outs': 83, 'sb': 8},
'R4': {'bb': 8, 'er': 10, 'h': 5, 'hr': 10, 'outs': 30, 'sb': 5}}],
{'R0': 23, 'R1': 24, 'R2': 21, 'R3': 37, 'R4': 15}),
('normal control 1',
[{'R0': {'bb': 2, 'er': 13, 'h': 11, 'hr': 12, 'outs': 0, 'sb': 5},
'R1': {'bb': 10, 'er': 7, 'h': 4, 'hr': 12, 'outs': 81, 'sb': 3},
'R2': {'bb': 8, 'er': 3, 'h': 20, 'hr': 10, 'outs': 18, 'sb': 5},
'R3': {'bb': 9, 'er': 0, 'h': 20, 'hr': 10, 'outs': 81, 'sb': 3},
'R4': {'bb': 3, 'er': 14, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 8},
'R5': {'bb': 7, 'er': 0, 'h': 4, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 22, 'R1': 32, 'R2': 22, 'R3': 27, 'R4': 26, 'R5': 39}),
('normal control 2',
[{'R0': {'bb': 5, 'er': 8, 'h': 7, 'hr': 10, 'outs': 36, 'sb': 5},
'R1': {'bb': 1, 'er': 1, 'h': 20, 'hr': 10, 'outs': 54, 'sb': 8},
'R2': {'bb': 5, 'er': 9, 'h': 11, 'hr': 10, 'outs': 0, 'sb': 5},
'R3': {'bb': 9, 'er': 14, 'h': 22, 'hr': 15, 'outs': 21, 'sb': 8}}],
{'R0': 21, 'R1': 25, 'R2': 11, 'R3': 23}),
('normal control 3',
[{'R0': {'bb': 8, 'er': 1, 'h': 8, 'hr': 10, 'outs': 30, 'sb': 8},
'R1': {'bb': 9, 'er': 10, 'h': 12, 'hr': 12, 'outs': 12, 'sb': 5},
'R2': {'bb': 10, 'er': 4, 'h': 3, 'hr': 12, 'outs': 30, 'sb': 3},
'R3': {'bb': 5, 'er': 4, 'h': 14, 'hr': 10, 'outs': 16, 'sb': 5},
'R4': {'bb': 6, 'er': 6, 'h': 22, 'hr': 15, 'outs': 30, 'sb': 8},
'R5': {'bb': 1, 'er': 12, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 34, 'R1': 18, 'R2': 30, 'R3': 17, 'R4': 35, 'R5': 34}),
('normal control 4',
[{'R0': {'bb': 1, 'er': 6, 'h': 24, 'hr': 12, 'outs': 0, 'sb': 8},
'R1': {'bb': 3, 'er': 0, 'h': 4, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 2, 'er': 4, 'h': 22, 'hr': 15, 'outs': 0, 'sb': 3},
'R3': {'bb': 10, 'er': 9, 'h': 0, 'hr': 12, 'outs': 81, 'sb': 5}}],
{'R0': 19, 'R1': 21, 'R2': 16, 'R3': 24})],
[('regression: ratio precision',
[{'R0': {'bb': 8, 'er': 7, 'h': 22, 'hr': 12, 'outs': 81, 'sb': 3},
'R1': {'bb': 8, 'er': 6, 'h': 24, 'hr': 12, 'outs': 81, 'sb': 5},
'R2': {'bb': 3, 'er': 11, 'h': 17, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 3, 'er': 9, 'h': 8, 'hr': 12, 'outs': 35, 'sb': 8}}],
{'R0': 18, 'R1': 20, 'R2': 20, 'R3': 22}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 2, 'er': 9, 'h': 2, 'hr': 12, 'outs': 81, 'sb': 8},
'R1': {'bb': 2, 'er': 6, 'h': 1, 'hr': 15, 'outs': 0, 'sb': 5},
'R2': {'bb': 9, 'er': 9, 'h': 4, 'hr': 12, 'outs': 82, 'sb': 5},
'R3': {'bb': 1, 'er': 6, 'h': 10, 'hr': 10, 'outs': 27, 'sb': 3},
'R4': {'bb': 8, 'er': 11, 'h': 6, 'hr': 12, 'outs': 27, 'sb': 8},
'R5': {'bb': 1, 'er': 14, 'h': 16, 'hr': 15, 'outs': 54, 'sb': 8}}],
{'R0': 38, 'R1': 20, 'R2': 33, 'R3': 18, 'R4': 24, 'R5': 35}),
('second regression',
[{'R0': {'bb': 2, 'er': 11, 'h': 11, 'hr': 12, 'outs': 81, 'sb': 8},
'R1': {'bb': 0, 'er': 7, 'h': 2, 'hr': 15, 'outs': 54, 'sb': 3},
'R2': {'bb': 6, 'er': 5, 'h': 9, 'hr': 12, 'outs': 30, 'sb': 5}}],
{'R0': 17, 'R1': 20, 'R2': 11}),
('normal control 1',
[{'R0': {'bb': 1, 'er': 12, 'h': 5, 'hr': 12, 'outs': 4, 'sb': 8},
'R1': {'bb': 10, 'er': 5, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 3},
'R2': {'bb': 7, 'er': 5, 'h': 12, 'hr': 12, 'outs': 0, 'sb': 3},
'R3': {'bb': 9, 'er': 1, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 5},
'R4': {'bb': 8, 'er': 4, 'h': 5, 'hr': 12, 'outs': 0, 'sb': 5},
'R5': {'bb': 6, 'er': 8, 'h': 13, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 34, 'R1': 29, 'R2': 17, 'R3': 38, 'R4': 22, 'R5': 28}),
('normal control 2',
[{'R0': {'bb': 0, 'er': 8, 'h': 20, 'hr': 12, 'outs': 8, 'sb': 5},
'R1': {'bb': 2, 'er': 11, 'h': 15, 'hr': 12, 'outs': 27, 'sb': 5},
'R2': {'bb': 4, 'er': 4, 'h': 3, 'hr': 12, 'outs': 81, 'sb': 3},
'R3': {'bb': 7, 'er': 1, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 3},
'R4': {'bb': 4, 'er': 6, 'h': 3, 'hr': 12, 'outs': 0, 'sb': 8},
'R5': {'bb': 9, 'er': 14, 'h': 18, 'hr': 12, 'outs': 27, 'sb': 3}}],
{'R0': 24, 'R1': 32, 'R2': 33, 'R3': 33, 'R4': 23, 'R5': 23}),
('normal control 3',
[{'R0': {'bb': 4, 'er': 14, 'h': 19, 'hr': 12, 'outs': 30, 'sb': 5},
'R1': {'bb': 3, 'er': 3, 'h': 13, 'hr': 12, 'outs': 27, 'sb': 8},
'R2': {'bb': 0, 'er': 7, 'h': 20, 'hr': 10, 'outs': 33, 'sb': 5},
'R3': {'bb': 5, 'er': 7, 'h': 17, 'hr': 10, 'outs': 27, 'sb': 8},
'R4': {'bb': 7, 'er': 11, 'h': 17, 'hr': 12, 'outs': 20, 'sb': 3}}],
{'R0': 23, 'R1': 37, 'R2': 24, 'R3': 22, 'R4': 14}),
('normal control 4',
[{'R0': {'bb': 9, 'er': 4, 'h': 14, 'hr': 10, 'outs': 0, 'sb': 8},
'R1': {'bb': 2, 'er': 0, 'h': 6, 'hr': 10, 'outs': 27, 'sb': 5},
'R2': {'bb': 6, 'er': 5, 'h': 2, 'hr': 12, 'outs': 30, 'sb': 3},
'R3': {'bb': 4, 'er': 11, 'h': 19, 'hr': 12, 'outs': 81, 'sb': 3}}],
{'R0': 15, 'R1': 21, 'R2': 22, 'R3': 22})],
[('regression: ratio precision',
[{'R0': {'bb': 4, 'er': 2, 'h': 19, 'hr': 15, 'outs': 65, 'sb': 5},
'R1': {'bb': 0, 'er': 12, 'h': 21, 'hr': 10, 'outs': 54, 'sb': 3},
'R2': {'bb': 4, 'er': 2, 'h': 7, 'hr': 15, 'outs': 27, 'sb': 3},
'R3': {'bb': 5, 'er': 5, 'h': 23, 'hr': 15, 'outs': 54, 'sb': 5},
'R4': {'bb': 2, 'er': 9, 'h': 3, 'hr': 12, 'outs': 9, 'sb': 3}}],
{'R0': 37, 'R1': 18, 'R2': 26, 'R3': 27, 'R4': 12}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 1, 'er': 5, 'h': 0, 'hr': 10, 'outs': 81, 'sb': 5},
'R1': {'bb': 4, 'er': 8, 'h': 15, 'hr': 15, 'outs': 0, 'sb': 3},
'R2': {'bb': 6, 'er': 1, 'h': 13, 'hr': 12, 'outs': 27, 'sb': 5},
'R3': {'bb': 1, 'er': 8, 'h': 7, 'hr': 12, 'outs': 54, 'sb': 5},
'R4': {'bb': 6, 'er': 7, 'h': 4, 'hr': 12, 'outs': 40, 'sb': 3},
'R5': {'bb': 6, 'er': 14, 'h': 1, 'hr': 12, 'outs': 81, 'sb': 8}}],
{'R0': 32, 'R1': 19, 'R2': 31, 'R3': 31, 'R4': 20, 'R5': 35}),
('second regression',
[{'R0': {'bb': 0, 'er': 1, 'h': 0, 'hr': 12, 'outs': 27, 'sb': 5},
'R1': {'bb': 9, 'er': 5, 'h': 25, 'hr': 15, 'outs': 81, 'sb': 5},
'R2': {'bb': 1, 'er': 12, 'h': 23, 'hr': 15, 'outs': 0, 'sb': 8}}],
{'R0': 17, 'R1': 16, 'R2': 15}),
('normal control 1',
[{'R0': {'bb': 9, 'er': 14, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 3},
'R1': {'bb': 10, 'er': 7, 'h': 19, 'hr': 12, 'outs': 0, 'sb': 5},
'R2': {'bb': 9, 'er': 14, 'h': 1, 'hr': 12, 'outs': 54, 'sb': 5}}],
{'R0': 14, 'R1': 13, 'R2': 21}),
('normal control 2',
[{'R0': {'bb': 8, 'er': 3, 'h': 21, 'hr': 12, 'outs': 81, 'sb': 5},
'R1': {'bb': 3, 'er': 11, 'h': 25, 'hr': 10, 'outs': 50, 'sb': 5},
'R2': {'bb': 7, 'er': 0, 'h': 12, 'hr': 12, 'outs': 54, 'sb': 5},
'R3': {'bb': 2, 'er': 4, 'h': 24, 'hr': 12, 'outs': 0, 'sb': 3},
'R4': {'bb': 4, 'er': 14, 'h': 16, 'hr': 15, 'outs': 0, 'sb': 5}}],
{'R0': 29, 'R1': 21, 'R2': 33, 'R3': 14, 'R4': 23}),
('normal control 3',
[{'R0': {'bb': 0, 'er': 1, 'h': 13, 'hr': 15, 'outs': 55, 'sb': 5},
'R1': {'bb': 10, 'er': 1, 'h': 16, 'hr': 10, 'outs': 27, 'sb': 3},
'R2': {'bb': 3, 'er': 5, 'h': 5, 'hr': 10, 'outs': 54, 'sb': 8},
'R3': {'bb': 2, 'er': 7, 'h': 18, 'hr': 12, 'outs': 27, 'sb': 5}}],
{'R0': 27, 'R1': 13, 'R2': 23, 'R3': 17}),
('normal control 4',
[{'R0': {'bb': 8, 'er': 11, 'h': 20, 'hr': 15, 'outs': 30, 'sb': 8},
'R1': {'bb': 5, 'er': 3, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 7, 'er': 13, 'h': 22, 'hr': 12, 'outs': 30, 'sb': 5}}],
{'R0': 20, 'R1': 18, 'R2': 10})],
[('regression: ratio precision',
[{'R0': {'bb': 9, 'er': 5, 'h': 21, 'hr': 10, 'outs': 81, 'sb': 8},
'R1': {'bb': 6, 'er': 7, 'h': 15, 'hr': 12, 'outs': 30, 'sb': 5},
'R2': {'bb': 6, 'er': 6, 'h': 25, 'hr': 15, 'outs': 54, 'sb': 3},
'R3': {'bb': 3, 'er': 4, 'h': 14, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 6, 'er': 6, 'h': 17, 'hr': 15, 'outs': 30, 'sb': 8}}],
{'R0': 31, 'R1': 16, 'R2': 25, 'R3': 24, 'R4': 24}),
('partial repair probe: ratio precision',
[{'R0': {'bb': 2, 'er': 14, 'h': 3, 'hr': 15, 'outs': 86, 'sb': 5},
'R1': {'bb': 1, 'er': 6, 'h': 5, 'hr': 12, 'outs': 54, 'sb': 5},
'R2': {'bb': 8, 'er': 9, 'h': 8, 'hr': 15, 'outs': 82, 'sb': 5},
'R3': {'bb': 7, 'er': 1, 'h': 9, 'hr': 12, 'outs': 81, 'sb': 5},
'R4': {'bb': 7, 'er': 14, 'h': 20, 'hr': 12, 'outs': 18, 'sb': 5}}],
{'R0': 29, 'R1': 24, 'R2': 29, 'R3': 24, 'R4': 14}),
('second regression',
[{'R0': {'bb': 0, 'er': 12, 'h': 12, 'hr': 12, 'outs': 30, 'sb': 5},
'R1': {'bb': 5, 'er': 14, 'h': 15, 'hr': 12, 'outs': 32, 'sb': 5},
'R2': {'bb': 10, 'er': 0, 'h': 7, 'hr': 10, 'outs': 30, 'sb': 5},
'R3': {'bb': 9, 'er': 1, 'h': 21, 'hr': 12, 'outs': 30, 'sb': 5},
'R4': {'bb': 8, 'er': 7, 'h': 15, 'hr': 12, 'outs': 81, 'sb': 5},
'R5': {'bb': 1, 'er': 1, 'h': 9, 'hr': 10, 'outs': 81, 'sb': 3}}],
{'R0': 29, 'R1': 23, 'R2': 29, 'R3': 27, 'R4': 33, 'R5': 27}),
('normal control 1',
[{'R0': {'bb': 10, 'er': 6, 'h': 21, 'hr': 10, 'outs': 0, 'sb': 3},
'R1': {'bb': 5, 'er': 10, 'h': 16, 'hr': 15, 'outs': 54, 'sb': 5},
'R2': {'bb': 3, 'er': 9, 'h': 24, 'hr': 15, 'outs': 27, 'sb': 3}}],
{'R0': 9, 'R1': 23, 'R2': 16}),
('normal control 2',
[{'R0': {'bb': 8, 'er': 14, 'h': 6, 'hr': 15, 'outs': 27, 'sb': 5},
'R1': {'bb': 9, 'er': 8, 'h': 20, 'hr': 15, 'outs': 0, 'sb': 8},
'R2': {'bb': 1, 'er': 10, 'h': 1, 'hr': 12, 'outs': 78, 'sb': 3}}],
{'R0': 17, 'R1': 15, 'R2': 16}),
('normal control 3',
[{'R0': {'bb': 2, 'er': 13, 'h': 0, 'hr': 15, 'outs': 81, 'sb': 8},
'R1': {'bb': 2, 'er': 0, 'h': 12, 'hr': 12, 'outs': 16, 'sb': 3},
'R2': {'bb': 2, 'er': 3, 'h': 8, 'hr': 12, 'outs': 0, 'sb': 5}}],
{'R0': 22, 'R1': 15, 'R2': 11}),
('normal control 4',
[{'R0': {'bb': 7, 'er': 2, 'h': 22, 'hr': 12, 'outs': 0, 'sb': 5},
'R1': {'bb': 9, 'er': 11, 'h': 25, 'hr': 10, 'outs': 30, 'sb': 5},
'R2': {'bb': 2, 'er': 5, 'h': 0, 'hr': 10, 'outs': 81, 'sb': 3},
'R3': {'bb': 7, 'er': 3, 'h': 13, 'hr': 12, 'outs': 30, 'sb': 3},
'R4': {'bb': 2, 'er': 14, 'h': 5, 'hr': 15, 'outs': 10, 'sb': 3},
'R5': {'bb': 4, 'er': 8, 'h': 0, 'hr': 12, 'outs': 30, 'sb': 8}}],
{'R0': 21, 'R1': 22, 'R2': 31, 'R3': 30, 'R4': 26, 'R5': 38})]]
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: ratio precision | {'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17} | {'R0': 15, 'R1': 17, 'R2': 31, 'R3': 17} | Passed |
| partial repair probe: ratio precision | {'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22} | {'R0': 25, 'R1': 33, 'R2': 25, 'R3': 15, 'R4': 22} | Passed |
| second regression | {'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16} | {'R0': 32, 'R1': 35, 'R2': 35, 'R3': 38, 'R4': 12, 'R5': 16} | Passed |
| normal control 1 | {'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13} | {'R0': 26, 'R1': 21, 'R2': 20, 'R3': 13} | Passed |
| normal control 2 | {'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22} | {'R0': 38, 'R1': 37, 'R2': 15, 'R3': 31, 'R4': 25, 'R5': 22} | Passed |
| normal control 3 | {'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26} | {'R0': 16, 'R1': 27, 'R2': 31, 'R3': 20, 'R4': 26} | Passed |
| normal control 4 | {'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19} | {'R0': 24, 'R1': 22, 'R2': 15, 'R3': 19} | Passed |
SHA-256 / ce94205a474fa3b6edef6b496334814983d5904b833aa0b4714af243ba9bd25e
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 2026-09-29T14:50:37.202175+00:00.
Case digest / b60a8020791f46b2f4b29c7812676b3717296370b8aedb5397d5c39b453ceac5