FA-85321 / Fantasy sports scoring / Open access

50-yard touchdown tier unreachable · case 01

An 80-yard touchdown earns the 40-yard bonus.

Verified by executionVariant 1 · 7 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The 40+ tier is tested first, shadowing the 50+ tier.

VERIFIED REPAIR

Test the 50+ tier before the 40-49 tier.

Unsuccessful approach: Adding the difference only above 50 misses touchdowns of exactly 50 yards.

Case contract

Per-play bonus tenths for one player: a touchdown of 50+ yards earns 3, a touchdown of 40-49 yards earns 2 (exclusive tiers); every rushing or receiving play (not passing) of 20+ yards earns 0.5 whether or not it scored; three or more touchdowns in the game earn 2 once.

Why this case matters

Long-play bonuses are layered rules where tier order and play-type filters are easy to get wrong.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(plays):
    bonus = 0
    for kind, yards, td in plays:
        if td and yards >= 40:
            bonus += 20
        elif td and yards >= 50:
            bonus += 30
        if kind != 'pass' and yards >= 20:
            bonus += 5
    tds = sum(1 for _, _, td in plays if td)
    if tds >= 3:
        bonus += 20
    return bonus
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: tier check order', [[['pass', 5, False], ['rush', 50, True], ['rush', 19, False]]], 35),
  ('partial repair probe: tier check order',
   [[['rec', -3, True], ['pass', 19, False], ['rec', 3, False], ['rush', 5, True], ['pass', 50, True]]], 50),
  ('second regression', [[['rec', 50, True], ['rec', 40, False], ['rec', 39, True]]], 45),
  ('normal control 1', [[['rec', 19, False], ['pass', 40, True]]], 20),
  ('normal control 2', [[['rec', 50, False], ['rec', 5, True], ['rec', 40, False]]], 10),
  ('normal control 3',
   [[['rec', 49, False], ['rush', 49, False], ['pass', 40, False], ['rec', 39, True], ['rec', 19, False],
     ['rush', 5, True]]],
   15),
  ('normal control 4', [[['rec', 19, True]]], 0)],
 [('regression: tier check order',
   [[['rec', 5, False], ['pass', 19, True], ['pass', 50, True], ['rush', 50, False]]], 35),
  ('partial repair probe: tier check order',
   [[['rush', 20, True], ['rec', 50, True], ['pass', 39, False], ['pass', 51, False]]], 40),
  ('second regression', [[['rush', 19, False], ['rush', 50, False], ['pass', 20, True], ['rush', 51, True]]],
   40),
  ('normal control 1', [[['rush', 39, True], ['rec', 40, False], ['pass', 39, True], ['rush', 9, False]]],
   10),
  ('normal control 2', [[['rush', 39, True], ['pass', 40, False]]], 5),
  ('normal control 3', [[['rec', 20, False], ['rush', -3, False], ['rec', -3, True], ['pass', -3, False]]],
   5),
  ('normal control 4', [[['rush', 50, False], ['pass', 49, False], ['rush', 20, True], ['pass', -3, False]]],
   10)],
 [('regression: tier check order', [[['pass', 49, False], ['pass', 51, True]]], 30),
  ('partial repair probe: tier check order', [[['rec', 50, True], ['rec', 50, True], ['rush', 20, True]]],
   95),
  ('second regression',
   [[['rec', 5, True], ['rush', 19, False], ['pass', 41, False], ['rush', 51, True], ['rec', 20, True]]],
   60),
  ('normal control 1',
   [[['rush', 19, True], ['pass', 51, False], ['pass', 39, False], ['pass', 51, False], ['pass', 49, True]]],
   20),
  ('normal control 2',
   [[['pass', 39, False], ['rec', 50, False], ['rec', 50, False], ['rush', 3, True], ['rush', 19, False],
     ['rec', 5, True]]],
   10),
  ('normal control 3', [[['pass', 20, False]]], 0),
  ('normal control 4',
   [[['pass', 39, False], ['rec', 20, True], ['pass', 40, False], ['pass', 41, False], ['pass', 39, False]]],
   5)],
 [('regression: tier check order',
   [[['pass', 50, True], ['pass', 40, True], ['rush', 49, False], ['pass', 43, True]]], 95),
  ('partial repair probe: tier check order', [[['rush', 39, True], ['pass', 50, True], ['pass', 5, False]]],
   35),
  ('second regression', [[['pass', 50, True]]], 30),
  ('normal control 1', [[['pass', 20, True], ['rush', 40, False], ['rush', 39, False], ['pass', 49, True]]],
   30),
  ('normal control 2',
   [[['rush', 39, False], ['rec', 49, False], ['pass', 61, False], ['pass', -3, False], ['rush', 19, True],
     ['rec', 5, False]]],
   10),
  ('normal control 3', [[['rec', 5, False], ['pass', -5, True]]], 0),
  ('normal control 4', [[['rush', 53, False], ['pass', 39, False]]], 5)],
 [('regression: tier check order',
   [[['rush', 50, True], ['rush', 20, True], ['pass', 49, False], ['rec', -3, False]]], 40),
  ('partial repair probe: tier check order',
   [[['rec', 49, False], ['rush', 51, False], ['rush', 51, True], ['rec', 5, True], ['rec', 50, True]]],
   100),
  ('second regression',
   [[['rush', 51, True], ['rec', 55, False], ['rec', 41, True], ['pass', 39, False], ['pass', 5, False]]],
   65),
  ('normal control 1',
   [[['pass', 41, False], ['rush', 40, False], ['rec', 5, False], ['rush', 49, True], ['pass', 49, False]]],
   30),
  ('normal control 2', [[['pass', 51, False], ['pass', -3, False]]], 0),
  ('normal control 3', [[['rec', 19, False]]], 0),
  ('normal control 4', [[['rush', 49, False], ['rush', 20, True], ['rush', 49, False], ['rush', 40, False]]],
   20)]]
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: tier check order	`25`	`35`	Failed
partial repair probe: tier check order	`40`	`50`	Failed
second regression	`35`	`45`	Failed
normal control 1	`20`	`20`	Passed
normal control 2	`10`	`10`	Passed
normal control 3	`15`	`15`	Passed
normal control 4	`0`	`0`	Passed

SHA-256 / dc60fb3f002a45a351ae8fa1b7aa5c5caf3c5ea46af4d392321cc684af09f067

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(plays):
    bonus = 0
    for kind, yards, td in plays:
        if td and yards >= 40:
            bonus += 20 + (10 if yards > 50 else 0)
        if kind != 'pass' and yards >= 20:
            bonus += 5
    tds = sum(1 for _, _, td in plays if td)
    if tds >= 3:
        bonus += 20
    return bonus
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: tier check order', [[['pass', 5, False], ['rush', 50, True], ['rush', 19, False]]], 35),
  ('partial repair probe: tier check order',
   [[['rec', -3, True], ['pass', 19, False], ['rec', 3, False], ['rush', 5, True], ['pass', 50, True]]], 50),
  ('second regression', [[['rec', 50, True], ['rec', 40, False], ['rec', 39, True]]], 45),
  ('normal control 1', [[['rec', 19, False], ['pass', 40, True]]], 20),
  ('normal control 2', [[['rec', 50, False], ['rec', 5, True], ['rec', 40, False]]], 10),
  ('normal control 3',
   [[['rec', 49, False], ['rush', 49, False], ['pass', 40, False], ['rec', 39, True], ['rec', 19, False],
     ['rush', 5, True]]],
   15),
  ('normal control 4', [[['rec', 19, True]]], 0)],
 [('regression: tier check order',
   [[['rec', 5, False], ['pass', 19, True], ['pass', 50, True], ['rush', 50, False]]], 35),
  ('partial repair probe: tier check order',
   [[['rush', 20, True], ['rec', 50, True], ['pass', 39, False], ['pass', 51, False]]], 40),
  ('second regression', [[['rush', 19, False], ['rush', 50, False], ['pass', 20, True], ['rush', 51, True]]],
   40),
  ('normal control 1', [[['rush', 39, True], ['rec', 40, False], ['pass', 39, True], ['rush', 9, False]]],
   10),
  ('normal control 2', [[['rush', 39, True], ['pass', 40, False]]], 5),
  ('normal control 3', [[['rec', 20, False], ['rush', -3, False], ['rec', -3, True], ['pass', -3, False]]],
   5),
  ('normal control 4', [[['rush', 50, False], ['pass', 49, False], ['rush', 20, True], ['pass', -3, False]]],
   10)],
 [('regression: tier check order', [[['pass', 49, False], ['pass', 51, True]]], 30),
  ('partial repair probe: tier check order', [[['rec', 50, True], ['rec', 50, True], ['rush', 20, True]]],
   95),
  ('second regression',
   [[['rec', 5, True], ['rush', 19, False], ['pass', 41, False], ['rush', 51, True], ['rec', 20, True]]],
   60),
  ('normal control 1',
   [[['rush', 19, True], ['pass', 51, False], ['pass', 39, False], ['pass', 51, False], ['pass', 49, True]]],
   20),
  ('normal control 2',
   [[['pass', 39, False], ['rec', 50, False], ['rec', 50, False], ['rush', 3, True], ['rush', 19, False],
     ['rec', 5, True]]],
   10),
  ('normal control 3', [[['pass', 20, False]]], 0),
  ('normal control 4',
   [[['pass', 39, False], ['rec', 20, True], ['pass', 40, False], ['pass', 41, False], ['pass', 39, False]]],
   5)],
 [('regression: tier check order',
   [[['pass', 50, True], ['pass', 40, True], ['rush', 49, False], ['pass', 43, True]]], 95),
  ('partial repair probe: tier check order', [[['rush', 39, True], ['pass', 50, True], ['pass', 5, False]]],
   35),
  ('second regression', [[['pass', 50, True]]], 30),
  ('normal control 1', [[['pass', 20, True], ['rush', 40, False], ['rush', 39, False], ['pass', 49, True]]],
   30),
  ('normal control 2',
   [[['rush', 39, False], ['rec', 49, False], ['pass', 61, False], ['pass', -3, False], ['rush', 19, True],
     ['rec', 5, False]]],
   10),
  ('normal control 3', [[['rec', 5, False], ['pass', -5, True]]], 0),
  ('normal control 4', [[['rush', 53, False], ['pass', 39, False]]], 5)],
 [('regression: tier check order',
   [[['rush', 50, True], ['rush', 20, True], ['pass', 49, False], ['rec', -3, False]]], 40),
  ('partial repair probe: tier check order',
   [[['rec', 49, False], ['rush', 51, False], ['rush', 51, True], ['rec', 5, True], ['rec', 50, True]]],
   100),
  ('second regression',
   [[['rush', 51, True], ['rec', 55, False], ['rec', 41, True], ['pass', 39, False], ['pass', 5, False]]],
   65),
  ('normal control 1',
   [[['pass', 41, False], ['rush', 40, False], ['rec', 5, False], ['rush', 49, True], ['pass', 49, False]]],
   30),
  ('normal control 2', [[['pass', 51, False], ['pass', -3, False]]], 0),
  ('normal control 3', [[['rec', 19, False]]], 0),
  ('normal control 4', [[['rush', 49, False], ['rush', 20, True], ['rush', 49, False], ['rush', 40, False]]],
   20)]]
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: tier check order	`25`	`35`	Failed
partial repair probe: tier check order	`40`	`50`	Failed
second regression	`35`	`45`	Failed
normal control 1	`20`	`20`	Passed
normal control 2	`10`	`10`	Passed
normal control 3	`15`	`15`	Passed
normal control 4	`0`	`0`	Passed

SHA-256 / b3c5faf1959685cd0696b6e7275723d46a5070fb89dc5df72d469be3e3050508

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json

N = 1
observations = []
def solve(plays):
    bonus = 0
    for kind, yards, td in plays:
        if td and yards >= 50:
            bonus += 30
        elif td and yards >= 40:
            bonus += 20
        if kind != 'pass' and yards >= 20:
            bonus += 5
    tds = sum(1 for _, _, td in plays if td)
    if tds >= 3:
        bonus += 20
    return bonus
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('regression: tier check order', [[['pass', 5, False], ['rush', 50, True], ['rush', 19, False]]], 35),
  ('partial repair probe: tier check order',
   [[['rec', -3, True], ['pass', 19, False], ['rec', 3, False], ['rush', 5, True], ['pass', 50, True]]], 50),
  ('second regression', [[['rec', 50, True], ['rec', 40, False], ['rec', 39, True]]], 45),
  ('normal control 1', [[['rec', 19, False], ['pass', 40, True]]], 20),
  ('normal control 2', [[['rec', 50, False], ['rec', 5, True], ['rec', 40, False]]], 10),
  ('normal control 3',
   [[['rec', 49, False], ['rush', 49, False], ['pass', 40, False], ['rec', 39, True], ['rec', 19, False],
     ['rush', 5, True]]],
   15),
  ('normal control 4', [[['rec', 19, True]]], 0)],
 [('regression: tier check order',
   [[['rec', 5, False], ['pass', 19, True], ['pass', 50, True], ['rush', 50, False]]], 35),
  ('partial repair probe: tier check order',
   [[['rush', 20, True], ['rec', 50, True], ['pass', 39, False], ['pass', 51, False]]], 40),
  ('second regression', [[['rush', 19, False], ['rush', 50, False], ['pass', 20, True], ['rush', 51, True]]],
   40),
  ('normal control 1', [[['rush', 39, True], ['rec', 40, False], ['pass', 39, True], ['rush', 9, False]]],
   10),
  ('normal control 2', [[['rush', 39, True], ['pass', 40, False]]], 5),
  ('normal control 3', [[['rec', 20, False], ['rush', -3, False], ['rec', -3, True], ['pass', -3, False]]],
   5),
  ('normal control 4', [[['rush', 50, False], ['pass', 49, False], ['rush', 20, True], ['pass', -3, False]]],
   10)],
 [('regression: tier check order', [[['pass', 49, False], ['pass', 51, True]]], 30),
  ('partial repair probe: tier check order', [[['rec', 50, True], ['rec', 50, True], ['rush', 20, True]]],
   95),
  ('second regression',
   [[['rec', 5, True], ['rush', 19, False], ['pass', 41, False], ['rush', 51, True], ['rec', 20, True]]],
   60),
  ('normal control 1',
   [[['rush', 19, True], ['pass', 51, False], ['pass', 39, False], ['pass', 51, False], ['pass', 49, True]]],
   20),
  ('normal control 2',
   [[['pass', 39, False], ['rec', 50, False], ['rec', 50, False], ['rush', 3, True], ['rush', 19, False],
     ['rec', 5, True]]],
   10),
  ('normal control 3', [[['pass', 20, False]]], 0),
  ('normal control 4',
   [[['pass', 39, False], ['rec', 20, True], ['pass', 40, False], ['pass', 41, False], ['pass', 39, False]]],
   5)],
 [('regression: tier check order',
   [[['pass', 50, True], ['pass', 40, True], ['rush', 49, False], ['pass', 43, True]]], 95),
  ('partial repair probe: tier check order', [[['rush', 39, True], ['pass', 50, True], ['pass', 5, False]]],
   35),
  ('second regression', [[['pass', 50, True]]], 30),
  ('normal control 1', [[['pass', 20, True], ['rush', 40, False], ['rush', 39, False], ['pass', 49, True]]],
   30),
  ('normal control 2',
   [[['rush', 39, False], ['rec', 49, False], ['pass', 61, False], ['pass', -3, False], ['rush', 19, True],
     ['rec', 5, False]]],
   10),
  ('normal control 3', [[['rec', 5, False], ['pass', -5, True]]], 0),
  ('normal control 4', [[['rush', 53, False], ['pass', 39, False]]], 5)],
 [('regression: tier check order',
   [[['rush', 50, True], ['rush', 20, True], ['pass', 49, False], ['rec', -3, False]]], 40),
  ('partial repair probe: tier check order',
   [[['rec', 49, False], ['rush', 51, False], ['rush', 51, True], ['rec', 5, True], ['rec', 50, True]]],
   100),
  ('second regression',
   [[['rush', 51, True], ['rec', 55, False], ['rec', 41, True], ['pass', 39, False], ['pass', 5, False]]],
   65),
  ('normal control 1',
   [[['pass', 41, False], ['rush', 40, False], ['rec', 5, False], ['rush', 49, True], ['pass', 49, False]]],
   30),
  ('normal control 2', [[['pass', 51, False], ['pass', -3, False]]], 0),
  ('normal control 3', [[['rec', 19, False]]], 0),
  ('normal control 4', [[['rush', 49, False], ['rush', 20, True], ['rush', 49, False], ['rush', 40, False]]],
   20)]]
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: tier check order	`35`	`35`	Passed
partial repair probe: tier check order	`50`	`50`	Passed
second regression	`45`	`45`	Passed
normal control 1	`20`	`20`	Passed
normal control 2	`10`	`10`	Passed
normal control 3	`15`	`15`	Passed
normal control 4	`0`	`0`	Passed

SHA-256 / 032f1bcc39887749ba308fcdb91b09874eb4c892b66e38a8a98b5b43f0e715fd

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 2026-09-29T14:50:39.257485+00:00.

Case digest / 2d9525663e0185b6a06520180449075e8610e0ed4071aa783bb5e2c9c1e8b1de