FA-84771 / Betting odds conversion / Open access

Six-leg teaser looks up a missing payout row · case 01

Teasers with more than five winning legs crash or pay only the stake.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The table lookup is not capped at five legs.

VERIFIED REPAIR

Use the five-leg payout for five or more winners.

Unsuccessful approach: Defaulting missing rows to zero pays nothing extra.

Case contract

Point-spread teaser. legs rows are [team spread line, team margin of victory]; every line is moved in the bettor's favour by points (adjusted = line + points). A leg wins if margin + adjusted > 0, pushes if = 0, loses if < 0. Any losing leg loses the ticket. Pushed legs are dropped; fewer than 2 remaining winners refunds the stake. Payout by winning legs from the American table {2: -120, 3: +160, 4: +260, 5: +400} (5 or more pay +400). Return [status, return cents rounded down].

Why this case matters

Sportsbooks grade teasers with shifted lines, push reduction and a tiered payout table.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
import math
N = 1
observations = []
def solve(legs, points, stake_cents):
    TABLE = {2: -120, 3: 160, 4: 260, 5: 400}
    wins = 0
    for line, margin in legs:
        adj = Fraction(line) + Fraction(points)
        v = margin + adj
        if v < 0:
            return ['lose', 0]
        if v > 0:
            wins += 1
    if wins < 2:
        return ['refund', stake_cents]
    am = TABLE[wins]
    dec = 1 + (Fraction(am, 100) if am > 0 else Fraction(100, -am))
    return ['win', math.floor(stake_cents * dec)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
def run(args):
    try:
        return solve(*args)
    except Exception as exc:
        return 'raised ' + type(exc).__name__
cases = [[('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+2.5', 13], ['-7', 2], ['+1.5', -3], ['-7', 6], ['-10', 8], ['-1', -1]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1', ([['+2.5', 0], ['+2.5', 1], ['+3', -9]], '7', 500), ['win', 1300]),
  ('variant scenario 2',
   ([['+1.5', 9], ['-7', 2], ['-6', -1], ['-1', 8], ['+1.5', -10]], '7', 500),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+2.5', 6], ['-6', 11], ['-7', 1], ['-1', 8], ['-1', -5], ['+7', -7]], '6.5', 1100),
   ['win', 5500]),
  ('variant scenario 1',
   ([['-1', -12], ['-3', -7], ['+2.5', 8], ['+3', -8]], '6', 500),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-1', -10], ['-7', -12], ['-7.5', -9], ['+2.5', 2], ['-1', 14], ['-7', -7]], '7', 500),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+7', -13], ['+1.5', -2], ['-1', -4], ['-3', -1], ['+1.5', -3], ['+3', 5]], '7', 500),
   ['win', 2500]),
  ('variant scenario 1',
   ([['-6', -7], ['-3', 3], ['-10', -2], ['+7', 2], ['-1', -8]], '6.5', 1000),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-10', 0], ['+2.5', -4], ['+2.5', -1], ['-10', -13], ['+7', 10]], '6', 1100),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1',
   ([['-3', -7], ['+7', -4], ['-7.5', -4], ['-3', 3]], '6.5', 1100),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-3', 11], ['-10', 11], ['-7', -10], ['+7', -10]], '7', 1000),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+1.5', 11], ['-1', 3], ['-7.5', 10], ['-6', 13], ['+7', -8], ['-10', 8]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1',
   ([['+1.5', -2], ['+3', -12], ['+2.5', -1], ['-3', 6], ['+3', -2], ['+3', 3]], '6.5', 1100),
   ['lose', 0]),
  ('variant scenario 2',
   ([['+3', 0], ['+3', 14], ['-10', 11], ['+3', 2], ['+2.5', -8], ['-7', -6]], '6.5', 1000),
   ['lose', 0])]]
for label, args, expected in cases[N - 1]:
    check(label, run(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
control two-team teaser	`['win', 2200]`	`['win', 2200]`	Passed
boundary push drops a leg	`['win', 1833]`	`['win', 1833]`	Passed
boundary reduced to one leg	`['refund', 1000]`	`['refund', 1000]`	Passed
control losing leg	`['lose', 0]`	`['lose', 0]`	Passed
control three winners	`['win', 2600]`	`['win', 2600]`	Passed
regression: table cap	`raised KeyError`	`['win', 5000]`	Failed
variant scenario 1	`['win', 1300]`	`['win', 1300]`	Passed
variant scenario 2	`['lose', 0]`	`['lose', 0]`	Passed

SHA-256 / ee1e87fc2bd4508f6dc29a8b47b8b0867da43129e221dad63f02e1661f6eff7f

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
import math
N = 1
observations = []
def solve(legs, points, stake_cents):
    TABLE = {2: -120, 3: 160, 4: 260, 5: 400}
    wins = 0
    for line, margin in legs:
        adj = Fraction(line) + Fraction(points)
        v = margin + adj
        if v < 0:
            return ['lose', 0]
        if v > 0:
            wins += 1
    if wins < 2:
        return ['refund', stake_cents]
    am = TABLE.get(wins, 0)
    dec = 1 + (Fraction(am, 100) if am > 0 else Fraction(100, -am))
    return ['win', math.floor(stake_cents * dec)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
def run(args):
    try:
        return solve(*args)
    except Exception as exc:
        return 'raised ' + type(exc).__name__
cases = [[('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+2.5', 13], ['-7', 2], ['+1.5', -3], ['-7', 6], ['-10', 8], ['-1', -1]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1', ([['+2.5', 0], ['+2.5', 1], ['+3', -9]], '7', 500), ['win', 1300]),
  ('variant scenario 2',
   ([['+1.5', 9], ['-7', 2], ['-6', -1], ['-1', 8], ['+1.5', -10]], '7', 500),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+2.5', 6], ['-6', 11], ['-7', 1], ['-1', 8], ['-1', -5], ['+7', -7]], '6.5', 1100),
   ['win', 5500]),
  ('variant scenario 1',
   ([['-1', -12], ['-3', -7], ['+2.5', 8], ['+3', -8]], '6', 500),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-1', -10], ['-7', -12], ['-7.5', -9], ['+2.5', 2], ['-1', 14], ['-7', -7]], '7', 500),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+7', -13], ['+1.5', -2], ['-1', -4], ['-3', -1], ['+1.5', -3], ['+3', 5]], '7', 500),
   ['win', 2500]),
  ('variant scenario 1',
   ([['-6', -7], ['-3', 3], ['-10', -2], ['+7', 2], ['-1', -8]], '6.5', 1000),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-10', 0], ['+2.5', -4], ['+2.5', -1], ['-10', -13], ['+7', 10]], '6', 1100),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1',
   ([['-3', -7], ['+7', -4], ['-7.5', -4], ['-3', 3]], '6.5', 1100),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-3', 11], ['-10', 11], ['-7', -10], ['+7', -10]], '7', 1000),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+1.5', 11], ['-1', 3], ['-7.5', 10], ['-6', 13], ['+7', -8], ['-10', 8]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1',
   ([['+1.5', -2], ['+3', -12], ['+2.5', -1], ['-3', 6], ['+3', -2], ['+3', 3]], '6.5', 1100),
   ['lose', 0]),
  ('variant scenario 2',
   ([['+3', 0], ['+3', 14], ['-10', 11], ['+3', 2], ['+2.5', -8], ['-7', -6]], '6.5', 1000),
   ['lose', 0])]]
for label, args, expected in cases[N - 1]:
    check(label, run(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
control two-team teaser	`['win', 2200]`	`['win', 2200]`	Passed
boundary push drops a leg	`['win', 1833]`	`['win', 1833]`	Passed
boundary reduced to one leg	`['refund', 1000]`	`['refund', 1000]`	Passed
control losing leg	`['lose', 0]`	`['lose', 0]`	Passed
control three winners	`['win', 2600]`	`['win', 2600]`	Passed
regression: table cap	`raised ZeroDivisionError`	`['win', 5000]`	Failed
variant scenario 1	`['win', 1300]`	`['win', 1300]`	Passed
variant scenario 2	`['lose', 0]`	`['lose', 0]`	Passed

SHA-256 / 79638069f22d4ddb6735a0cbb098901337c4b873b994feea9ce1008bed33a6b7

3 / The verified repair

Exit 0

"""Failure Map reference implementation. Python standard library only."""
import json
from fractions import Fraction
import math
N = 1
observations = []
def solve(legs, points, stake_cents):
    TABLE = {2: -120, 3: 160, 4: 260, 5: 400}
    wins = 0
    for line, margin in legs:
        adj = Fraction(line) + Fraction(points)
        v = margin + adj
        if v < 0:
            return ['lose', 0]
        if v > 0:
            wins += 1
    if wins < 2:
        return ['refund', stake_cents]
    am = TABLE[min(wins, 5)]
    dec = 1 + (Fraction(am, 100) if am > 0 else Fraction(100, -am))
    return ['win', math.floor(stake_cents * dec)]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
def run(args):
    try:
        return solve(*args)
    except Exception as exc:
        return 'raised ' + type(exc).__name__
cases = [[('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+2.5', 13], ['-7', 2], ['+1.5', -3], ['-7', 6], ['-10', 8], ['-1', -1]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1', ([['+2.5', 0], ['+2.5', 1], ['+3', -9]], '7', 500), ['win', 1300]),
  ('variant scenario 2',
   ([['+1.5', 9], ['-7', 2], ['-6', -1], ['-1', 8], ['+1.5', -10]], '7', 500),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+2.5', 6], ['-6', 11], ['-7', 1], ['-1', 8], ['-1', -5], ['+7', -7]], '6.5', 1100),
   ['win', 5500]),
  ('variant scenario 1',
   ([['-1', -12], ['-3', -7], ['+2.5', 8], ['+3', -8]], '6', 500),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-1', -10], ['-7', -12], ['-7.5', -9], ['+2.5', 2], ['-1', 14], ['-7', -7]], '7', 500),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+7', -13], ['+1.5', -2], ['-1', -4], ['-3', -1], ['+1.5', -3], ['+3', 5]], '7', 500),
   ['win', 2500]),
  ('variant scenario 1',
   ([['-6', -7], ['-3', 3], ['-10', -2], ['+7', 2], ['-1', -8]], '6.5', 1000),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-10', 0], ['+2.5', -4], ['+2.5', -1], ['-10', -13], ['+7', 10]], '6', 1100),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5], ['-3', 5]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1',
   ([['-3', -7], ['+7', -4], ['-7.5', -4], ['-3', 3]], '6.5', 1100),
   ['lose', 0]),
  ('variant scenario 2',
   ([['-3', 11], ['-10', 11], ['-7', -10], ['+7', -10]], '7', 1000),
   ['lose', 0])],
 [('control two-team teaser', ([['-7.5', 3], ['+2.5', -5]], '6', 1200), ['win', 2200]),
  ('boundary push drops a leg', ([['-7', 1], ['+3', 0], ['-1', 2]], '6', 1000), ['win', 1833]),
  ('boundary reduced to one leg', ([['-7', 1], ['+3', 5]], '6', 1000), ['refund', 1000]),
  ('control losing leg', ([['-10', 2], ['+3', 5], ['+7', 0]], '6', 1000), ['lose', 0]),
  ('control three winners', ([['-3', 1], ['+3', 0], ['-1', 0]], '6', 1000), ['win', 2600]),
  ('regression: table cap',
   ([['+1.5', 11], ['-1', 3], ['-7.5', 10], ['-6', 13], ['+7', -8], ['-10', 8]], '6', 1000),
   ['win', 5000]),
  ('variant scenario 1',
   ([['+1.5', -2], ['+3', -12], ['+2.5', -1], ['-3', 6], ['+3', -2], ['+3', 3]], '6.5', 1100),
   ['lose', 0]),
  ('variant scenario 2',
   ([['+3', 0], ['+3', 14], ['-10', 11], ['+3', 2], ['+2.5', -8], ['-7', -6]], '6.5', 1000),
   ['lose', 0])]]
for label, args, expected in cases[N - 1]:
    check(label, run(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
control two-team teaser	`['win', 2200]`	`['win', 2200]`	Passed
boundary push drops a leg	`['win', 1833]`	`['win', 1833]`	Passed
boundary reduced to one leg	`['refund', 1000]`	`['refund', 1000]`	Passed
control losing leg	`['lose', 0]`	`['lose', 0]`	Passed
control three winners	`['win', 2600]`	`['win', 2600]`	Passed
regression: table cap	`['win', 5000]`	`['win', 5000]`	Passed
variant scenario 1	`['win', 1300]`	`['win', 1300]`	Passed
variant scenario 2	`['lose', 0]`	`['lose', 0]`	Passed

SHA-256 / 1bd5f7ba862caf9f82e591ed7c8b5569a3474b26c1c994a494277b22b2149d1d

Verification & scope

Stipulated, bounded toy contract stated in the contract field; not a claim of conformance with any operator, exchange or regulator rule set. 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 2026-09-29T14:50:34.088851+00:00.

Case digest / b9d835cb9c8a5ca5462d62527427cdca6c8392f7cebdef1c9ad74f145c6c24c5