FAILURE MAP
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FA-84586 / Betting odds conversion / Open access

Break-even book reported as an arbitrage · case 01

A book summing to exactly 100 percent is reported as a sure bet.

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

ROOT CAUSE

The arbitrage test uses S > 1.

THE FAILURE

The arbitrage test uses S > 1.

Unsuccessful approach: A one-percent tolerance rejects small genuine arbitrages.

Case contract

Arbitrage finder. books rows are [bookmaker, outcome, decimal price]. For each outcome take the highest price; ties go to the alphabetically first bookmaker. S = sum of 1/best price. If S >= 1 return ["no arb"]. Otherwise stake_i = floor(total * (1/d_i) / S) cents; guaranteed return = min over outcomes of floor(stake_i * d_i). Return ["arb", [[outcome, bookmaker, stake] sorted by outcome], guaranteed return - sum of stakes].

Why this case matters

Odds comparison tools flag sure bets and split a bankroll across bookmakers.

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(books, total_cents):
    best = {}
    for book, outcome, price in books:
        d = Fraction(price)
        cur = best.get(outcome)
        if cur is None or d > cur[0] or (d == cur[0] and book < cur[1]):
            best[outcome] = (d, book)
    S = sum(1 / d for d, _ in best.values())
    if S > 1:
        return ['no arb']
    rows = []
    ret = None
    for outcome in sorted(best):
        d, book = best[outcome]
        stake = math.floor(total_cents * (1 / d) / S)
        rows.append([outcome, book, stake])
        r = math.floor(stake * d)
        ret = r if ret is None else min(ret, r)
    return ['arb', rows, ret - sum(r[2] for r in rows)]
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-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['bravo', 'home', '3.77'],
     ['kilo', 'home', '4.11'],
     ['delta', 'home', '3.81'],
     ['kilo', 'draw', '2.56'],
     ['delta', 'draw', '2.44'],
     ['alpha', 'draw', '2.44'],
     ['bravo', 'away', '2.54'],
     ['delta', 'away', '2.78']],
    9999),
   ['arb', [['away', 'delta', 3619], ['draw', 'kilo', 3930], ['home', 'kilo', 2448]], 63]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.17'],
     ['bravo', 'home', '2.25'],
     ['delta', 'away', '1.57'],
     ['alpha', 'away', '1.80']],
    9999),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '4.00'], ['bravo', 'draw', '2.56'], ['alpha', 'away', '2.61']], 10000),
   ['no arb']),
  ('variant scenario 2',
   ([['kilo', 'home', '2.04'],
     ['alpha', 'home', '2.13'],
     ['bravo', 'home', '2.13'],
     ['alpha', 'away', '2.07'],
     ['bravo', 'away', '1.99'],
     ['delta', 'away', '1.86']],
    10000),
   ['arb', [['away', 'alpha', 5071], ['home', 'alpha', 4928]], 497])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['bravo', 'home', '2.24'], ['delta', 'home', '2.40'], ['kilo', 'away', '1.72']], 25000),
   ['arb', [['away', 'kilo', 14563], ['home', 'delta', 10436]], 47]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['alpha', 'home', '2.57'], ['delta', 'away', '1.69'], ['bravo', 'home', '2.57']], 10000),
   ['arb', [['away', 'delta', 6032], ['home', 'alpha', 3967]], 195]),
  ('variant scenario 2',
   ([['bravo', 'home', '5.12'],
     ['kilo', 'home', '5.29'],
     ['delta', 'home', '5.73'],
     ['bravo', 'draw', '2.52'],
     ['kilo', 'draw', '2.36'],
     ['kilo', 'away', '2.51']],
    10000),
   ['arb', [['away', 'kilo', 4108], ['draw', 'bravo', 4092], ['home', 'delta', 1799]], 309])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['delta', 'home', '1.68'],
     ['bravo', 'home', '1.81'],
     ['alpha', 'home', '1.86'],
     ['alpha', 'away', '2.11'],
     ['bravo', 'away', '2.18']],
    9999),
   ['arb', [['away', 'bravo', 4603], ['home', 'alpha', 5395]], 36]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '2.55'],
     ['delta', 'away', '1.60'],
     ['kilo', 'away', '1.43'],
     ['bravo', 'away', '1.43'],
     ['bravo', 'home', '2.55']],
    10000),
   ['no arb']),
  ('variant scenario 2',
   ([['bravo', 'home', '2.81'],
     ['delta', 'home', '3.32'],
     ['kilo', 'home', '2.88'],
     ['alpha', 'draw', '2.81'],
     ['bravo', 'draw', '3.10'],
     ['delta', 'draw', '2.76'],
     ['alpha', 'away', '3.00'],
     ['kilo', 'away', '2.79']],
    10000),
   ['arb', [['away', 'alpha', 3482], ['draw', 'bravo', 3370], ['home', 'delta', 3146]], 446])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['alpha', 'home', '4.94'],
     ['kilo', 'home', '5.07'],
     ['kilo', 'draw', '1.98'],
     ['bravo', 'away', '3.23'],
     ['delta', 'away', '3.40']],
    25000),
   ['arb', [['away', 'delta', 7379], ['draw', 'kilo', 12671], ['home', 'kilo', 4948]], 88]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '1.92'],
     ['bravo', 'draw', '4.45'],
     ['delta', 'draw', '4.87'],
     ['alpha', 'draw', '4.90'],
     ['kilo', 'away', '3.87'],
     ['alpha', 'away', '4.12']],
    25000),
   ['arb', [['away', 'alpha', 6270], ['draw', 'alpha', 5272], ['home', 'bravo', 13456]], 834]),
  ('variant scenario 2',
   ([['alpha', 'home', '1.95'],
     ['bravo', 'home', '2.31'],
     ['bravo', 'away', '1.86'],
     ['alpha', 'away', '1.81'],
     ['kilo', 'away', '1.91']],
    9999),
   ['arb', [['away', 'kilo', 5473], ['home', 'bravo', 4525]], 454])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['bravo', 'home', '2.86'],
     ['kilo', 'draw', '3.14'],
     ['delta', 'draw', '3.06'],
     ['alpha', 'draw', '3.35'],
     ['bravo', 'away', '2.86'],
     ['alpha', 'away', '2.51'],
     ['kilo', 'away', '2.83']],
    9999),
   ['arb', [['away', 'bravo', 3503], ['draw', 'alpha', 2991], ['home', 'bravo', 3503]], 21]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '2.94'],
     ['kilo', 'home', '2.99'],
     ['alpha', 'draw', '3.29'],
     ['bravo', 'draw', '2.93'],
     ['alpha', 'away', '2.69']],
    25000),
   ['no arb']),
  ('variant scenario 2',
   ([['delta', 'home', '2.53'],
     ['alpha', 'home', '2.76'],
     ['kilo', 'draw', '2.86'],
     ['delta', 'draw', '2.83'],
     ['bravo', 'away', '3.60']],
    10000),
   ['arb', [['away', 'bravo', 2806], ['draw', 'kilo', 3532], ['home', 'alpha', 3660]], 103])]]
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 fixtureActualExpectedOutcome
control two-way arb['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]Passed
boundary exactly fair book['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 0]['no arb']Failed
boundary tie goes to first name['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]Passed
control no arb['no arb']['no arb']Passed
regression: arb threshold['arb', [['away', 'delta', 3619], ['draw', 'kilo', 3930], ['home', 'kilo', 2448]], 63]['arb', [['away', 'delta', 3619], ['draw', 'kilo', 3930], ['home', 'kilo', 2448]], 63]Passed
regression: arb threshold['arb', [['away', 'alpha', 5555], ['home', 'bravo', 4444]], 0]['no arb']Failed
variant scenario 1['no arb']['no arb']Passed
variant scenario 2['arb', [['away', 'alpha', 5071], ['home', 'alpha', 4928]], 497]['arb', [['away', 'alpha', 5071], ['home', 'alpha', 4928]], 497]Passed

SHA-256 / 25909d96dc7f53c191ea27cc461ea0ccae16baa46fa60d0fd1b9988e483b6fdc

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(books, total_cents):
    best = {}
    for book, outcome, price in books:
        d = Fraction(price)
        cur = best.get(outcome)
        if cur is None or d > cur[0] or (d == cur[0] and book < cur[1]):
            best[outcome] = (d, book)
    S = sum(1 / d for d, _ in best.values())
    if S >= Fraction(99, 100):
        return ['no arb']
    rows = []
    ret = None
    for outcome in sorted(best):
        d, book = best[outcome]
        stake = math.floor(total_cents * (1 / d) / S)
        rows.append([outcome, book, stake])
        r = math.floor(stake * d)
        ret = r if ret is None else min(ret, r)
    return ['arb', rows, ret - sum(r[2] for r in rows)]
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-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['bravo', 'home', '3.77'],
     ['kilo', 'home', '4.11'],
     ['delta', 'home', '3.81'],
     ['kilo', 'draw', '2.56'],
     ['delta', 'draw', '2.44'],
     ['alpha', 'draw', '2.44'],
     ['bravo', 'away', '2.54'],
     ['delta', 'away', '2.78']],
    9999),
   ['arb', [['away', 'delta', 3619], ['draw', 'kilo', 3930], ['home', 'kilo', 2448]], 63]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.17'],
     ['bravo', 'home', '2.25'],
     ['delta', 'away', '1.57'],
     ['alpha', 'away', '1.80']],
    9999),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '4.00'], ['bravo', 'draw', '2.56'], ['alpha', 'away', '2.61']], 10000),
   ['no arb']),
  ('variant scenario 2',
   ([['kilo', 'home', '2.04'],
     ['alpha', 'home', '2.13'],
     ['bravo', 'home', '2.13'],
     ['alpha', 'away', '2.07'],
     ['bravo', 'away', '1.99'],
     ['delta', 'away', '1.86']],
    10000),
   ['arb', [['away', 'alpha', 5071], ['home', 'alpha', 4928]], 497])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['bravo', 'home', '2.24'], ['delta', 'home', '2.40'], ['kilo', 'away', '1.72']], 25000),
   ['arb', [['away', 'kilo', 14563], ['home', 'delta', 10436]], 47]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['alpha', 'home', '2.57'], ['delta', 'away', '1.69'], ['bravo', 'home', '2.57']], 10000),
   ['arb', [['away', 'delta', 6032], ['home', 'alpha', 3967]], 195]),
  ('variant scenario 2',
   ([['bravo', 'home', '5.12'],
     ['kilo', 'home', '5.29'],
     ['delta', 'home', '5.73'],
     ['bravo', 'draw', '2.52'],
     ['kilo', 'draw', '2.36'],
     ['kilo', 'away', '2.51']],
    10000),
   ['arb', [['away', 'kilo', 4108], ['draw', 'bravo', 4092], ['home', 'delta', 1799]], 309])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['delta', 'home', '1.68'],
     ['bravo', 'home', '1.81'],
     ['alpha', 'home', '1.86'],
     ['alpha', 'away', '2.11'],
     ['bravo', 'away', '2.18']],
    9999),
   ['arb', [['away', 'bravo', 4603], ['home', 'alpha', 5395]], 36]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '2.55'],
     ['delta', 'away', '1.60'],
     ['kilo', 'away', '1.43'],
     ['bravo', 'away', '1.43'],
     ['bravo', 'home', '2.55']],
    10000),
   ['no arb']),
  ('variant scenario 2',
   ([['bravo', 'home', '2.81'],
     ['delta', 'home', '3.32'],
     ['kilo', 'home', '2.88'],
     ['alpha', 'draw', '2.81'],
     ['bravo', 'draw', '3.10'],
     ['delta', 'draw', '2.76'],
     ['alpha', 'away', '3.00'],
     ['kilo', 'away', '2.79']],
    10000),
   ['arb', [['away', 'alpha', 3482], ['draw', 'bravo', 3370], ['home', 'delta', 3146]], 446])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['alpha', 'home', '4.94'],
     ['kilo', 'home', '5.07'],
     ['kilo', 'draw', '1.98'],
     ['bravo', 'away', '3.23'],
     ['delta', 'away', '3.40']],
    25000),
   ['arb', [['away', 'delta', 7379], ['draw', 'kilo', 12671], ['home', 'kilo', 4948]], 88]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '1.92'],
     ['bravo', 'draw', '4.45'],
     ['delta', 'draw', '4.87'],
     ['alpha', 'draw', '4.90'],
     ['kilo', 'away', '3.87'],
     ['alpha', 'away', '4.12']],
    25000),
   ['arb', [['away', 'alpha', 6270], ['draw', 'alpha', 5272], ['home', 'bravo', 13456]], 834]),
  ('variant scenario 2',
   ([['alpha', 'home', '1.95'],
     ['bravo', 'home', '2.31'],
     ['bravo', 'away', '1.86'],
     ['alpha', 'away', '1.81'],
     ['kilo', 'away', '1.91']],
    9999),
   ['arb', [['away', 'kilo', 5473], ['home', 'bravo', 4525]], 454])],
 [('control two-way arb',
   ([['alpha', 'home', '2.10'], ['bravo', 'away', '2.10'], ['bravo', 'home', '1.90']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]),
  ('boundary exactly fair book',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('boundary tie goes to first name',
   ([['kilo', 'home', '2.20'], ['alpha', 'home', '2.20'], ['bravo', 'away', '2.20']], 10000),
   ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]),
  ('control no arb', ([['alpha', 'home', '1.90'], ['alpha', 'away', '1.90']], 10000), ['no arb']),
  ('regression: arb threshold',
   ([['bravo', 'home', '2.86'],
     ['kilo', 'draw', '3.14'],
     ['delta', 'draw', '3.06'],
     ['alpha', 'draw', '3.35'],
     ['bravo', 'away', '2.86'],
     ['alpha', 'away', '2.51'],
     ['kilo', 'away', '2.83']],
    9999),
   ['arb', [['away', 'bravo', 3503], ['draw', 'alpha', 2991], ['home', 'bravo', 3503]], 21]),
  ('regression: arb threshold',
   ([['alpha', 'home', '2.00'], ['bravo', 'away', '2.00']], 10000),
   ['no arb']),
  ('variant scenario 1',
   ([['bravo', 'home', '2.94'],
     ['kilo', 'home', '2.99'],
     ['alpha', 'draw', '3.29'],
     ['bravo', 'draw', '2.93'],
     ['alpha', 'away', '2.69']],
    25000),
   ['no arb']),
  ('variant scenario 2',
   ([['delta', 'home', '2.53'],
     ['alpha', 'home', '2.76'],
     ['kilo', 'draw', '2.86'],
     ['delta', 'draw', '2.83'],
     ['bravo', 'away', '3.60']],
    10000),
   ['arb', [['away', 'bravo', 2806], ['draw', 'kilo', 3532], ['home', 'alpha', 3660]], 103])]]
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 fixtureActualExpectedOutcome
control two-way arb['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500]Passed
boundary exactly fair book['no arb']['no arb']Passed
boundary tie goes to first name['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 1000]Passed
control no arb['no arb']['no arb']Passed
regression: arb threshold['no arb']['arb', [['away', 'delta', 3619], ['draw', 'kilo', 3930], ['home', 'kilo', 2448]], 63]Failed
regression: arb threshold['no arb']['no arb']Passed
variant scenario 1['no arb']['no arb']Passed
variant scenario 2['arb', [['away', 'alpha', 5071], ['home', 'alpha', 4928]], 497]['arb', [['away', 'alpha', 5071], ['home', 'alpha', 4928]], 497]Passed

SHA-256 / dc143538ffa0601d52db418170bd2f6fe265eddf8529a2fa05070599f5e5b2a8

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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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 2026-09-29T14:50:32.376321+00:00.

Case digest / 4d3a583521fc38edaf66f5d43d3990017faca55d788e6074953deac1d0d056ce