FA-84576 / Betting odds conversion / Open access
Arbitrage scan keeps the worst price per outcome · case 01
Genuine sure bets are missed because the lowest quote is used.
ROOT CAUSE
The best-price comparison keeps a lower price.
VERIFIED REPAIR
Keep the highest price per outcome.
Unsuccessful approach: Keeping the last quote seen per outcome depends on feed order.
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: best price selection',
([['kilo', 'home', '1.77'],
['delta', 'home', '1.79'],
['kilo', 'away', '2.33'],
['bravo', 'away', '2.21'],
['delta', 'away', '2.07']],
25000),
['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307]),
('variant scenario 1',
([['bravo', 'home', '1.69'],
['alpha', 'away', '2.32'],
['bravo', 'away', '2.14'],
['delta', 'away', '2.26']],
10000),
['no arb']),
('variant scenario 2',
([['kilo', 'home', '2.33'], ['delta', 'away', '1.88'], ['bravo', 'away', '1.91']], 9999),
['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495])],
[('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: best price selection',
([['delta', 'home', '3.08'],
['alpha', 'home', '2.92'],
['kilo', 'draw', '2.68'],
['alpha', 'away', '3.29'],
['delta', 'away', '3.29'],
['kilo', 'away', '3.68']],
10000),
['arb', [['away', 'kilo', 2802], ['draw', 'kilo', 3848], ['home', 'delta', 3348]], 313]),
('variant scenario 1',
([['delta', 'home', '3.01'],
['kilo', 'home', '2.64'],
['kilo', 'draw', '3.17'],
['alpha', 'draw', '3.30'],
['delta', 'away', '3.27']],
25000),
['arb', [['away', 'delta', 8124], ['draw', 'alpha', 8050], ['home', 'delta', 8825]], 1564]),
('variant scenario 2',
([['kilo', 'home', '2.66'],
['alpha', 'home', '2.70'],
['bravo', 'home', '2.71'],
['kilo', 'away', '1.72'],
['delta', 'away', '1.54'],
['alpha', 'home', '2.66']],
25000),
['arb', [['away', 'kilo', 15293], ['home', 'bravo', 9706]], 1304])],
[('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: best price selection',
([['kilo', 'home', '2.23'],
['alpha', 'away', '1.83'],
['kilo', 'away', '2.07'],
['bravo', 'away', '1.86']],
10000),
['arb', [['away', 'kilo', 5186], ['home', 'kilo', 4813]], 733]),
('variant scenario 1',
([['delta', 'home', '1.53'],
['delta', 'away', '2.80'],
['bravo', 'away', '2.80'],
['kilo', 'away', '2.70']],
9999),
['no arb']),
('variant scenario 2',
([['kilo', 'home', '2.53'],
['delta', 'home', '3.01'],
['alpha', 'draw', '3.61'],
['kilo', 'draw', '3.70'],
['delta', 'draw', '3.67'],
['kilo', 'away', '2.87'],
['bravo', 'away', '2.92'],
['delta', 'away', '2.58']],
10000),
['arb', [['away', 'bravo', 3624], ['draw', 'kilo', 2860], ['home', 'delta', 3515]], 581])],
[('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: best price selection',
([['delta', 'home', '3.40'],
['bravo', 'home', '3.33'],
['kilo', 'draw', '2.36'],
['delta', 'draw', '2.28'],
['kilo', 'away', '3.93'],
['bravo', 'away', '3.75']],
10000),
['arb', [['away', 'kilo', 2617], ['draw', 'kilo', 4358], ['home', 'delta', 3024]], 282]),
('variant scenario 1',
([['kilo', 'home', '3.59'],
['bravo', 'home', '3.20'],
['alpha', 'home', '3.30'],
['alpha', 'draw', '2.44'],
['kilo', 'draw', '2.29'],
['bravo', 'draw', '2.36'],
['delta', 'away', '3.54'],
['bravo', 'away', '3.81']],
9999),
['arb', [['away', 'bravo', 2760], ['draw', 'alpha', 4309], ['home', 'kilo', 2929]], 515]),
('variant scenario 2',
([['alpha', 'home', '3.52'], ['delta', 'away', '1.35'], ['bravo', 'away', '1.48']], 9999),
['arb', [['away', 'bravo', 7039], ['home', 'alpha', 2959]], 417])],
[('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: best price selection',
([['bravo', 'home', '2.92'],
['alpha', 'home', '3.07'],
['kilo', 'home', '3.06'],
['alpha', 'draw', '3.65'],
['delta', 'draw', '3.52'],
['delta', 'away', '2.53'],
['alpha', 'away', '2.36'],
['bravo', 'away', '2.67']],
9999),
['arb', [['away', 'bravo', 3843], ['draw', 'alpha', 2811], ['home', 'alpha', 3343]], 263]),
('variant scenario 1',
([['kilo', 'home', '2.38'],
['alpha', 'home', '2.05'],
['bravo', 'home', '2.37'],
['alpha', 'away', '1.74'],
['bravo', 'away', '1.82']],
10000),
['arb', [['away', 'bravo', 5666], ['home', 'kilo', 4333]], 313]),
('variant scenario 2',
([['delta', 'home', '4.55'],
['bravo', 'home', '4.54'],
['kilo', 'home', '4.47'],
['kilo', 'draw', '2.17'],
['delta', 'draw', '2.23'],
['bravo', 'draw', '2.19'],
['bravo', 'away', '3.24'],
['delta', 'away', '3.26'],
['kilo', 'away', '3.37']],
10000),
['arb', [['away', 'kilo', 3075], ['draw', 'delta', 4647], ['home', 'delta', 2277]], 361])]]
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-way arb | ['no arb'] | ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500] | Failed |
| 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: best price selection | ['no arb'] | ['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307] | Failed |
| variant scenario 1 | ['no arb'] | ['no arb'] | Passed |
| variant scenario 2 | ['arb', [['away', 'delta', 5533], ['home', 'kilo', 4465]], 404] | ['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495] | Failed |
SHA-256 / d6979eb523c8c01680ab3e00deb9f27e32f907b8670043c70f7edb0754e317d1
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 True:
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: best price selection',
([['kilo', 'home', '1.77'],
['delta', 'home', '1.79'],
['kilo', 'away', '2.33'],
['bravo', 'away', '2.21'],
['delta', 'away', '2.07']],
25000),
['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307]),
('variant scenario 1',
([['bravo', 'home', '1.69'],
['alpha', 'away', '2.32'],
['bravo', 'away', '2.14'],
['delta', 'away', '2.26']],
10000),
['no arb']),
('variant scenario 2',
([['kilo', 'home', '2.33'], ['delta', 'away', '1.88'], ['bravo', 'away', '1.91']], 9999),
['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495])],
[('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: best price selection',
([['delta', 'home', '3.08'],
['alpha', 'home', '2.92'],
['kilo', 'draw', '2.68'],
['alpha', 'away', '3.29'],
['delta', 'away', '3.29'],
['kilo', 'away', '3.68']],
10000),
['arb', [['away', 'kilo', 2802], ['draw', 'kilo', 3848], ['home', 'delta', 3348]], 313]),
('variant scenario 1',
([['delta', 'home', '3.01'],
['kilo', 'home', '2.64'],
['kilo', 'draw', '3.17'],
['alpha', 'draw', '3.30'],
['delta', 'away', '3.27']],
25000),
['arb', [['away', 'delta', 8124], ['draw', 'alpha', 8050], ['home', 'delta', 8825]], 1564]),
('variant scenario 2',
([['kilo', 'home', '2.66'],
['alpha', 'home', '2.70'],
['bravo', 'home', '2.71'],
['kilo', 'away', '1.72'],
['delta', 'away', '1.54'],
['alpha', 'home', '2.66']],
25000),
['arb', [['away', 'kilo', 15293], ['home', 'bravo', 9706]], 1304])],
[('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: best price selection',
([['kilo', 'home', '2.23'],
['alpha', 'away', '1.83'],
['kilo', 'away', '2.07'],
['bravo', 'away', '1.86']],
10000),
['arb', [['away', 'kilo', 5186], ['home', 'kilo', 4813]], 733]),
('variant scenario 1',
([['delta', 'home', '1.53'],
['delta', 'away', '2.80'],
['bravo', 'away', '2.80'],
['kilo', 'away', '2.70']],
9999),
['no arb']),
('variant scenario 2',
([['kilo', 'home', '2.53'],
['delta', 'home', '3.01'],
['alpha', 'draw', '3.61'],
['kilo', 'draw', '3.70'],
['delta', 'draw', '3.67'],
['kilo', 'away', '2.87'],
['bravo', 'away', '2.92'],
['delta', 'away', '2.58']],
10000),
['arb', [['away', 'bravo', 3624], ['draw', 'kilo', 2860], ['home', 'delta', 3515]], 581])],
[('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: best price selection',
([['delta', 'home', '3.40'],
['bravo', 'home', '3.33'],
['kilo', 'draw', '2.36'],
['delta', 'draw', '2.28'],
['kilo', 'away', '3.93'],
['bravo', 'away', '3.75']],
10000),
['arb', [['away', 'kilo', 2617], ['draw', 'kilo', 4358], ['home', 'delta', 3024]], 282]),
('variant scenario 1',
([['kilo', 'home', '3.59'],
['bravo', 'home', '3.20'],
['alpha', 'home', '3.30'],
['alpha', 'draw', '2.44'],
['kilo', 'draw', '2.29'],
['bravo', 'draw', '2.36'],
['delta', 'away', '3.54'],
['bravo', 'away', '3.81']],
9999),
['arb', [['away', 'bravo', 2760], ['draw', 'alpha', 4309], ['home', 'kilo', 2929]], 515]),
('variant scenario 2',
([['alpha', 'home', '3.52'], ['delta', 'away', '1.35'], ['bravo', 'away', '1.48']], 9999),
['arb', [['away', 'bravo', 7039], ['home', 'alpha', 2959]], 417])],
[('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: best price selection',
([['bravo', 'home', '2.92'],
['alpha', 'home', '3.07'],
['kilo', 'home', '3.06'],
['alpha', 'draw', '3.65'],
['delta', 'draw', '3.52'],
['delta', 'away', '2.53'],
['alpha', 'away', '2.36'],
['bravo', 'away', '2.67']],
9999),
['arb', [['away', 'bravo', 3843], ['draw', 'alpha', 2811], ['home', 'alpha', 3343]], 263]),
('variant scenario 1',
([['kilo', 'home', '2.38'],
['alpha', 'home', '2.05'],
['bravo', 'home', '2.37'],
['alpha', 'away', '1.74'],
['bravo', 'away', '1.82']],
10000),
['arb', [['away', 'bravo', 5666], ['home', 'kilo', 4333]], 313]),
('variant scenario 2',
([['delta', 'home', '4.55'],
['bravo', 'home', '4.54'],
['kilo', 'home', '4.47'],
['kilo', 'draw', '2.17'],
['delta', 'draw', '2.23'],
['bravo', 'draw', '2.19'],
['bravo', 'away', '3.24'],
['delta', 'away', '3.26'],
['kilo', 'away', '3.37']],
10000),
['arb', [['away', 'kilo', 3075], ['draw', 'delta', 4647], ['home', 'delta', 2277]], 361])]]
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-way arb | ['no arb'] | ['arb', [['away', 'bravo', 5000], ['home', 'alpha', 5000]], 500] | Failed |
| 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: best price selection | ['no arb'] | ['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307] | Failed |
| variant scenario 1 | ['no arb'] | ['no arb'] | Passed |
| variant scenario 2 | ['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495] | ['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495] | Passed |
SHA-256 / 61711b2a9369255294524fcf487435fb75fa87c177cd878fd7895a008d757007
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(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: best price selection',
([['kilo', 'home', '1.77'],
['delta', 'home', '1.79'],
['kilo', 'away', '2.33'],
['bravo', 'away', '2.21'],
['delta', 'away', '2.07']],
25000),
['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307]),
('variant scenario 1',
([['bravo', 'home', '1.69'],
['alpha', 'away', '2.32'],
['bravo', 'away', '2.14'],
['delta', 'away', '2.26']],
10000),
['no arb']),
('variant scenario 2',
([['kilo', 'home', '2.33'], ['delta', 'away', '1.88'], ['bravo', 'away', '1.91']], 9999),
['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495])],
[('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: best price selection',
([['delta', 'home', '3.08'],
['alpha', 'home', '2.92'],
['kilo', 'draw', '2.68'],
['alpha', 'away', '3.29'],
['delta', 'away', '3.29'],
['kilo', 'away', '3.68']],
10000),
['arb', [['away', 'kilo', 2802], ['draw', 'kilo', 3848], ['home', 'delta', 3348]], 313]),
('variant scenario 1',
([['delta', 'home', '3.01'],
['kilo', 'home', '2.64'],
['kilo', 'draw', '3.17'],
['alpha', 'draw', '3.30'],
['delta', 'away', '3.27']],
25000),
['arb', [['away', 'delta', 8124], ['draw', 'alpha', 8050], ['home', 'delta', 8825]], 1564]),
('variant scenario 2',
([['kilo', 'home', '2.66'],
['alpha', 'home', '2.70'],
['bravo', 'home', '2.71'],
['kilo', 'away', '1.72'],
['delta', 'away', '1.54'],
['alpha', 'home', '2.66']],
25000),
['arb', [['away', 'kilo', 15293], ['home', 'bravo', 9706]], 1304])],
[('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: best price selection',
([['kilo', 'home', '2.23'],
['alpha', 'away', '1.83'],
['kilo', 'away', '2.07'],
['bravo', 'away', '1.86']],
10000),
['arb', [['away', 'kilo', 5186], ['home', 'kilo', 4813]], 733]),
('variant scenario 1',
([['delta', 'home', '1.53'],
['delta', 'away', '2.80'],
['bravo', 'away', '2.80'],
['kilo', 'away', '2.70']],
9999),
['no arb']),
('variant scenario 2',
([['kilo', 'home', '2.53'],
['delta', 'home', '3.01'],
['alpha', 'draw', '3.61'],
['kilo', 'draw', '3.70'],
['delta', 'draw', '3.67'],
['kilo', 'away', '2.87'],
['bravo', 'away', '2.92'],
['delta', 'away', '2.58']],
10000),
['arb', [['away', 'bravo', 3624], ['draw', 'kilo', 2860], ['home', 'delta', 3515]], 581])],
[('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: best price selection',
([['delta', 'home', '3.40'],
['bravo', 'home', '3.33'],
['kilo', 'draw', '2.36'],
['delta', 'draw', '2.28'],
['kilo', 'away', '3.93'],
['bravo', 'away', '3.75']],
10000),
['arb', [['away', 'kilo', 2617], ['draw', 'kilo', 4358], ['home', 'delta', 3024]], 282]),
('variant scenario 1',
([['kilo', 'home', '3.59'],
['bravo', 'home', '3.20'],
['alpha', 'home', '3.30'],
['alpha', 'draw', '2.44'],
['kilo', 'draw', '2.29'],
['bravo', 'draw', '2.36'],
['delta', 'away', '3.54'],
['bravo', 'away', '3.81']],
9999),
['arb', [['away', 'bravo', 2760], ['draw', 'alpha', 4309], ['home', 'kilo', 2929]], 515]),
('variant scenario 2',
([['alpha', 'home', '3.52'], ['delta', 'away', '1.35'], ['bravo', 'away', '1.48']], 9999),
['arb', [['away', 'bravo', 7039], ['home', 'alpha', 2959]], 417])],
[('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: best price selection',
([['bravo', 'home', '2.92'],
['alpha', 'home', '3.07'],
['kilo', 'home', '3.06'],
['alpha', 'draw', '3.65'],
['delta', 'draw', '3.52'],
['delta', 'away', '2.53'],
['alpha', 'away', '2.36'],
['bravo', 'away', '2.67']],
9999),
['arb', [['away', 'bravo', 3843], ['draw', 'alpha', 2811], ['home', 'alpha', 3343]], 263]),
('variant scenario 1',
([['kilo', 'home', '2.38'],
['alpha', 'home', '2.05'],
['bravo', 'home', '2.37'],
['alpha', 'away', '1.74'],
['bravo', 'away', '1.82']],
10000),
['arb', [['away', 'bravo', 5666], ['home', 'kilo', 4333]], 313]),
('variant scenario 2',
([['delta', 'home', '4.55'],
['bravo', 'home', '4.54'],
['kilo', 'home', '4.47'],
['kilo', 'draw', '2.17'],
['delta', 'draw', '2.23'],
['bravo', 'draw', '2.19'],
['bravo', 'away', '3.24'],
['delta', 'away', '3.26'],
['kilo', 'away', '3.37']],
10000),
['arb', [['away', 'kilo', 3075], ['draw', 'delta', 4647], ['home', 'delta', 2277]], 361])]]
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-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: best price selection | ['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307] | ['arb', [['away', 'kilo', 10861], ['home', 'delta', 14138]], 307] | Passed |
| variant scenario 1 | ['no arb'] | ['no arb'] | Passed |
| variant scenario 2 | ['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495] | ['arb', [['away', 'bravo', 5494], ['home', 'kilo', 4504]], 495] | Passed |
SHA-256 / 648981d678645f154c7a9e6bc6883a050dd3b71dfc0fc659e291aca0dcfc7b5d
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 2026-09-29T14:50:32.283172+00:00.
Case digest / 119133fc895d7670ef7b1323ca6fb2ed2a596f13a3fabbe848d390b5fcbc8276