FA-84701 / Betting odds conversion / Open access

Cash-out margin applied as a flat or grossed-up deduction · case 01

Offers differ from the stated percentage deduction.

Verified by executionVariant 1 · 10 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The margin percentage is subtracted as cents.

VERIFIED REPAIR

Multiply the value by (100 - margin) / 100.

Unsuccessful approach: Dividing by 1 + margin grosses the value down by a different amount.

Case contract

Cash-out offer for a single or multiple back bet. legs rows are [price taken, current] where current is a decimal price for an open leg, "won" or "lost". Any lost leg makes the offer [0, 0]. Otherwise value = stake * product of prices taken / product of current prices of open legs, reduced by margin_pct percent, rounded down to a cent. partial_cents 0 means full cash-out: return [value, 0]. A partial amount above the value returns "invalid"; otherwise return [partial, remaining stake] with remaining = floor(stake * (1 - partial / value)).

Why this case matters

Cash-out and partial cash-out offers are recomputed from live prices on every tick.

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, stake_cents, margin_pct, partial_cents):
    value = Fraction(stake_cents)
    for price, cur in legs:
        if cur == 'lost':
            return [0, 0]
        value *= Fraction(price)
        if cur != 'won':
            value /= Fraction(cur)
    value = value - Fraction(margin_pct)
    full = math.floor(value)
    if partial_cents == 0:
        return [full, 0]
    if partial_cents > full:
        return 'invalid'
    remaining = math.floor(stake_cents * (1 - Fraction(partial_cents, full)))
    return [partial_cents, remaining]
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 single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['3.98', 'won'], ['3.24', 'won'], ['2.39', '4.03'], ['2.04', 'won']], 500, '5', 500),
   [500, 466]),
  ('regression: margin application',
   ([['3.31', '5.65'], ['4.82', '5.34']], 2500, '5', 0),
   [1255, 0]),
  ('variant scenario 1',
   ([['2.61', 'won'], ['2.54', '3.04'], ['4.36', 'won'], ['3.63', '5.65']], 2500, '0', 500),
   [500, 2418]),
  ('variant scenario 2', ([['2.56', 'lost']], 500, '7.5', 800), [0, 0])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application', ([['4.31', '1.48']], 500, '5', 500), [500, 319]),
  ('regression: margin application', ([['2.56', '3.02']], 1000, '5', 0), [805, 0]),
  ('variant scenario 1',
   ([['3.54', 'won'], ['4.17', '2.42'], ['3.80', 'won'], ['3.99', 'lost']], 500, '7.5', 200),
   [0, 0]),
  ('variant scenario 2', ([['2.56', 'won']], 2500, '0', 200), [200, 2421])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['1.77', '5.47'], ['4.57', 'won'], ['4.63', 'won'], ['4.20', 'won']], 1000, '5', 200),
   [200, 992]),
  ('regression: margin application', ([['4.21', 'won']], 500, '5', 0), [1999, 0]),
  ('variant scenario 1',
   ([['4.24', 'lost'], ['4.73', '5.96'], ['3.59', 'won']], 1000, '7.5', 0),
   [0, 0]),
  ('variant scenario 2', ([['4.94', '1.31'], ['2.71', '5.06']], 1000, '0', 800), [800, 603])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application', ([['1.66', '3.53']], 2500, '5', 200), [200, 2051]),
  ('variant scenario 1', ([['1.54', 'won'], ['3.01', '3.82']], 1000, '0', 500), [500, 587]),
  ('variant scenario 2', ([['3.86', '5.37']], 500, '7.5', 0), [332, 0])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['4.64', '5.35'], ['4.09', 'won'], ['4.50', '2.09']], 1000, '7.5', 0),
   [7064, 0]),
  ('variant scenario 1',
   ([['2.22', 'lost'], ['2.66', 'won'], ['4.77', '1.58'], ['3.17', 'lost']], 2500, '5', 200),
   [0, 0]),
  ('variant scenario 2',
   ([['4.16', '1.91'], ['4.67', '5.15'], ['2.46', '4.20'], ['3.13', '3.40']], 500, '0', 0),
   [532, 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 single shortened	`[1500, 0]`	`[1500, 0]`	Passed
control margin applied	`[1495, 0]`	`[1425, 0]`	Failed
boundary won leg keeps price	`[2666, 0]`	`[2666, 0]`	Passed
boundary partial cash out	`[500, 666]`	`[500, 666]`	Passed
control lost leg	`[0, 0]`	`[0, 0]`	Passed
boundary partial above value	`invalid`	`invalid`	Passed
regression: margin application	`[500, 467]`	`[500, 466]`	Failed
regression: margin application	`[1316, 0]`	`[1255, 0]`	Failed
variant scenario 1	`[500, 2418]`	`[500, 2418]`	Passed
variant scenario 2	`[0, 0]`	`[0, 0]`	Passed

SHA-256 / 71a75b8a4edb3fdee6fd9ca2bf8fc9f550de25e5f7d4293c1e9aaa29d8f6eecd

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, stake_cents, margin_pct, partial_cents):
    value = Fraction(stake_cents)
    for price, cur in legs:
        if cur == 'lost':
            return [0, 0]
        value *= Fraction(price)
        if cur != 'won':
            value /= Fraction(cur)
    value = value / (1 + Fraction(margin_pct) / 100)
    full = math.floor(value)
    if partial_cents == 0:
        return [full, 0]
    if partial_cents > full:
        return 'invalid'
    remaining = math.floor(stake_cents * (1 - Fraction(partial_cents, full)))
    return [partial_cents, remaining]
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 single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['3.98', 'won'], ['3.24', 'won'], ['2.39', '4.03'], ['2.04', 'won']], 500, '5', 500),
   [500, 466]),
  ('regression: margin application',
   ([['3.31', '5.65'], ['4.82', '5.34']], 2500, '5', 0),
   [1255, 0]),
  ('variant scenario 1',
   ([['2.61', 'won'], ['2.54', '3.04'], ['4.36', 'won'], ['3.63', '5.65']], 2500, '0', 500),
   [500, 2418]),
  ('variant scenario 2', ([['2.56', 'lost']], 500, '7.5', 800), [0, 0])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application', ([['4.31', '1.48']], 500, '5', 500), [500, 319]),
  ('regression: margin application', ([['2.56', '3.02']], 1000, '5', 0), [805, 0]),
  ('variant scenario 1',
   ([['3.54', 'won'], ['4.17', '2.42'], ['3.80', 'won'], ['3.99', 'lost']], 500, '7.5', 200),
   [0, 0]),
  ('variant scenario 2', ([['2.56', 'won']], 2500, '0', 200), [200, 2421])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['1.77', '5.47'], ['4.57', 'won'], ['4.63', 'won'], ['4.20', 'won']], 1000, '5', 200),
   [200, 992]),
  ('regression: margin application', ([['4.21', 'won']], 500, '5', 0), [1999, 0]),
  ('variant scenario 1',
   ([['4.24', 'lost'], ['4.73', '5.96'], ['3.59', 'won']], 1000, '7.5', 0),
   [0, 0]),
  ('variant scenario 2', ([['4.94', '1.31'], ['2.71', '5.06']], 1000, '0', 800), [800, 603])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application', ([['1.66', '3.53']], 2500, '5', 200), [200, 2051]),
  ('variant scenario 1', ([['1.54', 'won'], ['3.01', '3.82']], 1000, '0', 500), [500, 587]),
  ('variant scenario 2', ([['3.86', '5.37']], 500, '7.5', 0), [332, 0])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['4.64', '5.35'], ['4.09', 'won'], ['4.50', '2.09']], 1000, '7.5', 0),
   [7064, 0]),
  ('variant scenario 1',
   ([['2.22', 'lost'], ['2.66', 'won'], ['4.77', '1.58'], ['3.17', 'lost']], 2500, '5', 200),
   [0, 0]),
  ('variant scenario 2',
   ([['4.16', '1.91'], ['4.67', '5.15'], ['2.46', '4.20'], ['3.13', '3.40']], 500, '0', 0),
   [532, 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 single shortened	`[1500, 0]`	`[1500, 0]`	Passed
control margin applied	`[1428, 0]`	`[1425, 0]`	Failed
boundary won leg keeps price	`[2666, 0]`	`[2666, 0]`	Passed
boundary partial cash out	`[500, 666]`	`[500, 666]`	Passed
control lost leg	`[0, 0]`	`[0, 0]`	Passed
boundary partial above value	`invalid`	`invalid`	Passed
regression: margin application	`[500, 466]`	`[500, 466]`	Passed
regression: margin application	`[1259, 0]`	`[1255, 0]`	Failed
variant scenario 1	`[500, 2418]`	`[500, 2418]`	Passed
variant scenario 2	`[0, 0]`	`[0, 0]`	Passed

SHA-256 / 96955c2159ecadf95f0f0500bf2d38b06339ed0012197c42198a5b00bd142b33

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, stake_cents, margin_pct, partial_cents):
    value = Fraction(stake_cents)
    for price, cur in legs:
        if cur == 'lost':
            return [0, 0]
        value *= Fraction(price)
        if cur != 'won':
            value /= Fraction(cur)
    value = value * (100 - Fraction(margin_pct)) / 100
    full = math.floor(value)
    if partial_cents == 0:
        return [full, 0]
    if partial_cents > full:
        return 'invalid'
    remaining = math.floor(stake_cents * (1 - Fraction(partial_cents, full)))
    return [partial_cents, remaining]
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 single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['3.98', 'won'], ['3.24', 'won'], ['2.39', '4.03'], ['2.04', 'won']], 500, '5', 500),
   [500, 466]),
  ('regression: margin application',
   ([['3.31', '5.65'], ['4.82', '5.34']], 2500, '5', 0),
   [1255, 0]),
  ('variant scenario 1',
   ([['2.61', 'won'], ['2.54', '3.04'], ['4.36', 'won'], ['3.63', '5.65']], 2500, '0', 500),
   [500, 2418]),
  ('variant scenario 2', ([['2.56', 'lost']], 500, '7.5', 800), [0, 0])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application', ([['4.31', '1.48']], 500, '5', 500), [500, 319]),
  ('regression: margin application', ([['2.56', '3.02']], 1000, '5', 0), [805, 0]),
  ('variant scenario 1',
   ([['3.54', 'won'], ['4.17', '2.42'], ['3.80', 'won'], ['3.99', 'lost']], 500, '7.5', 200),
   [0, 0]),
  ('variant scenario 2', ([['2.56', 'won']], 2500, '0', 200), [200, 2421])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['1.77', '5.47'], ['4.57', 'won'], ['4.63', 'won'], ['4.20', 'won']], 1000, '5', 200),
   [200, 992]),
  ('regression: margin application', ([['4.21', 'won']], 500, '5', 0), [1999, 0]),
  ('variant scenario 1',
   ([['4.24', 'lost'], ['4.73', '5.96'], ['3.59', 'won']], 1000, '7.5', 0),
   [0, 0]),
  ('variant scenario 2', ([['4.94', '1.31'], ['2.71', '5.06']], 1000, '0', 800), [800, 603])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application', ([['1.66', '3.53']], 2500, '5', 200), [200, 2051]),
  ('variant scenario 1', ([['1.54', 'won'], ['3.01', '3.82']], 1000, '0', 500), [500, 587]),
  ('variant scenario 2', ([['3.86', '5.37']], 500, '7.5', 0), [332, 0])],
 [('control single shortened', ([['3.00', '2.00']], 1000, '0', 0), [1500, 0]),
  ('control margin applied', ([['3.00', '2.00']], 1000, '5', 0), [1425, 0]),
  ('boundary won leg keeps price', ([['2.00', 'won'], ['2.00', '1.50']], 1000, '0', 0), [2666, 0]),
  ('boundary partial cash out', ([['3.00', '2.00']], 1000, '0', 500), [500, 666]),
  ('control lost leg', ([['2.00', 'lost'], ['2.00', '1.50']], 1000, '0', 0), [0, 0]),
  ('boundary partial above value', ([['2.00', '4.00']], 1000, '0', 600), 'invalid'),
  ('regression: margin application',
   ([['4.64', '5.35'], ['4.09', 'won'], ['4.50', '2.09']], 1000, '7.5', 0),
   [7064, 0]),
  ('variant scenario 1',
   ([['2.22', 'lost'], ['2.66', 'won'], ['4.77', '1.58'], ['3.17', 'lost']], 2500, '5', 200),
   [0, 0]),
  ('variant scenario 2',
   ([['4.16', '1.91'], ['4.67', '5.15'], ['2.46', '4.20'], ['3.13', '3.40']], 500, '0', 0),
   [532, 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 single shortened	`[1500, 0]`	`[1500, 0]`	Passed
control margin applied	`[1425, 0]`	`[1425, 0]`	Passed
boundary won leg keeps price	`[2666, 0]`	`[2666, 0]`	Passed
boundary partial cash out	`[500, 666]`	`[500, 666]`	Passed
control lost leg	`[0, 0]`	`[0, 0]`	Passed
boundary partial above value	`invalid`	`invalid`	Passed
regression: margin application	`[500, 466]`	`[500, 466]`	Passed
regression: margin application	`[1255, 0]`	`[1255, 0]`	Passed
variant scenario 1	`[500, 2418]`	`[500, 2418]`	Passed
variant scenario 2	`[0, 0]`	`[0, 0]`	Passed

SHA-256 / 2bf84c26555309e433fce3ebff48f01cd3388a61e374039d71dc4cf386975df1

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 2026-09-29T14:50:33.401964+00:00.

Case digest / c9550f9ace298f4405bba44fdeb0b6afb12841530b6b77c9da1860328b71e903