FA-84356 / Betting odds conversion / Open access

Decimal price of 1.00 not rejected · case 01

A 1.00 price raises a division error instead of returning invalid.

Verified by executionVariant 1 · 9 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The guard only rejects prices below 1.

THE FAILURE

The guard only rejects prices below 1.

Unsuccessful approach: Rejecting only non-positive prices still divides by zero at 1.00.

Case contract

Convert a decimal price string to an American moneyline string. Prices at or below 1 return "invalid". For d >= 2 the line is "+" followed by 100 * (d - 1); for d < 2 it is "-" followed by 100 / (d - 1). The magnitude is computed exactly from the decimal text and rounded half up to an integer. Evens (2.00) is "+100".

Why this case matters

Sportsbooks display the same price in decimal and American formats and must agree at every boundary.

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(decimal):
    d = Fraction(decimal)
    if d < 1:
        return 'invalid'
    if d >= 2:
        v = (d - 1) * 100
        sign = '+'
    else:
        v = 100 / (d - 1)
        sign = '-'
    n = math.floor(v + Fraction(1, 2))
    return sign + str(n)
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 underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('2.125',), '+113'),
  ('variant scenario 2', ('2.56',), '+156')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('0.95',), 'invalid'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('9.66',), '+866'),
  ('variant scenario 2', ('3.95',), '+295')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('2.00',), '+100'),
  ('variant scenario 2', ('1.82',), '-122')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('0.95',), 'invalid'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('8.63',), '+763'),
  ('variant scenario 2', ('1.916',), '-109')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('0.95',), 'invalid'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('1.188',), '-532'),
  ('variant scenario 2', ('3.17',), '+217')]]
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 underdog	`+150`	`+150`	Passed
control favourite	`-200`	`-200`	Passed
boundary evens	`+100`	`+100`	Passed
boundary half-cent rounds up	`+101`	`+101`	Passed
boundary no-profit price	`raised ZeroDivisionError`	`invalid`	Failed
control short favourite	`-1250`	`-1250`	Passed
regression: no profit guard	`raised ZeroDivisionError`	`invalid`	Failed
variant scenario 1	`+113`	`+113`	Passed
variant scenario 2	`+156`	`+156`	Passed

SHA-256 / 8eed7860d8dddc07be42c548be6b006a26398394524b80d775736d066981ee25

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(decimal):
    d = Fraction(decimal)
    if d <= 0:
        return 'invalid'
    if d >= 2:
        v = (d - 1) * 100
        sign = '+'
    else:
        v = 100 / (d - 1)
        sign = '-'
    n = math.floor(v + Fraction(1, 2))
    return sign + str(n)
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 underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('2.125',), '+113'),
  ('variant scenario 2', ('2.56',), '+156')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('0.95',), 'invalid'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('9.66',), '+866'),
  ('variant scenario 2', ('3.95',), '+295')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('2.00',), '+100'),
  ('variant scenario 2', ('1.82',), '-122')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('0.95',), 'invalid'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('8.63',), '+763'),
  ('variant scenario 2', ('1.916',), '-109')],
 [('control underdog', ('2.50',), '+150'),
  ('control favourite', ('1.50',), '-200'),
  ('boundary evens', ('2.00',), '+100'),
  ('boundary half-cent rounds up', ('2.005',), '+101'),
  ('boundary no-profit price', ('1.00',), 'invalid'),
  ('control short favourite', ('1.08',), '-1250'),
  ('regression: no profit guard', ('0.95',), 'invalid'),
  ('regression: no profit guard', ('1.00',), 'invalid'),
  ('variant scenario 1', ('1.188',), '-532'),
  ('variant scenario 2', ('3.17',), '+217')]]
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 underdog	`+150`	`+150`	Passed
control favourite	`-200`	`-200`	Passed
boundary evens	`+100`	`+100`	Passed
boundary half-cent rounds up	`+101`	`+101`	Passed
boundary no-profit price	`raised ZeroDivisionError`	`invalid`	Failed
control short favourite	`-1250`	`-1250`	Passed
regression: no profit guard	`raised ZeroDivisionError`	`invalid`	Failed
variant scenario 1	`+113`	`+113`	Passed
variant scenario 2	`+156`	`+156`	Passed

SHA-256 / ce21bcf20e8663c424093c89fe1bbd94b5e864e5b52250be717c3cdb047c29e1

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

This mechanism has 9 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.

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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 2026-09-29T14:50:30.056875+00:00.

Case digest / 8ce0c5159e884f9ea6526528da63ced9327296e209a1941a210083c4f14879b8