Editorial and Corrections Policy
How Learn Center content is written, labeled, reviewed, updated, and corrected when it turns out to be wrong.
Parlay Logic AI publishes people-first educational content built around exact wager language, complete outcome math, and clearly labeled assumptions. Every hypothetical example is identified as hypothetical, every worked calculation is reproducible from the numbers shown on the page, and time-sensitive claims are checked against current product rules rather than copied forward from an older draft. When a material error is found, it is corrected at the source page, the updated date is revised, and — where the error could have meaningfully changed a reader's understanding — a visible correction note is added rather than the mistake being quietly removed.
Purpose of this content
Learn Center content exists to help readers understand live betting risk and how Parlay Logic AI's math works — not to provide picks or suggest that any sporting outcome is likely or certain.
Every article should begin from a real bettor question: what does it mean for a favorite to lead while its spread bet is losing, why did a recommendation change from Watch to Actionable, what happens to a hedge when a line moves before the ticket is confirmed. From that question, the article should identify the exact market involved, explain the relevant live context in plain language, and show concretely how Hold, Watch, a specific protection mode, or a $0 recommendation affects the reader's actual financial position.
Educational pages are written to lead a reader toward informed, independent use of the product rather than to pressure them toward placing another wager. An article that only exists to justify a call to action, without teaching the reader anything they can use on their own, does not meet the bar for publication.
A direct answer belongs at the top of every section
Readers skimming under time pressure — often while a game is live — should be able to get the core answer from the first sentence of a section, then read further for the full reasoning and the math behind it.
Accuracy and exact market language
The scoreboard and the saved wager are never described as if they mean the same thing. Every example that matters to the outcome must name the market, line, odds, and stake precisely.
Sports betting language is precise for a reason: a seven-point lead and a -7 spread bet describe two different relationships to risk, and a reader who confuses them will misjudge their own exposure. Any example that depends on this distinction should name the exact market, the exact line, the exact odds, the exact stake, and — when relevant — the exact opposite market being compared against it.
| Value | Definition | Common error to avoid |
|---|---|---|
| Gross payout | Total amount returned if a wager wins, including the stake | Describing this as 'profit' |
| Net profit | Gross payout minus the original stake | Confusing with gross payout or a cash-out quote |
| Total exposure | Sum of all stakes at risk across original and protection wagers | Omitting the protection stake from the total |
| Upside sacrificed | Reduction in best-case profit caused by adding protection | Leaving this unstated in a worked example |
A cash-out offer, in particular, must never be described as profit until the original stake has been subtracted from it. A sportsbook's cash-out screen typically shows a gross figure, and an article that repeats that figure without the subtraction step is teaching a reader to overstate their own position.
Standards for worked examples and calculations
Every worked protection example must include enough detail — original stake, original price, protection price, protection stake, total exposure, and net under every covered outcome — that a reader can reproduce it with a calculator.
A worked example that cannot be checked by hand is not evidence of anything; it is a narrative dressed up as math. The editorial standard requires each example to show its inputs plainly enough that a skeptical reader can redo the arithmetic and either confirm it or flag a discrepancy.
Illustrative worked example format used across the Learn Center
Break EvenEvery figure above can be reproduced from the original stake, original decimal price, and the live opposite decimal price alone, which is the level of transparency every published example must meet.
Hypothetical example used only to demonstrate the required level of disclosure — not a specific past recommendation.
Required elements in any published worked example
- Original stake and original decimal or American price.
- Protection price and protection stake, or an explanation of why no protection qualified.
- Total exposure across both wagers.
- Net result under each explicitly covered settlement outcome.
- Upside sacrificed relative to holding the original position unprotected.
- A visible label identifying the example as hypothetical when it is not a specific documented case.
A displayed Guaranteed Profit Opportunity label carries an additional obligation: the example must satisfy the actual qualifying condition — a positive net result on every covered outcome of at least 20% of the original stake — and must state the execution and settlement limitations that apply, rather than presenting the guarantee as unconditional.
Sources and changing information
Time-sensitive external facts are checked against current, authoritative sources before publication, and internal product rules are checked against the current production methodology rather than an older draft.
Rules, sportsbook terms, product capabilities, and public data all change over time. An article that states a fact tied to a moment in time — a market's typical settlement treatment, a specific sportsbook's void policy, a feature's current behavior — is expected to identify or link its source where practical, so a reader can independently verify it rather than take the claim on faith.
Internal claims about how Parlay Logic AI itself works are held to a stricter standard. They must match the current production methodology, not a description carried over from an earlier version of the product or from marketing copy that predates a change. When the methodology changes, every dependent article is expected to be reviewed for consistency rather than left to drift.
The methodology page is the tie-breaker
Where any Learn Center article appears to disagree with the published hedge math methodology on formulas, thresholds, or rejection rules, the methodology page is treated as authoritative and the discrepancy is corrected.
AI-assisted drafting
Parlay Logic AI may use AI assistance for drafting, organization, and quality checks, but that assistance never removes the requirement to verify claims, calculations, and terminology before anything is published.
Using drafting tools is not, by itself, a departure from editorial standards. What is not acceptable is unsupported certainty, filler that adds no information, phrasing copied from elsewhere, or pages produced at volume that merely rearrange the same keywords without adding a genuine scenario or a complete calculation. Every published page is expected to contain a useful worked scenario, correct math where relevant, and a direct answer a reader can actually apply to a live decision.
- Claims about product behavior are checked against the current methodology before publication.
- Calculations are independently verified rather than trusted because they look plausible.
- Hypothetical examples are explicitly labeled as hypothetical, never presented as documented results.
- No testimonials, user counts, win rates, or performance statistics are invented or implied.
This last point is treated as a firm boundary rather than a preference. Parlay Logic AI does not publish claims about how many users it has, what results users have achieved, or any performance statistic that has not been independently verified and disclosed with its methodology. An article that needs an invented number to feel persuasive should be rewritten instead.
Corrections and updates
Material errors — arithmetic, market, settlement, or product-rule mistakes — are fixed at the source page as soon as they are confirmed, with the visible updated date revised to reflect the change.
The corrections process is designed around one principle: a reader who found an error and returns later should be able to see that it was fixed, not wonder whether the page was quietly replaced. The canonical URL for an article is preserved when the subject and search intent remain the same, so links and bookmarks continue to point to the corrected version rather than a dead page.
How a reported error moves through the process
A hypothetical walk-through of how a confirmed arithmetic error is handled end to end.
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WatchDay 0Score Report receivedLive odds N/AProtection stake N/A
What changedA reader flags a suspected arithmetic mismatch in a worked example.
Why PLA changed its callThe report includes the page URL and the specific disputed figure.
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WatchDay 1Score VerificationLive odds N/AProtection stake N/A
What changedEditorial recomputes the example from its stated inputs.
Why PLA changed its callThe error is confirmed to be material — it would change a reader's understanding of the outcome.
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ActionableDay 2Score Correction publishedLive odds N/AProtection stake N/A
What changedThe figure is corrected at the source page and the updated date is revised.
Why PLA changed its callA visible correction note is added because the original error could have changed a reader's decision.
- Fix arithmetic, market, settlement, or product-rule errors as soon as they are confirmed.
- Update the visible modification date whenever a change materially affects the answer.
- Preserve the canonical URL when the subject and search intent remain the same.
- Add a visible correction note when an earlier error could have materially changed a reader's understanding.
- Remove or redirect a page when it duplicates or contradicts a current canonical page.
Readers can report a suspected issue through the available Parlay Logic AI support channel. A useful report includes the page URL, the specific passage in question, and, where possible, the calculation or source that contradicts it. Reports that identify a genuine, material error are prioritized over general feedback about tone or presentation.
Commercial transparency
Learn Center articles may link to product features, pricing, and signup, but the educational answer must stand on its own before a reader ever reaches a call to action.
Pricing, offers, and any commercial relationship referenced in an article must be described accurately. Promotional language is not permitted to override a risk disclosure, and no article may imply that Parlay Logic AI controls sporting events, guarantees the outcome of an original wager, or ensures that every recommendation will succeed. If a call to action and a risk disclosure ever appear to be in tension on a page, the risk disclosure takes precedence in how the page is written.
If you can remove every call to action from a Learn Center article and the remaining page still teaches you something useful and correct, the article has met the editorial bar. If it does not, it needs rework, not more calls to action.
Frequently Asked Questions
How do I report an error in a Learn Center article?
Use the available Parlay Logic AI support channel and include the exact page URL, the specific passage or figure you believe is wrong, and, if possible, the calculation or source that contradicts it. Reports describing a concrete, material error — an arithmetic mistake, a misdescribed market, or an outdated product rule — are prioritized for review and correction.
Will a corrected article show that it was changed?
The visible updated date is revised whenever a change materially affects the answer on the page, and a visible correction note is added when the original error could have meaningfully changed a reader's understanding of the topic. Minor copyediting that does not change the substance of the answer does not require a correction note, but the modification date is still kept current.
Are examples in Learn Center articles real cases?
Most worked examples are explicitly labeled as hypothetical and are constructed to demonstrate a formula or a decision pattern clearly, not to describe a specific past recommendation. Where a real case is referenced, it is anonymized unless permission exists to identify the user, and it is still held to the same reproducibility standard as any hypothetical example.
Does Parlay Logic AI publish user counts, win rates, or testimonials?
No. The editorial policy treats invented or unverified testimonials, user counts, and performance statistics as a firm boundary, not a style preference. If an article would need a number like that to feel persuasive, it is rewritten to make its point using verifiable methodology and labeled hypothetical examples instead.
How does this policy relate to the hedge math methodology page?
The hedge math methodology page is the authoritative reference for every formula, threshold, and rejection rule Parlay Logic AI uses. Where any other Learn Center article appears to disagree with it, the methodology page is treated as correct and the other page is corrected under this policy, with the discrepancy disclosed if it was material.
See the formulas this policy holds every example to
Every worked example in the Learn Center is built to the same reproducibility standard defined in the hedge math methodology page.
Read the Hedge Math Methodology