Probability & Margins / THE EXPLAINER

Comparing Prices and Settlement Terms

Compare like-for-like sports markets, calculate stated fees and identify differences in periods, lines, participation and promotional return terms.

Lesson 25 – Comparing Prices and Settlement Terms

Learning goals and lesson guide

**Estimated reading time:** 7 min read.

**Level:** Intermediate. **Study time:** Allow 30–40 minutes with a comparison worksheet. **Prerequisites:** Decimal returns, expected value and market definitions. All operators, fees and terms in the examples are fictional.

Two screens show prices of 1.90 and 1.95 beside the same team. The larger number offers a larger conditional return only if the selections are genuinely comparable. One might include overtime while the other ends at regulation; one might use a different handicap or participation condition. A price comparison begins with matching the contract, not sorting the numbers.

By the end of this lesson, you should be able to build a like-for-like comparison, calculate a stated fee on winnings and identify cases where a headline price cannot be ranked without additional information. You will also practise documenting availability and avoiding retrospective selection of the best-looking historical quote.

## 1. Match the event and the question

Confirm competition, participants, date, market, period, line and settlement conditions. A tennis match-winner price with one retirement rule is not automatically equivalent to another with a different rule. A football normal-time winner is different from qualification, even when the selected club is the same.

Player markets require statistic definitions and participation conditions. A market requiring a start can behave differently from one requiring any appearance. A whole-number handicap with push terms differs from a three-way handicap with an adjusted draw.

Make a comparison key containing all those fields. If one differs, mark the row “not directly comparable” until the effect is understood. This step prevents a spreadsheet from calculating a precise ranking of mismatched products.

## 2. Compare ordinary cash returns

For identical no-fee terms and a PHP 100 hypothetical cash stake, a winning selection at 1.90 returns PHP 190 and one at 1.95 returns PHP 195. The conditional difference is PHP 5. The event's chance of occurring is not changed by selecting a larger quoted number.

The simple break-even probabilities are approximately 52.63% and 51.28%, respectively. This arithmetic describes the prices under the stated win/loss assumptions. It does not establish a true outcome probability or guarantee either selection has positive expected value.

Keep the stake constant when illustrating price differences. Comparing PHP 100 at one price with PHP 200 at another confounds the effect of the price with the amount exposed. Use net results and total returns consistently.

## 3. Incorporate a clearly defined commission

Assume a fictional product charges 5% of net winnings on a winning isolated selection and no fee on a loss. At decimal 2.10 on one unit, gross profit is 1.10. The fee is 0.055, leaving 1.045 net profit and an effective total return of 2.045.

Under that simplified rule, effective decimal return is 1 + (d − 1) × (1 − c), where c is the fee rate. This formula does not cover every exchange's market-level netting, discounts, premium charges, transaction costs or jurisdictional deductions. Use the actual charging base rather than assuming a universal fee model.

Compare a no-fee price of 2.05 with the example's 2.10 subject to 5% commission. The no-fee return of 2.05 slightly exceeds the effective 2.045. The larger raw quote did not produce the larger net return under the stated assumptions.

## 4. Push and void rules can change the comparison

Consider two fictional markets with the same team and apparent price, but one refunds a draw and the other loses on a draw. Their possible net outcomes differ. A direct decimal comparison ignores a meaningful condition.

To compare them analytically, specify probabilities for win, draw and loss and apply each product's return rules. If the probabilities are uncertain, show a sensitivity range. Do not remove a draw outcome simply because the screen displays two team names.

The same logic applies to retirements, non-participation, postponements and changed opponents. The purpose is not to find a universal best rule; it is to recognise which outcomes each contract covers. Missing terms prevent a complete comparison.

## 5. Promotional stakes need separate accounting

A free-bet token that excludes the stake from winning returns is different from an ordinary cash stake. For a hypothetical PHP 100 token at 2.50 with winnings-only return, the credited win amount is PHP 150. A PHP 100 cash stake at 2.50 returns PHP 250, including its original stake.

Do not compare these by multiplying face value by odds and ignoring the product definition. Restricted balances, wagering requirements and expiry can further change the interpretation. A promotional headline is not equivalent to unrestricted cash.

For this course, keep promotional comparisons in separate worksheets and label all terms as fictional unless verified from a current offer. Avoid suggesting that a nominally larger bonus should override a spending boundary or justify additional activity.

## 6. Availability is part of the observation

A historical price screenshot does not establish that a hypothetical stake could have been accepted. Quotes may have changed, been limited or applied to another customer or market version. Paper studies should disclose this gap rather than presenting observed prices as executed transactions.

Record source, timestamp, market state and any known restrictions relevant to comparability. If the data service supplies only periodic snapshots, the best price between snapshots is unknown. Do not fill that gap with a favourable assumption.

Similarly, comparing a morning quote from one source with a closing quote from another mixes time and provider differences. If the question is simultaneous price comparison, synchronise the observation times as closely as the data permit and state the tolerance.

## 7. Rounding can matter near a narrow difference

Carry adequate precision through working calculations and round final displayed results consistently. A net-return difference of 0.005 units can disappear or change appearance under coarse rounding. Do not describe a tiny difference as practically decisive without considering measurement and probability uncertainty.

For a PHP 100 example, effective odds of 2.045 imply a PHP 204.50 total return before any product-specific rounding rule. Whether an actual system rounds at the selection, market or account level depends on its terms. Use the confirmed rule when exact settlement is the task.

The educational conclusion should distinguish arithmetic precision from evidence quality. Calculating six decimal places does not compensate for an unverified retirement condition or an uncertain price timestamp.

## 8. Build a comparison table

Use one row per source and columns for event, market, period, line, special rules, timestamp, raw price, fee basis, effective return and unresolved issues. Add a final comparable/not-comparable flag before ranking anything.

For an invented example, Source A offers 1.95 with overtime included, Source B offers 2.00 regulation-only and Source C offers 1.98 with overtime included and no fees. A and C are comparable if the remaining terms match; B is a different proposition. You cannot simply rank B first because 2.00 is the largest number.

Then add Source D at 2.00 including overtime with a 5% fee on isolated net winnings. Its effective return is 1.95, matching A under these simplified conditions. State the fee assumption prominently so the comparison can be reproduced.

## 9. Practice questions and answers

1. What is the return difference between 1.85 and 1.92 on a winning PHP 100 cash stake with identical no-fee terms? 2. What effective decimal return results from 2.20 with 5% commission on net winnings only? 3. Can regulation-only and overtime-inclusive prices be directly ranked as identical products? 4. Why must a paper study distinguish observed from accepted prices? 5. Does a winnings-only token return its face value under that stated rule? 6. What should happen when participation conditions are missing? 7. Does greater arithmetic precision resolve missing settlement terms?

### Answer key

1. PHP 7 in conditional return: PHP 192 minus PHP 185. 2. 1 + 1.20 × 0.95 = 2.14. 3. No. They cover different event periods and possible outcomes. 4. Observation does not establish actual availability, limits or acceptance. 5. No. Only the defined winnings are credited in that example. 6. Mark the comparison incomplete or not directly comparable until the relevant rule is known. 7. No. Precision in calculation is different from completeness of evidence.

## 10. Completion check

Produce a three-source fictional comparison in which at least one row is excluded for a documented mismatch. Calculate net returns for the comparable rows and explain every fee assumption. A justified exclusion is an analytical success; forcing unlike products into one ranking is not.

Review [returns](https://betting.crazywingo.ph/article/read-betting-odds-calculate-payouts), [market types](https://betting.crazywingo.ph/article/moneyline-spread-total-parlay-beginners), [probability](https://betting.crazywingo.ph/article/implied-probability-bookmaker-margins-beginners), [market identification](https://betting.crazywingo.ph/article/sports-betting-basics-for-beginners) and [budget boundaries](https://betting.crazywingo.ph/article/betting-budget-limits-avoid-chasing-losses) as needed. The next lessons apply disciplined research to individual sports.