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WORKED EXAMPLE

Closing Line Value: Calculate CLV Without Confusing It with Profit

Calculate raw and margin-adjusted closing line value with worked examples, then learn what CLV can and cannot tell you about an analysis process.

OddsTips Editorial Team6 min read

Closing line value, usually abbreviated to CLV, compares a recorded earlier price with a closing-market reference for the same selection. It helps separate the price you obtained from whether one match happened to win. There is more than one calculation called CLV, so a useful report states its formula and reference source.

Define the closing reference first

Choose the bookmaker, event, market period, line and final pre-match observation rule before looking at results. For an archive, “closing” normally means the last captured quote before the provider's cut-off. It is not necessarily the last price any user could have obtained. A record taken after kick-off cannot serve as a pre-match close.

The OddsTips guide to odds movement explains why price observations need consistent source and timing definitions. The same requirement applies to a CLV log. Missing closing quotes should remain marked as missing under a rule you chose in advance.

Calculate a raw price-ratio measure

Suppose you record decimal odds of 2.20 for a selection and the equivalent closing quote is 2.00. One simple definition is raw CLV = (earlier odds ÷ closing odds − 1) × 100. Here that gives (2.20 ÷ 2.00 − 1) × 100 = 10%.

Under this definition, your earlier quote offers 10% more gross return than the closing quote for the same winning selection. It does not mean your realised profit is 10%, your chance of winning improved by ten percentage points, or your estimated edge is automatically 10%.

The raw implied probabilities are 45.45% at 2.20 and 50% at 2.00. That is a 4.55 percentage-point difference. A chart showing probability-point changes must be labelled differently from a chart showing price ratios.

Remove margin for a probability-based benchmark

Now suppose the complete two-outcome closing market is 2.00 and 1.90, with no draw or push. Its raw probabilities are 50% and 52.6316%, totalling 102.6316%. With proportional normalisation, the first selection's closing fair-probability estimate is 0.50 ÷ 1.026316 = 48.7179%.

The corresponding fair closing price is approximately 2.0526. Against that reference, the earlier 2.20 quote has an estimated return of 2.20 × 0.487179 − 1 = 7.18% per unit staked. Equivalently, 2.20 ÷ 2.0526 − 1 gives the same result, allowing for rounding.

The raw measure was 10%; the margin-adjusted estimate is 7.18%. Neither number is a measured profit. The second calculation assumes the chosen margin-removal method produces a useful probability estimate. Our fair odds article explains that assumption and alternatives.

Keep the result in another column

If this one-unit selection wins at 2.20, its net result is +1.20 units. If it loses, the result is −1 unit. Neither outcome changes the recorded CLV. A positive-CLV selection can lose, and a negative-CLV selection can win.

Over a sample, report the number of qualifying records, missing closes, the CLV distribution and realised results separately. If stakes vary, distinguish a simple average across selections from a stake-weighted average. Otherwise one report can quietly give large and small positions the same importance.

Know where the benchmark can fail

A stale price, a lightly covered market or mismatched settlement rules can make the comparison misleading. A closing reference may contain useful later information without being a perfect estimate of the outcome probability. The quality of the benchmark needs checking across the sport and market you actually study.

Changing a handicap or total line also changes the selection. An earlier over 2.5 price cannot be divided by a closing over 3.0 price and interpreted as ordinary same-selection CLV. Pushes, quarter lines and exchange commission require calculations appropriate to their payoff rules.

Use CLV as one diagnostic in a documented research process. Pair it with consistent price comparisons, testing on later data and a clear record of assumptions. It is evidence about pricing, not a guarantee of profitable future results.

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