Weighted Pipeline Calculator

A weighted pipeline multiplies each open deal’s amount by its estimated probability of closing won, then adds the results. It expresses the pipeline as an expected value rather than a nominal total: a 20,000 deal at 25 % contributes 5,000. Sales managers, revenue operations teams and founders use it to prepare forecasts, compare the pipeline with a remaining target and spot periods that depend on low-probability deals. It is an estimate built on probabilities, not a commitment that those amounts will be booked.

For each eligible open deal, the calculator multiplies the deal amount by its close probability (50 % counts as 0.5). It then adds these weighted amounts together. In parallel it adds the raw amounts to show the unweighted pipeline, and divides the weighted total by the unweighted total to give the implied average probability, weighted by deal value.

If you enter a forecast period, only deals whose expected close date falls inside it are counted; deals dated outside the period or without a date are excluded and counted separately, so you can see what was left out. Without a period, every listed deal is included. All amounts must be in one currency, and only open deals belong in the list: won deals are already bookings and lost deals are worth zero.

What each term means

Deal amount

Open opportunity monetary amount.

Where to find it: The amount of each open opportunity from your CRM, in one currency and on the same basis as your target (for example first-year contract value, excluding taxes). Do not list won or lost deals.

Close probability

Estimated likelihood the deal closes won; 0–100%.

Where to find it: Your estimated chance that the deal closes won, from 0 to 100. Use the stage probability configured in your CRM or a deal-level estimate, but preferably one checked against how deals at that stage actually ended. Enter 25 for 25 %.

Expected close date

Forecast date the customer decision will occur.

Where to find it: The date the customer decision is expected, as recorded on the opportunity. It is optional, but needed if you want the period filter to include the deal; a deal without a date is excluded when a period is set.

Forecast period

Period included in the forecast and quota comparison. Leave both dates empty to include every listed deal.

Where to find it: Optional start and end dates of the month, quarter or year you are forecasting. Deals with an expected close date inside these dates are counted; leave both empty to include every listed deal.

Weighted pipeline

Sum of each eligible open deal multiplied by its estimated close probability.

Hypothetical example: two open deals, one of 10,000 at a 50 % probability and one of 20,000 at 25 %, with no forecast period set.

1. Weighted pipeline10,000 × 50% + 20,000 × 25% = 10,000

Weighted pipeline = 10,000

10,000 × 50 % = 5,000 and 20,000 × 25 % = 5,000, so the weighted pipeline is 10,000 against an unweighted total of 30,000. The implied average probability is 10,000 ÷ 30,000 = 33.3 %. If the second deal moved to a 35 % probability after a successful demo, its weighted value would rise to 7,000 and the total to 12,000, while the raw pipeline would stay at 30,000. Note that neither deal will ever produce exactly 5,000: each will be won in full or lost. The weighted figure only becomes meaningful across many deals.

Hypothetical numbers, used to show the calculation. Not real company data.

Use the weighted pipeline when you need one number for what the current pipeline is likely to produce in a period, for instance to prepare a forecast call or to compare expected bookings with the remaining quota.

It is also a quick quality check. When the weighted value is a small fraction of the raw total, the pipeline is dominated by early-stage or low-confidence deals, and a large raw figure gives a false sense of security.

Applied to the same period every week, it shows whether deals are progressing (weighted value rising without new deals) or whether the total is propped up by new, early opportunities.

A raw pipeline total assumes, implicitly, that every open deal will close at its full amount. No team expects that, yet nominal figures are often discussed as if they were the likely outcome. Weighting corrects this by giving each deal a share of its value proportional to its chance of closing, so that a pipeline full of first meetings no longer looks as strong as a pipeline full of negotiations.

The quality of the weighted figure depends entirely on the probabilities. Stage probabilities, fixed percentages attached to each CRM stage, are simple and consistent, but they ignore the specifics of a deal: a competitor in the deal, an unconfirmed budget or a stalled champion. Deal-level estimates capture those specifics but invite optimism, especially from the person who owns the deal.

Whichever you use, calibrate it. Look at deals that sat at a given stage or probability in past periods and check what share of their value was eventually won. If deals labelled 50 % historically won only 30 % of their value, your weighted pipeline is overstated by the same proportion. Update the probabilities from that evidence instead of from habit, and review them per segment, because enterprise and small-business deals rarely convert alike.

The weighted pipeline is an expected value: across many deals, actual bookings should scatter around it if probabilities are well calibrated. With few deals, or one dominant deal, the real outcome will be far from it in either direction.

The implied average probability summarises how mature the pipeline is. A falling value means the mix is shifting toward early or uncertain deals, even if the raw total is growing.

Practical levers

• Calibrate stage probabilities against your own past win outcomes by value.
• Require a dated next step and an expected close date before a deal counts in the forecast period.
• Re-qualify or close out large deals with high probabilities but no recent customer activity.
• Review the deals that contribute most to the weighted total first; they carry most of the uncertainty.

Common mistakes

• Leaving won or lost deals in the list, which double-counts or inflates the total.
• Using probabilities nobody has checked against actual outcomes.
• Treating the weighted figure as committed bookings, or as recognized revenue or cash.
• Mixing currencies or contract bases (annual versus multi-year value) in the same list.
• Forgetting that undated deals are excluded once a forecast period is set.

Scenario comparison

The conservative case lowers every deal’s probability by 10 percentage points and every amount by 10 %; the optimistic case raises them by the same amounts (probabilities stay between 0 and 100). These are illustrative stress tests, not predictions.

If a 10-point shift in probabilities moves the weighted total more than a 10 % change in amounts, the forecast is more exposed to your probability assumptions than to deal sizing, which is a strong reason to calibrate them.

Probabilities are estimates. The result is only as reliable as the way they were set, and deal-level guesses tend to be optimistic.

The method treats deals as independent. In practice several deals can depend on the same budget cycle, product release or economic condition and slip together.

It does not include deals that are not yet in the pipeline. For a period forecast, combine it with won value to date, as the revenue forecast calculator does.