Weighted vs Unweighted Pipeline

Weighted pipeline is the sum of every open deal's amount times its odds of closing, which usually come from the deal's stage. Unweighted pipeline adds the same deals at full value. A $50,000 deal at a 40 percent stage counts as $20,000 weighted and $50,000 unweighted. Use unweighted for coverage and weighted for expected revenue. Updated October 2026: added the formula step by step, stage odds from win history, a worked example and the cases where weighting misleads.

What is the difference between weighted and unweighted pipeline?

Unweighted pipeline adds up every open deal at its full amount. Weighted pipeline multiplies each deal by a probability of closing before it adds them up. One tells you how much total opportunity is on the table. The other tries to estimate how much of it turns into revenue. They answer different questions, and reporting one when a decision needs the other is where teams get into trouble.

The gap between the two numbers is large. A pipeline that reads $4M unweighted might read $1.2M weighted once you apply stage probabilities. Neither number is wrong. They measure different things, and each is right for a specific job.

What is unweighted pipeline?

Unweighted pipeline is the total dollar value of every open opportunity, counted at full amount regardless of how likely each one is to close. If you have twenty open deals worth $50,000 each, your unweighted pipeline is $1,000,000. A deal in first-meeting stage counts exactly the same as a deal in final contract review.

That flatness is the point. Unweighted pipeline measures the size of the opportunity in front of the team, not the odds attached to it. It is the number behind pipeline coverage, the ratio of open pipeline to quota that most teams hold somewhere between 3x and 5x. Because it ignores probability, unweighted pipeline is stable. It moves when deals are created, closed, or resized, and not when a rep nudges a probability field.

What is weighted pipeline?

Weighted pipeline is the sum of every open deal multiplied by its probability of closing. That probability usually comes from the deal's stage or forecast category. A $50,000 deal at a stage mapped to 60 percent contributes $30,000 to weighted pipeline. The same deal at 20 percent contributes $10,000.

The goal is a single directional estimate of what the current pipeline is worth in expected revenue. Weighted pipeline leans on the idea that a deal's stage is a decent proxy for its odds, so a later-stage deal should count for more than an early one. The number is only as good as the odds you give each stage. Say 40 percent of the deals that reach Proposal go on to close, and you map Proposal to 40 percent. Then the math holds. If you map it to 80 percent because that is what hope wanted, weighted pipeline takes on the error.

How do you calculate weighted pipeline?

Multiply each open deal's amount by the odds for its stage, then add up the results. Do it one deal at a time, and only for deals whose close dates fall in the period you are measuring.

Weighted pipeline = the sum of each deal's amount times its stage odds of closing

1. Pull every open deal with a close date in the period. Leave out deals already closed won or closed lost. 2. Look up the odds for each deal's stage. Set them from your own history, as the next section shows. 3. Multiply each deal's amount by its odds. 4. Add the results. The total is your weighted pipeline.

In a spreadsheet, put the amounts in one column and the stage odds in the next. One SUMPRODUCT does the whole sum:

``` =SUMPRODUCT(C2:C7, D2:D7) ```

Two mistakes come up again and again in CRM forums. The first is a report that adds the stage percentages together, so the weighted total comes out far too high. The second is taking the average of the stage odds and applying it to the whole pipeline. The worked example below shows how far that drifts. A CRM can do the per-deal math for you once the odds are set. In HubSpot, the forecast tool's Weighted amount is "the Amount multiplied by the Deal probability", so whatever odds you set flow straight into it.

How do you set stage probabilities from your win history?

Set each stage's odds to the share of deals that reached that stage and later closed won. Measure it on deals that are finished, won or lost, over the last four to six quarters.

Illustrative: 400 finished deals from the last six quarters, 60 of them won. Every won deal passed through every stage, so each row shows the same 60 wins. The probability is wins divided by deals that reached the stage.

A few rules keep the table honest. Count only finished deals, since open deals have not had their chance to win or lose and drag every rate down. Count closed lost and no-decision deals as losses, or every rate reads high. For the full method, see CRM stage probability vs historical conversion rates.

Then hold the exit criteria fixed. Stage weights work when every stage has strict entry and exit criteria. When the stage is left to each rep's judgment, you put an objective number on a subjective call, and the quarter ends with a miss. Build separate tables for each motion, too. New business, expansion and renewal close at different rates. So do enterprise and SMB deals, and so do different products. In practice, most teams run one table for all of it. I cover both failures in why stage-weighted forecasting misses.

Worked example: the weighted pipeline math for one quarter

Here is the math on six open deals, using the stage odds from the table above. The numbers are illustrative.

Weighted pipeline is $166,000, about 38 percent of the $435,000 unweighted total. Now try the shortcut. The six stage odds average 43 percent, and 43 percent of $435,000 is $188,500. That is $22,500 too high, because the average gives the big Discovery deal the same odds as the late ones.

Set it against a $150,000 goal for the quarter. Unweighted coverage is 2.9x ($435,000 divided by $150,000). Weighted pipeline sits above the goal at $166,000. Both say this is a quarter you can make.

Then look at timing. The stage odds say how often a deal ends up won. They say nothing about when. In ORM's data, of the pipeline value carrying an in-quarter close date on day one, only about 20 percent closes in that quarter. If these six deals followed that pattern, about $87,000 would land this quarter. That is well short of the goal and of the weighted figure. ORM groups deals with machine learning and fits a close curve to each group. Those curves run from 1 to 80 weeks, with most of the expected value before week 12. A quarter is 13 weeks. So a weighted number for this quarter needs a second factor: the odds the deal closes by quarter end. A stage table does not have it.

When does weighted pipeline mislead?

Weighted pipeline misleads when the inputs under it are off: the stage, the amount, the close date, or the mix of deals. Weighting multiplies those errors. It does not catch them.

- When stages are a judgment call. If reps decide the stage without firm exit criteria, the stage odds take on their hope. - When one table covers every motion. Renewals have a known amount and a known date. In ORM's data they close within about 30 days on either side of the renewal date. New business timing follows the last stage change. One set of odds cannot fit both. - When the amounts are inflated. Most deals close for less than their CRM amount. I have seen a pipeline with an $80,000 average deal size where closed-won deals averaged $40,000. A stage weight on an inflated amount is wrong twice. See why deals close for less than the amount in your CRM. - When the pipeline is stale. Across ORM's customers, 10 percent or more of the pipeline has not been touched in 12 months. We count a deal as active only when its stage, close date or amount changes. A stale deal still carries its full stage weight. - When close dates keep moving. The best signal that a deal will slip is the rep changing its close date. A deal that slips from one quarter to the next is less likely to close, even in commit. Its stage weight stays the same. - When a few big deals carry the total. In the example, deal E adds $54,000. If it closes, the quarter gets $90,000 from E. If it slips, it gets nothing. Neither outcome is $54,000. A Monte Carlo forecast shows that range in place of one expected value.

Coverage has the same blind spot. A team can show 4x coverage and still miss badly. The pipeline can sit in the wrong stage, rest on a few large deals, or be full of stale deals and moving close dates. Weighting does not fix any of that. A machine learning forecast replaces the single stage table with odds and timing learned for each group of similar deals.

How do weighted and unweighted pipeline compare side by side?

The short version: unweighted measures capacity while weighted estimates revenue, and each carries a failure mode you have to respect.

Read the table as a division of labor. When the question is whether you have enough at-bats, unweighted is the right tool. When the question is what the pipeline is probably worth, weighted gets you closer. Problems start when the two get swapped.

When should you use unweighted pipeline?

Use unweighted pipeline whenever the question is about capacity rather than expected revenue. Coverage planning is the clearest case. The coverage ratio divides unweighted pipeline by the goal. Applying probabilities there would count the risk twice, since the ratio already builds it in. That is why the 3x coverage rule targets 3x to 5x instead of 1x. Across ORM's customers, most run near 3.5x. If you also want a coverage figure built on weighted pipeline, track it as its own ratio and set its target from your own history.

Unweighted is also the right number for pipeline-generation targets and rep workload, and for any early-stage conversation where probabilities are mostly noise. A stage-one deal's 10 percent is a placeholder, not a measurement, and weighting a top-of-funnel pipeline by those placeholders manufactures false precision. When you want a number that does not flinch every time someone edits a field, use unweighted.

When should you use weighted pipeline?

Use weighted pipeline when you need one directional revenue estimate and your stage probabilities are calibrated to reality. It is the better tool for comparing pipeline value across reps or segments that carry different stage mixes, because it corrects for the fact that one rep's pipeline might be mostly early and another's mostly late. A raw unweighted comparison flatters whoever has more open deals, quality aside.

Weighted also earns its place in an executive summary that needs a single expected-value figure next to the goal. Tie the probabilities to historical win rates by stage rather than to hope. The habit that keeps weighted pipeline honest is unglamorous. Every quarter or two, check whether each stage actually closes at the rate you have it mapped to, and re-map it when it has drifted.

Why does neither number equal a forecast?

Because both are static snapshots of the pipeline you can see today, and a real forecast has to account for the pipeline you cannot see yet. Unweighted overstates by ignoring the odds. Weighted corrects for the odds, but only through fixed stage averages that fit almost no individual deal. A 60 percent Proposal probability is an average across hundreds of deals, while the specific deal in front of you is closer to 90 percent or 15 percent.

There is a larger gap under that one. Both metrics count only deals already in the CRM. Neither models the revenue that is created and closed inside the quarter, or the deals pulled forward from a later period to save the number. Close dates make it worse. As the worked example shows, only about 20 percent of day-one pipeline dated for the quarter closes in it. The mistake I see most often is a team treating the weighted number as the forecast itself.

So use both as inputs, not answers. Unweighted tells you whether there are enough at-bats. Weighted gives you a first-pass read on revenue. A real sales forecast breaks the quarter into what will close from existing pipeline, what still has to be created and closed in-quarter, and what might be pulled forward, then attaches the risk to each path. Weighted and unweighted pipeline are two useful gauges. They were never the whole instrument panel.