Inside the 2025 P2P Top 30

One of the things I love about a rich dataset is that it lets you test your assumptions. In peer-to-peer fundraising, we carry around a lot of assumptions about how programs work — what drives revenue, what "good" looks like, how to grow, and so forth. Some of those assumptions hold up over time, and some of them don't.

The 2025 Top 30 dataset covers 109 events from 65 organizations. Of those, 102 report participant counts, which lets us test a critical question: All things being equal, do more participants equate to more revenue?

The short answer, as you might expect, is "yes." But the longer answer is, "Yes, but it depends," and how it depends is where it gets interesting.

The chart below plots every event that reported participant data. Each dot is one event. The horizontal axis is participant count; the vertical axis is gross revenue. Bigger dots represent larger programs.

The colors represent event types: green for Walk/Run, dark green for Cycling, pink for Endurance, and blue for DIY.

Because some programs are huge, they dwarf the others in the graph. So using log transformations, we adjust the scale of the graph and make things easier to see. Click "Spread" and the relationships should become very easy to see (and conversely, click "Linear" if you want to see the raw scale before the adjustment.)  

Click the "Spread" button and watch the magic happen. See how everything goes up and to the right? That’s showing you the basic truth: the more participants you attract, the more money you raise. In fact, the differences in participants alone account for about half of the variance between all the revenue results. It's quite strong.

However, there's more to the story. Each kind of event type has different dynamics, and in some cases, you can't keep endlessly adding participants. Clicking each event type will filter the graph and allow you to see the relationships in more detail. 

The five cards across the top describe the statistical relationship between participants and revenue for each event type. "Strong, Nearly Linear" means that participant count is a reliable predictor of revenue and the relationship is nearly proportional — add people, get dollars. "Strong, Diminishing" means participant count still predicts revenue well, but with steep diminishing returns — you’d need to quadruple participants to double revenue. (The R² and β values at the bottom of each card are the underlying statistics for readers who want them.)

There is, as you would think, a positive relationship between participants and gross revenue. More people generally means more money. But the scatter is enormous. Some programs bring in tens of millions with a few thousand participants. Others have tens of thousands of participants and raise a fraction of that.

The relationship is real, but it's messy — and the messiness is the story.

Try clicking the cards to filter the chart by event type. When you look at all 102 events together, the relationship between participants and revenue is moderate. When you filter by event type, the picture sharpens dramatically. Within Walk/Run events, the relationship is strong and nearly linear. Within DIY programs, it’s almost perfectly predictable.

Again, if most of your events are clustered in the bottom-left corner and you can’t see them clearly, click “Spread” to space things out. (As noted above, this applies a log transformation that gives smaller events more room on the chart.)

What explains the variation in performance? Two things, primarily: who your participants are, and what you’re asking them to do. And that’s the next section.

Not all participants are fundraisers. In a walk event, you might have 50,000 people show up, but only a fraction of them actively raise money. In an endurance event, nearly every participant is a fundraiser. That’s the deal: you commit to a ride or a race, and you commit to raising a required minimum.

We call this percentage activation — the share of participants who actively fundraise. Activation varies wildly across event types.

Walk/Run events in the Top 30 have a median activation rate of about 39%. That means that for every 10 people who register, only four actively fundraise. Cycling events come in closer to 73%. Endurance programs are often near 89%.

This isn’t an accident. It's a function of event design.

The chart above shows the median event gross output per participant for each event type. Note, this isn’t what any individual participant raised. Rather, it’s how much total revenue each program generated for every person who showed up. In other words, it’s a measure of program efficiency. (The cards across the top show the same numbers, and the footnote below the chart explains the methodology in more detail.)

The variation is striking. DIY programs generate a median of $3,008 per participant. Walk/Run events: $275. That’s more than a 10× difference, and it’s almost entirely a function of pricing strategy and activation.

Longer, harder events can impose fundraising minimums. In other words, you can’t participate unless you raise a threshold amount. That gate guarantees higher revenue per participant but suppresses volume. Pan-Mass Challenge generates $88 million from 10,200 riders ($8,627 per participant). Making Strides generates $51 million from 931,000 walkers ($55 per participant). The activity creates the gate.

Neither model is “better.” Walk events have enormous reach; the Walk to End Alzheimer’s alone involves over 400,000 participants. Endurance events are smaller but generate more per person. They’re different strategies with different growth dynamics.

Be careful mixing the two! It’s very, very difficult to cultivate high volume with a high barrier. At the same time, a low-barrier event requires a high volume of participants to recoup the investment.

Here’s the strategic question: if your walk event is generating $275 per participant and you’re wondering how to grow, is the answer more walkers? Or is it more coaching, more tools, and more support to help the walkers you already have raise more?

The implications are significant. If you’re running a walk program, you have two levers: get more people, or activate more of the people you already have. Most programs focus almost exclusively on the first lever. The second one is often cheaper and more effective. (At More For Many, we use a proprietary scenario model to help you decide between one approach or the other, or a mixture of both.)

The organizations that consistently outperform don’t just recruit well. They empower their participants to ask. They coach them. They give them stories, tools, and confidence. That’s the difference between handing someone a fundraising page and teaching them how to use it.

Here’s what I take from all of this.

First, the relationship between participants and revenue is real, but event design profoundly shapes it. The same number of participants can produce wildly different revenue depending on what you’re asking them to do and how you support them in doing it.

Second, efficiency metrics often matter more than top-line metrics. Revenue per participant tells you more about program health than gross revenue does. A $5 million program generating $2,400 per participant may be in a fundamentally stronger position than a $20 million program generating $275 per participant — because the first one has already solved the harder problem of getting people to fundraise at a high level.

That said, acquiring one new participant who will raise $2,400 might be much harder than acquiring ten new participants who will raise $275! You have to be intentional about the approach.

Third, and most importantly: the people are the strategy. Not the platform, not the t-shirt, not the email sequence. The people.

In our Radiance P2P framework, we organize the P2P work into three phases: Design, Mobilize, and Multiply. The data in this post maps directly to the Mobilize essentials: recruit your evangelists, empower them to ask, and ignite the network. The programs that do these well show up in the efficiency metrics. The programs that skip them don’t.

We've updated this page twice since it was published, and there's still more to say. 

In the coming weeks, we'll be adding a couple more chapters to this page exploring more of what the Top 30 data reveals:

The Benchmarks We Don't See. 139 events have appeared in the Top 30 over twenty years. Only 109 remain. We’ll dig into survivorship bias, sector concentration, churn, and what the data looks like when you adjust for inflation.

Oh Canada! We’ve started with U.S. events, but our neighbors to the North (near north, here in Michigan) have gone from strength to strength. We’ll look at what’s working. 

Check back, or subscribe to our newsletter to get notified when new chapters go live.