Analyzing sports teams like SaaS companies

A new way for sports teams to measure success

Samir Javer
8 min readJan 18, 2022

While most consumers relate to sports teams merely as fans, sports franchises are businesses at the end of the day. Businesses that seek to make customers happy, make shareholders happy, and make a profit.

I recently saw a tweet showing how NHL franchise valuations have changed over time. Amazingly, every single franchise has increased in value annually since 2014 — even in 2020, despite a global pandemic that saw no sports!

This is primarily because the revenue multiple that these teams are valued at has been increasing over time, most notably in the NBA:

Seeing these charts reminded me of big tech companies, most of whom’s valuations also tend to increase over time, due to their high growth potential.

It was then that I realized: when you think about it, sports teams are kind of like SaaS (software-as-a-service) companies.

They acquire customers (fans), who pay them revenue (tickets & merchandise), and they try to retain these fans for life.

Heck, they even offer subscriptions (season tickets), sell their product (tickets) at different pricing tiers, and are seasonal in nature.

Traditionally, sports franchises have measured themselves on two key metrics:

  • Franchise valuations
  • Revenue

Sounds similar to SaaS companies, doesn’t it?

But while those metrics are useful, and can depict the health of a business, I don’t think they paint the whole picture.

In fact, they can often be misleading; when COVID-19 hit, teams’ revenue plummeted as games were cancelled or played without fans in the stands.

But does that mean those franchises weren’t “healthy” businesses? On their income statements, sure — but not in the big picture, I argue.

The big picture needs to take into account the engagement of their customers — their fans — and how likely they are to spend and retain over time.

In this post, I’ll propose a set of new metrics that sports teams can measure themselves by, drawing parallels to metrics commonly used in the SaaS industry.


Let’s start with revenue, since it’s a metric already used by sports teams. Here, I’ll focus on revenue acquired from end users (fans), rather than sponsorships.

Total revenue is a great metric, but here’s the problem: much like SaaS customers, the amount of revenue that each sports fan contributes to a team varies wildly.

Die-hards may spend thousands of dollars a year on season tickets, while a casual fan might only spend $100 on a jersey or a single-game ticket.

Sports teams always want their fans to spend more on their teams; it’s why they always offer bundles and discounts.

So, what if there was a way to measure how much revenue an individual fan was contributing every year?

Well, we can use Average Revenue Per User, or ARPU:

The way to calculate this for a sports team would be: total $ revenue from fans (tickets, merchandise, concessions, etc.) ÷ unique # of fans.

This could be broken down even further to a per-game level; teams could measure ARPU by how much revenue they made from a home game, and divide that by the number of fans in attendance.

For example, it’s reported that a Toronto Maple Leafs home game nets $2 million in revenue. Scotiabank Arena, where they play, seats 19,800 fans — and is always sold out.

So, if we divide the two figures, we can conclude that the ARPU for a Leafs home game is $101.

ARPU could be used as a way to benchmark the willingness to pay of fans, and would be a valuable comparison tool for teams and leagues.

Customer acquisition

Just like any other business, sports teams spend a significant portion of their marketing budget to acquire new customers (fans).

Those may be existing fans who become first-time ticket buyers, or net new fans who develop an interest in the team.

And just like SaaS companies, their goal is for these customers to stick around long-term.

SaaS companies like to measure not only how much it costs to acquire a customer (CAC), but how long it’ll take to pay back that cost, via the revenue they receive from that new customer.

For example, if a team knows it costs roughly $75 to acquire a new fan, they could calculate how much revenue they’d have to earn from that fan over time (or how long they’d have to retain them), in order for it to be profitable.

This is referred to as the ‘CAC payback period’ in SaaS:

Once that fan has ‘signed up’, the team could make efforts to recoup that CAC by offering that fan a discounted game ticket, or a sale price on a jersey. This is not dissimilar from how SaaS companies often offer new users discounts or promotions, to incentivize long-term usage.


Retention is the bread and butter of SaaS companies. It doesn’t matter how many users you have; if they’re not sticking around, you’re just a leaky bucket.

I think it’d be fascinating for sports teams to measure the retention of their fans.

Much like businesses, if sports teams have no fans, their business will die. And fan engagement is tied directly to team performance. And fans can talk the talk with not just their voices, but their wallets too.

For example, teams could measure what % of their fans watch every single game — as opposed to, say, one game a week.

In SaaS, this is referred to as the DAU/WAU ratio, which measures the ratio of daily active users to weekly active users. The higher the ratio, the more days in a week users are using your product — and the more likely they are to stick around. It’s a leading indicator of long-term retention, essentially.

DAU/WAU ratios for popular tech products.

In addition, teams could measure retention for new fans specifically — for example, what % of fans are retained (still watching games) after going to their first-ever game?

If this sounds familiar, it’s kind of like a cohort analysis in SaaS products, where Day 0 is the ‘signup’ date:

Taking it a step further, teams could segment their fan bases by various attributes — age, gender, occupation, etc. Again, much like SaaS companies do!

This would allow them to identify opportunities to boost retention and engagement for particular segments, based on their unique pain points.

For example, if a team saw that the retention of students was low because they can’t always watch games due to their hectic schedules (but consume lots of video asynchronously), a team could lean into engagement tactics that cater to them, like posting game highlights on TikTok.

They could then measure retention by segments; e.g. students who watched game highlights on TikTok vs those who didn’t:

Repeating this process over and over for their various segments would ultimately enable teams to keep their fans engaged long term, no matter their constraints. And this would translate to more revenue, and higher valuations.

You could imagine all these retention curves moving up or down over time, too, based on the real-life events of the team. If the team hires a new coach or makes a big trade to improve the team, retention may increase. But if they sell off their players at the trade deadline or hire a coach with a boring style of play, retention may decrease.

Teams already pay close attention to this sort of fan sentiment via social listening, surveys, etc., so presumably they’d want to see this reflected in a more quantitative way. That’s the beauty of measuring retention.


The opposite of retention is churn — when a customer leaves, and thus stops paying you.

Here’s the interesting thing about sports: fans often say they’ll stop cheering for a team (AKA, churn) if they don’t start winning soon, or don’t make a major personnel change, but how much of that is just talk?

Teams could quantify this ‘threat’ by measuring churn.

They could look at it over a monthly, yearly, or even multi-year time frame. It would allow them to gauge the business impact of personnel changes and team performance — with real numbers, not just ‘fan sentiment’.

If the owner of a franchise saw that, say, 5% of their fans were churning on a monthly basis due to poor results, that may spark them to take action on firing a GM or coach, rather than simply ‘waiting it out’ — as teams often do.

Finally, teams could measure the resurrection of ‘churned’ fans; fans who used to watch their team, but have stopped following them. While life circumstances may be a cause here, it’s often poor team performance that makes fans cut ties with their teams.

If a team was a bottom-dweller for years but is now on the upswing, teams could re-engage those fans through win-back campaigns (and offer discounts to entice them), and measure the re-activation rate.

The goal, just like SaaS companies, should be to have net negative churn — AKA churn that is less than zero.

The power of negative churn.

In conclusion, here’s why I believe sports teams should measure themselves like SaaS companies:

  • It’d allow them to calculate how much revenue each fan contributes, as a benchmark for willingness to pay
  • It’d help them profitably acquire new customers (and keep them retained) by measuring their CAC payback period
  • It’d identify opportunities to boost retention for particular fan segments
  • It’d allow them to re-engage fans who used to follow their team

This is a series of blog posts on my observations from the tech industry and product management. I’m on Twitter at @samir_javer! 👋