"Variance is probably the worst enemy of the Spin & Go player."

Chapter 6: Understanding Variance in Spin & Go

This chapter is the logical follow-up to the previous one, where we began to explore the concept of variance.

Written by Gandalf, professional Spin & Go player and co-founder of Poker Sciences.

After reading the last chapter, you’re probably asking yourself the following question (and if you are, you’re absolutely right):

"Okay, I get that it’s possible to win at Spin & Go, and I understand that short-term results are meaningless.

But concretely, how many games do I need to play to guarantee that I’m winning?"

To answer that, we’re going to run some simulations.

⏪   To do this, we’ll once again use the Swongsim software. We’re going to run bankroll simulations, meaning real money wins or losses—something tangible.

We’ll simulate the bankroll of 100 good Spin & Go regulars playing at the €1 stake (with a CEV of 65 — which is very achievable at this level).

We’ll simulate sets of 200 games, then 1,000, and finally 10,000, to observe the impact of variance.

1. 100 players, each playing 200 games

Here’s the result:

100 swongsim simulations, 200 games
It might look messy (as Swongsim graphs usually do), but don’t worry — we’ll break it down clearly.

This simulation gives us the following insights:

  • 30% of players lost money after 200 games.
  • The unluckiest 5% had losses of over 20 buy-ins, while the luckiest 5% achieved gains of over 40 buy-ins.
  • On average (technically, the median), players made about 10 buy-ins in profit.

So, is 200 games enough to be sure you'll make money with a CEV of 65?

👉 NO.

2. 100 players, each playing 1,000 games

Here’s the result of this second simulation:

100 swongsim simulations, 1000 games
Yep... these graphs just keep getting messier.

This time, the insights are:

  • 10% of players still lost money — a small percentage, but still enough to cause serious doubt.
  • The luckiest players earned over 120 buy-ins.
  • The average gain was around 50 buy-ins.

So, is 1,000 games enough to guarantee profit with a CEV of 65?

👉 NO.

3. 100 players, each playing 10,000 games

Here’s the final simulation:

100 swongsim simulations, 1000 games

And the results are:

  • All 100 players ended up profitable after 10,000 games.
  • 90% of players landed between +238 and +718 buy-ins.
  • Special shout-out to the poor player who was down 226 buy-ins after their first 2,000 games (that’s the pink curve at the bottom). Remember — this is a good player. He just ran bad.

So, is 10,000 games enough to be sure you’ll make money with a CEV of 65?

👉 YES.

But note that there can still be huge gaps between theoretical and actual winnings, even among solid players.

Conclusion: A high volume of games is essential to beat variance in Spin & Go.
Icône représentant un livre ouvert avec un point d’interrogation dessus.

In summary:

In the short term, variance can completely distort your perception.

Even great players can go through downswings, especially over small samples (200 or 1,000 games).

Over larger volumes (10,000+ games), variance levels out — but large differences in profit can still occur among winning players.

Note: f you’d like to run your own simulations to estimate your potential earnings based on buy-in level, jackpot structure, volume, and CEV, we’ve written a guide on how to use Swongsim (good news: Swongsim is free!).