Why Perth drivers know exactly when to fill up their tanks

Every Monday evening in Perth, something remarkable happens. Across Australia's fourth-largest city, fuel prices spike by 15-20 pence per litre in a matter of hours. Then, over the following six days, they drift steadily downward until the pattern repeats. This isn't chaos—it's clockwork.

Perth's 2.2 million residents have unknowingly become participants in one of economics' most predictable phenomena. While drivers in Sydney wait over a month between price cycles, Perth completes the same pattern every week. The city has become a fascinating example for understanding how fuel markets really work.

This predictable rhythm reveals something about competition that challenges everything we assume about markets. More competitors doesn't always mean stable prices—sometimes it creates chaos. Albeit, profitable chaos.

The hidden pattern in fuel markets

Perth isn't unique—it's just the most visible example of something happening in cities worldwide. Large fuel retailers follow a predictable pattern called the Edgeworth cycle—essentially a financial game of chicken that plays out on every high street.

The pattern unfolds in four distinct phases. First, competitors try to undercut one another by lowering prices in an attempt to gain larger market share. This granular decrease continues because all retailers sell essentially the same product—price becomes the only real difference.

After days, weeks, or months, profit margins erode until competitors make minimal gains or even losses. No one wants to break the stalemate by raising prices first, as this puts them at a significant disadvantage. But it's beneficial for everyone if someone takes this leap.

Eventually, one competitor breaks rank and raises petrol prices to profitable levels. Others follow suit, wanting their share of better margins. Then the undercutting begins again, restarting the cycle.

This cycle plays a key role in how petrol is priced at your local stations. As a consumer, understanding it helps you find the best time to fill up. As a competitor, understanding it helps you set better prices.

The science behind the pattern

One method for understanding complex market behaviour is simulation modelling—a tool we use at Datasparq to tackle real-world problems. To demonstrate how this tool could be used, let’s create a simple simulation model to help us determine what the impact of having more competitors in a local market has on the period of the Edgeworth cycle—in essence, we want to find out how much time there is between peaks. 

In this simple simulation model, we’ll set the marginal cost at 125p and peak price at 175p for every competitor. Each competitor can only change prices once daily in 5p increments, starting from the most expensive, following identical pricing strategies. To start with we’ll consider 2 petrol stations competing over 1 month.

Here we see that the two petrol stations compete with each other to gain a larger market share, and as a result follow the Edgeworth cycle—this validates that the simulation model is working as expected. For this example we see that within 1 month there are three complete Edgeworth cycles in total.

But what happens when a third competitor enters the market?

With just one new player entering the market, we observe five complete cycles rather than three in the same period—meaning that prices change almost twice as fast. This drastic acceleration reveals a crucial insight: as more competitors enter the market, the frequency at which petrol prices oscillate increases.

While our assumptions around pricing frequency and increments are simplified, the simulation provides valuable insight into market dynamics. The next step involves iterating the model to better align with real-world data and business expertise, moving towards more robust and granular insights.

The real-world evidence

Australia provides a natural experiment for understanding Edgeworth cycles. The country's competition authority tracks petrol prices in the five largest cities, recording how long each takes to complete a full cycle:

The variation is striking. Despite similar populations, Sydney and Melbourne take over six times longer than Perth to complete the same cycle. Perth's weekly rhythm creates a clear pattern where peak prices aren't fixed—they fluctuate based on broader market conditions while maintaining the underlying cycle structure. We can see a very clear Edgeworth cycle occurring every week:

This data confirms what the simulation suggested: local market dynamics, not just global factors, drive fuel price patterns.

How to win the game

Understanding Edgeworth cycles transforms you from passive participant to informed player. As a consumer, you can track petrol prices in your local area to ensure you buy fuel at the lowest possible price. Apps like PetrolPrices.com claim average savings of £205 annually for every 1,000 litres of petrol (or £240 for diesel).

As a competitor, there are two primary strategies you can implement. 

First, monitor the petrol prices of your competitors closer and use this to create a forecasting model to predict what the petrol prices will be over time. With this you can stay on top of the trend, and ensure you are pricing at the best possible price. This process could then be automated by developing a dynamic pricing model—another thing we do at Datasparq.

Second, you could avoid the cycle altogether. To do this, find a way to differentiate your offering from your competitors’. This might involve choosing more convenient locations, creating customer loyalty programmes or adding amenities like shops or cafés to incentivise customers beyond price alone. Offer something that gives customers a reason to shop with you aside from your prices.

Beyond fuel markets

The key insight from Edgeworth cycles extends beyond fuel markets. In any market with limited competitors, no product differentiation and aggressive price competition, expect continual oscillations regardless of global conditions. This pattern can sometimes be observed in other markets—low-cost airlines being a notable example.

For businesses operating in these markets, the strategies are straightforward: monitor competitor pricing closely enough to predict cycles, or differentiate your offering to reduce price sensitivity. For consumers, track local patterns to time purchases optimally. Either way, what appears chaotic becomes manageable once you recognise the underlying structure.

Are you curious about how we could help your business? Get in touch with our team today.