Investigating the long term growth of some key blockchain games

Generating market intelligence

In a previous Medium post, we considered how to use DappRadar’s new data export option to perform basic analysis on the user and volume data for a single dapp.

Now, it’s time to get a little more serious.

Instead of considering just one dapp, we’re now going to crunch the lifetime user data for seven blockchain games and see what trends we can discover.

The starting point is to head to each dapp’s DappRadar page, select lifetime data and then export the CSV file. The seven games chosen were:

Start the data crunch

The next step is to import the seven CSV files into a single spreadsheet, also creating a blank sheet for our data analysis and graphs.

Our goal is to create a single graph showing the chronological growth in users over the past 12 months, which will make it easy to see which games are growing, which games are growing fastest, and whether any games are declining.

However, because the unique daily user (technically unique daily wallet) data for each dapp is fairly volatile, if we use this raw data it can be difficult to see what’s actually going on.

This is a mess

So we’re going to remove the noise and highlight the signal by creating a smoother, averaged user data set

In order to do this, we’re going to average the daily user numbers for each dapp over the past 90 days (aka the trailing 90 day period).

Of course, this period of time — 3 months — is somewhat arbitrary. For example, if we wanted to see more granular results, we could average the data over 30 days, but for the purposes of this experiment, 90 days provides a nice, smooth curve that highlights the long term trends we’re interested in.

The difference can be seen clearly in the following graph.

Now it’s easy to see the broad trends

In terms of these five dapps — all of which run on the Ethereum blockchain — we can see that on a trailing 90 day average, CryptoKitties has steadily declined from over 400 DAUs at the start of July 2018 to just under 300.

The other four dapps have seen growth, although Axie Infinity’s upward momentum has levelled off at around 200 DAUs, similarly for HyperDragons at 400 DAUs, while Blockchain Cuties’ peaked at 530.

In that context, 0xUniverse is the only game continuing to generate growth, albeit its user base — currently 600-strong — would be considered relatively small in any sector other than the dapp market.

Adding the big guns

This scale issue is further highlighted when we add in the final two dapps.

Over our considered timescale, My Crypto Heroes has been the most popular game running on Ethereum, while EOS Knights (which runs on EOS) has been the most popular game on either Ethereum, EOS or TRON.

Obviously it’s clear My Crypto Heroes is still growing, while EOS Knights is now in decline.

Scale is everything

Yet, all such analysis comes with caveats.

The first is because we are using trailing 90 day data, we should be careful about using such graphs to discuss current activity.

For example, our 90 day user chart suggests EOS Knights remains more popular than My Crypto Heroes. But the raw data shows the two games could be about to cross over in terms of audience size at around 3,000 DAUs.

Also, by throwing away the daily noise, we’re losing granularity that would be interesting to consider if we were focused on an individual dapp. 0xUnivese, for example, demonstrates high levels of volatility.

The raw DAU data

In addition, because our goal was to look at historic data, we’ve not considered the impact of any new games. For example, HyperSnakes launched on 24 May 2019 and has already peaked at 4,000 DAUs on Ethereum and 2,000 on TRON, so a strong argument could be made that it’s now the most popular blockchain game.

Finally, there’s always the tricky issue of whether it’s legitimate to compare the performance of games running on different blockchains. This isn’t a big issue in this example as six of the seven titles use Ethereum.

Nevertheless, a game than runs on EOS (or TRON) operates very differently to one running on Ethereum and we should be careful in making strong conclusions from such comparisons.

If you want to see more details of how this data analysis was created, please check out the following video.

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