Introduction to User Statistics

A few days ago we introduces Gamification and explained how we intended to transpose it to Prosper through User statistics. It is time to explain a little bit further what user statistics we have implemented and how we intend to use them.

Your Personal dashboard

As you might have seen already, connecting your wallet to the prediction platform now grants you access to a statistics pop-up window with two tabs.

The first tab is for your Prediction track record :

It allows you to track how many predictions you made, your ratio of wins Vs losses, and your outcomes in terms of investment. It gives you clear information of how much you predicted and how much you made / lost.

The second tabs present your Profits and Losses (PNL):

These tabs compile for you key indicators such as Net results, average participations and gains, and best round.

While all of these data remained used for your private information so far, their true power lies in how we intend to use them in the future.

Prediction Data for ladders and events

As explained previously, the goal of implementing user statistics is mainly to create more emulation between users in the form of ladders, limited time prediction speedruns, and contests. It also allows us to collect data on the platform usage, such as peak prediction times, dominant locations etc.

We can for example imagine maintaining a global prediction ranking based on volume predicted, or on win/loss ratio, and distribute weekly / monthly rewards to the first ranks.

We can even go further and create a user index combining a user’s volume stats, win/loss ratios, best rounds, and establish a ranking based on this index. We can organize multi-stage ladders with average prediction amount brackets, letting people with similar funds compete on the win/loss ratio ladder.

The possibilities are limitless as we can also restrict in time, by launching specific events, or even “seasons” like you can find in many games, reseting ladders every several months to increase participation. Last, we can organize geolocalised spot events for specific countries or places, matching a prediction event to an IRL event for example.

We will soon start introducing features and events based on stats. If you can think of any particular stats, indicator or feature linked to data, you are more than welcome to drop us a message in our Telegram chat!