Play to Earn Model: Bots Aren’t Your Enemy; But they’re not your friend either.

Do repost and rate:

I’m a big fan of play to earn models for games. While a play to earn model isn’t necessary, I think that any game where you could end up spending hundreds, or even thousands of dollars a year, just to remain competitive, should have a play to earn model.

For better or worse, online play to earn games draw in a lot of bots. These bots are automated programs that are coded to be able to play the game. Some do better than others, but the idea is that if they do well enough, they can earn enough to be profitable.

So bots are stealing from earnings that players could be making. Or are they? Economics says otherwise.

Connection: High Frequency Trading Algorithms

The closest analog to gaming bots is HFT algorithms. These algorithms too are often seen as negatives. A lot of people hate that HFT is a major component of modern stock markets. And yet, without HFT and day traders in general, we’d have a major problem in the market: insufficient liquidity.

Day traders, and their HFT algorithms, connect with buyers and sellers in the market, and provide the liquidity that might otherwise be lacking. They do gain a profit from the price difference, but this profit is essentially payment for the added liquidity.

However, as the percentage of trades becomes saturated by these bots, the amount of profits decreases. As profits decrease, the number of bots is reduced, because it is no longer profitable for them to be run. Thus, at least in general, the system is self-correcting.

Match Liquidity Providers

In play to earn games, where players are matched up with other players, a limited player base can mean waiting a very long time for a match. Even when the player base is larger, if there isn’t a solid distribution of skill, players can end up being paired with people who are well above their own rank and skill set.

Bots solve this issue, at least partially. Bots may be matched with other bots. However, they’re very often matched with human players. These bots perform decently, and have a moderate skill set, which makes them perfect for players who also have moderate skill sets, and maybe less than the best set of cards or monsters needed to play in the higher ranks.

And when bots are removed from the system, we start to see match liquidity problems. We start to see longer delays between match requests and match starts. We start to see more players having to compete against much higher ranked players. So removing bots isn’t necessarily a good idea.

So, just removing bots can actually hurt, rather than help. It can make the game less enjoyable for the players. As long as bots aren’t consuming too much of the profit, trying to eliminate bots might be a bad idea, even if they do eat into the total revenue generation of the game.

Player Headaches

Aside from the drop in match liquidity, players also have to suffer whenever a platform introduces anti-bot measures. Sometimes these measures are limited, but platforms often try very hard to limit or even eliminate botting.

Increasing cooldown times, locking cards that are traded between accounts, reducing payouts as a person plays more often, and many other options are used to make botting less profitable. Making a loss more painful is another common option. Since bots are more likely to lose, they’ll be coded to only play matches they can win.

But these actions also make the game more frustrating for players, and make it less profitable for players as well. The goal is to make a play to earn model that is organic and enjoyable, not one where the players have to jump through a lot of hoops or handle a lot of excess anti-botting measures.

Options

So what options are available? A platform does want to ensure that human players are getting paid to play, and that bots aren’t absorbing all of the funds. First, there are a few ways of directly handling botting.

  • Do nothing, and let the botting happen is of course the easiest option. By doing nothing, the platform is hoping that the market is self-correcting. Markets usually are. As bot farms end up competing with themselves, it becomes less profitable.
  • Official bots are another option. The platform can run a number of bots that work to out compete the bot farms. In this way, the lost revenue from botting just goes back to the platform.
  • Sponsored bots are an alternative to internally run bots. These bots could be run by fans of the platform. They would be run ethically in order to ensure that players have a good time.

The last two options can offer solutions that still allow the benefits of botting, while reducing the negatives.

Declining rewards for rapid fire play, and limiting the ability to move assets between potential dummy accounts, isn’t a terrible option for reducing botting. But again, it needs to be limited, or it will take away from the actual game play. In general, market solutions are better than technical solutions.

Additionally, because the benefits of bots are that they provide increased match liquidity, it would be best to focus on improving the matching algorithm so that bots aren’t matched with other bots, rather than focusing on eliminating botting. Developers will find ways around anti-bot measures, but would actually be happy if their bots are less likely to pair with another one of their own bots!

 

There are other solutions that I haven’t written, and probably many more that I haven’t considered. The key takeaway from this article shouldn’t be the method through which botting is addressed, but rather that the philosophy that bots are bad is wrong, and that we need to treat bots as economic agents in the game. They are a double edged sword that aren’t necessarily bad or good.

Originally published on Medium as Play to Earn Model: Bots Aren't Your Enemy

Regulation and Society adoption

Ждем новостей

Нет новых страниц

Следующая новость