Difficulty Level: An observation

Lately I’ve been frustrated while trying to tweak the difficulty level of my game, Project Claw. You see, the people whom I tested the game on showed varying degree of responses. Some guys are very good at playing the game that I feel like I need to introduce new challenge very often so they don’t get bored, while some other guys encountered difficulty really early in the game. Without any reliable player level that I can base on, how should I adjust the difficulty?

Fortunately I have set up some analytics in the game so I can actually measure up user’s progress level. And since the game has been released for some time in Google Play, it should have accumulated enough data to accurately reflect user’s behaviour. This data about user’s progress will hopefully shed some light on how I should adjust the difficulty level of Project Claw.

So here’s a little chart based on that progress data.
(Some absolute data have been omitted though)

User progress chart

Some explanations are in order I suppose. This chart shows the percentage of users who has reached a certain height in Project Claw (remember that the game is about going as high as possible). For example, we can see that all (100%) users has reached 0-65 m height while only 99% users managed to get past 65 m (and only 70% reached 150 m, and so on). This chart is made based on the data taken using Flurry Analytics from of a couple hundreds users who play the game in October. While I’m sure the analytics doesn’t record all users, I think the sample size is big enough that any difference with the actual data can safely be ignored.

Well, how could we understand the difficulty of Project Claw from this chart? I think it’s safe to say that the difficulty level of a game is proportional to the amount of player who reached the end of the game. So the harder a game is, the less amount of players who would reach the end of that game and vice versa. What about Project Claw then?

Well, we’ve got some really nice number on the start, 99% of the users managed to reach 65 m, which is pretty understandable, that section was designed to be a safe area with reduced falling speed where users can learn and experiment with the game mechanism. But then we got a sudden drop, only 72% of users managed to reach 150 m, apparently there’s something before that mark which some users found quite challenging.

Another sudden drop is encountered before users reached 400 m since only 38% of users managed to reach that point. This second drop is much more mysterious. The reason for the first drop can be attributed to the falling speed being restored to normal, while the second drop has none of that and only introduced new type of orbs. Of course it is possible that some users have a hard time with these new orbs.

Then we have another interesting point, apparently 80% of the users who reached 400 m also reached 800 m which is the last height level (since beyond that point the falling speed will start to increase). Based on that, I think it’s safe to assume that most users who reached 400 m has got a good grasp on how to play the game. But then again, only 30% of users has managed to get to the endgame, which I suppose is okay for a true endless game (like Temple Run), but it’s a big problem for a level-based game (which I intended Project Claw to be).

Wait, so what does all that say about the difficulty of Project Claw? Well, since the data shows that almost all users manage to pass the first section and only 30% of them reach the endgame, we can say that Project Claw is easy to understand, hard to get the hang of, and hard to master. The “hard to get the hang of” part is the problem here since casual gamers need to quickly be able to do well to be engaged with a game.

Based on all that information, there are several actions that can be done to improve user’s progress in the game (that is, adjusting the difficulty level so more users will be engaged). One of them is to expand the safe area so users would have more time to learn and master the game mechanic. This is supported by the data which shows that users who have understood what to do would progress far into the game.

Another stuff that can be done is to lower the overall difficulty, which can be achieved either by decreasing the maximum falling speed or by decreasing the gravitational acceleration. I don’t really like this option though, since I designed most stuff based on those values. Not to mention that  some movements might feel unreal if they’re slowed down too much.

I don’t know if I would do all of them, I think I will just pick one or two actions and see how it affects the progress level. I think aiming for 85% of users to reach 150 m and 50% of users to reach 400 m is a nice goal =)


One thought on “Difficulty Level: An observation

  1. Pingback: A Look Back on 2012: AdMob Edition | LegACy's Journal

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