The Magic of Analytics (Loc Part 8)

This stuff is sooooooo cool.

And here was the first ever graph we made! It, in essence, represents the difficulty curve of Loc. Really, it’s just the average time of our testers per level. Getting a real difficulty curve, which measures how hard it is to move all of the tiles on certain faces, potentially certain patterns that could be harder or easier would have been amazing to document as well, but we didn’t have the time.

So we stuck with average tester time to determine difficulty. In addition I was present at every one of these play sessions so often I would sit down and watch them attempt to solve a puzzle to try to pinpoint a particular weakness in certain levels.

But this data was invaluable. Nearly every two weeks I generated a new one, trying to examine the changes made from one two week cycle to another. In this method I slowly ground through the sections of the game, starting at section 1 and moving to section 6.

From the beginning I had a vision of what I wanted the difficulty curve to be. A series of small hills that go up, flatten out, dip a little, than rise back up again. Why this kind of curve? Well, I didn’t want to do an exponential one. That does not fit a puzzle game, I wanted to keep the game challenging, but not so much that the player would tire from the experience. Throwing in those easy puzzles every once in a while was a method of keeping the player engaged.

And it worked… Somehow I was right. Testers and players of the game called it addictive. “Oh, just let me finish this level.” Or, “Just one more. I think I know how to do it.” Were common compliments which justified the horrible amount of time it took to create each level.

So how close is the actual average time graph to my prediction you ask? Well here it is.