Arcade-Game-Stats
OpenML dataset with id 43491
No author found.
Full work available at URL: https://api.openml.org/data/v1/download/22102316/Arcade-Game-Stats.arff
Upload date: 23 March 2022
Dataset Characteristics
Number of features: 7 (numeric: 4, symbolic: 1 and in total binary: 1 )
Number of instances: 6,814
Number of instances with missing values: 0
Number of missing values: 0
Statistics on a Blockbreaker-like Game The author is in the process of creating a blockbreaker-like game, in which the jumping-off point is the "Block Breaker" section of the Udemy course, Complete C Unity Developer 2D: Learn to Code Making Games After making lots of levels, the author needed to sort them by difficulty. How does one measure the difficulty of a level? A first-cut solution is to make an auto-play bot that is not perfect, and see how well the bot does on each level, using thousands of trials. Here is a video of the game in auto-play action. Fields
Date: date and time the game was auto-played
Level: the name of the level (the 3-digit number is an estimate of the difficulty from a previous run, no longer valid after tweaking)
NumBlocks: how many blocks have to be broken to win the level
IsWin: True if autoplay broke all the blocks, False if the ball fell past the paddle.
ElapsedTime: Seconds until either won or lost (game is played at 4x speed, so multiply by 4 to get an estimate of how long a human might play it)
Score: total score when the game was won or lost
Accuracy: the autoplay is tuned with a randomly-chosen accuracy. Higher numbers are more likely to win.
This page was built for dataset: Arcade-Game-Stats
