Sisyphus: The Board Game (Digital Edition)

I’m off work sick today: it’s just a cold, but it’s had a damn good go at wrecking my lungs and I feel pretty lousy. You know how when you’ve got too much of a brain-fog to trust yourself with production systems but you still want to write code (or is that just me?), so this morning I threw together a really, really stupid project which you can play online here.

Screenshot showing Sisyphus carrying a rock up a long numbered gameboard; he's on square 993 out of 1000, but (according to the rules printed below the board) he needs to land on 1000 exactly and never roll a double-1 or else he returns to the start.
It’s a board game. Well, the digital edition of one. Also, it’s not very good.

It’s inspired by a toot by Mason”Tailsteak” Williams (whom I’ve mentioned before once or twice). At first I thought I’d try to calculate the odds of winning at his proposed game, or how many times one might expect to play before winning, but I haven’t the brainpower for that in my snot-addled brain. So instead I threw together a terrible, terrible digital implementation.

Go play it if, like me, you’ve got nothing smarter that your brain can be doing today.

39 replies to Sisyphus: The Board Game (Digital Edition)

  1. By crappy napkin math, it would take an average of 143 rolls to make it to 1000. Just to roll two dice 143 times without hitting a snake-eyes is a 1.78% chance. I am too lazy to compute how many of those runs you would need to land exactly on 1000, but you’ll be at it a while…






  2. The only addition I can think of would be a reminder of the option for the player to at any time accept defeat and stop rolling it. You know, to emphasize that they’re doing this to themselves.






  3. I also ran simulations (in Perl).

    10,000 games
    Best score: 160 rolls
    Worse score: 1,029,702 rolls
    Mean score: 112,115
    Std Dev: 112,982

    Not sure why my mean & std dev are 10x higher than @digitrev’s, though my worst is also 10x higher. More games = more chances for bad games.








  4. I probably should have looked at quartiles, since the distribution has a lower limit but not an upper limit, and even a few bad runs can drive the sample mean up crazy high








  5. Only thing i would like to add is a highest score, nothing like the taunt of hope for having reached higher only to be brought low once again.





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