Kartlytics: Applying Big Data Analytics to Mario Kart

http://www.joyent.com/blog/introducing-kartlytics-mario-kart-64-analytics

by ChrisArchitect • 13 years ago

167 33 13 years ago

mharsch• 13 years ago

This gives me the feeling that the referee guy from 'King of Kong' is about to be replaced by a very small shell script.

bcantrill• 13 years ago

Mario Kart 64 is one thing -- but if this same technique is applied to Street Fighter 2, I am honestly concerned about our Seattle office descending into civil war. Or perhaps having hard data leads to less animal struggle for dominance because the hierarchy of the herd has been quantified?

elijahwright• 13 years ago

How many sprites can SF2 possibly have? :)

incision• 13 years ago

Not sure, but any who aren't too familiar with fighters might be surprised to learn of frame data [0][1] dissection.

0: http://nki.combovideos.com/data.html

1: http://nki.combovideos.com/flame.html

CGamesPlay• 13 years ago

Really neat article and demonstrates a great way to introduce your startup's new product.

samsnelling• 13 years ago

Should note (I may have missed it in the article) the website with all of their results is http://kartlytics.com/

WestCoastJustin• 13 years ago

If you liked this, you might also like a general technique for automating NES games, with Mario Bros demo [1]. There is a video, research paper, and source code too.

[1] http://www.cs.cmu.edu/~tom7/mario/

daraul• 13 years ago

I just about lost my shit during a break here, when at the end of the video the AI actually ragequits during a game of Tetris.

laxatives• 13 years ago

Not only is it logical to rage quit a game after losing, but optimal as well.

sailfast2• 13 years ago

I can't be the only person that thinks this would also be a great idea for GoldenEye, right?

I have a lot of learning to do to make that happen, but would happily provide moral support to anyone that might want to attempt it!

dap3• 13 years ago

Absolutely! GoldenEye is a favorite here too. I haven't thought about it too much, but I bet it would be easy to adapt kartlytics to that, since it also uses a pretty straightforward on-screen display.

squozzer• 13 years ago

The answers to that game are obvious -- Oddjob and the laser.

sailfast2• 13 years ago

True - the discovery piece (which weapons work best where, trending, etc) would likely not produce revelations, but it would make for an excellent leaderboard for the extremely competitive.

the_watcher• 13 years ago

This is so cool. I'd love to see it's method's applied to other games. In college we played a lot of Super Smash Bros. 64 (same idea as SF2). At work now, Dr. Mario has shockingly become the game to master.

jlees• 13 years ago

A friend and I were thinking of doing something similar to this for Smash and League of Legends. We probably should!

saraid216• 13 years ago

From a thing I said two years ago:

"Exporting games down to stats per millisecond. Stats I'd want: all the obvious stuff, like gold, KDAs, minion kills, items: but possibly more interesting would be HP per millisecond, and any secondary stats as well. Ability cooldowns. Ward expenditure.

"Could possibly do something interesting for positioning, but I'm not sure how to express that. X,Y coords? That would be enough; it'd be hard to consume, but that's what data processing is for. Clicks and pings would also be worth dumping."

I think you could get a lot of coarse-grained positioning data from the minimap, and possibly coarse-grained HP snapshots from spectator mode. You could definitely get ultimate/summoner spell expenditures from snapshots, too.

I really do expect interesting data to come out of analyzing the spatial layout of the teams.

beambot• 13 years ago

Liquipedia needs this for StarCraft2 VODs.

jcurbo• 13 years ago

You don't even need the VODs, because a replay encodes all the information about the game already in machine readable form. I wouldn't be surprised if someone somewhere is already doing large scale analysis of available SC2 replays.

jamesaguilar• 13 years ago

We have that in League of Legends already, but the analytics that have been done so far are fairly rudimentary (who counters who, who has the highest win rate, etc.)

vutekst• 13 years ago

Prepare to be un-surprised:

http://www.ggtracker.com/

http://sc2replaystats.com/

http://www.sc2replays.eu/

https://sites.google.com/site/sc2gears/

sans-serif• 13 years ago

Yep, we have been doing this since way back in SC1. Player analytics, APM charting, heatmap, etc.

omn12• 13 years ago

Sounds like a nice proof of concept, but I would have tried to identify the in-game variables as in [0] and identify the state of the game from there. Maybe it would take a bit longer, but in the end one could track if a player is sliding or was using an item and so on. Grabbing video frames and doing some kind of template matching on the still images sounds a bit... inconvenient.

[0] http://orbitaldecay.com/N64/Lesson1/Lesson1.html

dap3• 13 years ago

Author here. That's an approach we considered as well, but we didn't want to have to use an emulator to play the game. Still, you could potentially get much richer information with that approach, and I'd love to see a demo based on it!

[Edited for detail]

omn12• 13 years ago

I know what you mean. Nevertheless, there are USB controllers which feel like the real thing. Mupen64plus behaves just like the original console so this might be a start. Here are some memory locations I found: https://sites.google.com/site/jamesskingdom/Home/video-game-...

stinky613• 13 years ago

I too was surprised that the author didn't go that route--especially considering there are hundreds of gameshark codes available to give you interesting RAM locations to monitor. There's a weight modifier code for each player which could make for some interesting analysis, also.

kylek• 13 years ago

someone hook this thing up to twitch.tv and speedrunslive!!

stdbrouw• 13 years ago

As I was looking for a non-insane alternative to Hadoop/EMR, I figured I'd check out Manta, the product they're (sort of) trying to push in the blogpost. Can't say if it scales / is fast / is cheap... but it's very developer-friendly. Couple of lines of JSON pipeline config and you're map/reducing.

retr0h• 13 years ago

I'd love to see some beard analytics...

TomAnthony• 13 years ago

This is so epic. I want the software. We have a MarioKart 64 room with bean bags at Distilled's London office and I'd die to have stats like this.

I might have to spend some money on setting this up... Thanks for sharing. :)

Kartlytics: Applying Big Data Analytics to Mario Kart

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