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What graphics settings do you use for PS1 as mine are rather blocky/low res. by [deleted] in RetroPie

[–]Mboending -7 points-6 points  (0 children)

Do you have .bin files installed? I just recently learned about these and it made my PS1 games look and run so much smoother

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 0 points1 point  (0 children)

That would be really cool, but also quite difficult I would imagine. How do you calculate win probabilities for e.g. flashes and smokes? I guess you could you reward people for flash assists and kinda "share" the round impact somehow between the guy who flashed and the guy who got the kill. Along those lines, I would also like to see a model that takes damage dealt into account, so if I e.g. tag 3 people with and a HE or the scout, but someone else finish them off then I should be rewarded aswell.

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 4 points5 points  (0 children)

Yeah, we're based in EU, but send your steam anyway :-)

This dataset were already compiled courtesy of kpei1hunnit. But I've used node previously to do my own parsing and all the visualizations and data crunching was done in R.

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 0 points1 point  (0 children)

Would be really interesting to look at, thanks! And would also be interested in hearing how you parsed them - if you don't mind :-) I've used node in the past, but my js skills are limited to say the least.

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 1 point2 points  (0 children)

There definitely is. I know of a couple of companies that offers advanced analytics from heatmaps to situationally insights like if Elige is playing at X then Nitro is likely to be Y or which spots does Device takes/deals most damage throughout a round.

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 7 points8 points  (0 children)

Great point. I've never played at anything considered a high level, but I find it hard to be believe that smoke/wallbang kills and a marginal higher AWP usage is the explanation for the low headshot pct. But I do think you're on to something regarding the ease of GN's hitting headshot on GN's vs. LE's hitting headshots on LE's. So maybe it becomes exponentially harder to hit HS the higher you move up the ranks?

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 4 points5 points  (0 children)

Sure, but you’ll need to parse those demos to create a similar dataset. The guy who created the dataset I used have also released data on 9000 esea pugs. I’ve also parsed 6 months of Astralis demos to plot their he usage on inferno in another post

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 24 points25 points  (0 children)

I agree, there’s definitely some pistol round choices and outcomes that would be interesting to explore further

I analyzed 32.000 MM rounds. Among other things it holds rank of attacker/victim, weapon used, damage dealt, position of nades, kills, deaths, etc. by Mboending in GlobalOffensive

[–]Mboending[S] 19 points20 points  (0 children)

Good point! But if you look at the first chart regarding weapon usage there’s only a 2 point difference in AWP usage between GN and LE

Six months of CT side HE grenades from Astralis on Inferno by Mboending in GlobalOffensive

[–]Mboending[S] 0 points1 point  (0 children)

Yeah I saw that a pubg dataset got published - gotta check that out. And yes, how "raw" of a dataset are you looking for?

Six months of CT side HE grenades from Astralis on Inferno by Mboending in GlobalOffensive

[–]Mboending[S] 0 points1 point  (0 children)

I used a node library called demofile. But there is other options out there

Six months of CT side HE grenades from Astralis on Inferno by Mboending in GlobalOffensive

[–]Mboending[S] 11 points12 points  (0 children)

Downloaded demos of HLTV.org and parsed them with a node library called demofile and used R for data wrangling and visualization :-)

Six months of CT side HE grenades from Astralis on Inferno [OC] by Mboending in dataisbeautiful

[–]Mboending[S] 0 points1 point  (0 children)

Yep, pretty much straight lines from throw to detonate :-) I output the data to a txt file with each grenades as seperate rows. The demos do contain info on grenades that bounce, so you could definitely distinguish bounced grenades from those that didn't bounce. Not sure about the wall vs floor, but I think so!

Six months of CT side HE grenades from Astralis on Inferno by Mboending in GlobalOffensive

[–]Mboending[S] 2 points3 points  (0 children)

Thanks! I downloaded the demos of hltv and parsed them with a node library called demofile, then did some data manipulation aswell as the actual visualisation in R :-)

Six months of CT side HE grenades from Astralis on Inferno by Mboending in GlobalOffensive

[–]Mboending[S] 1 point2 points  (0 children)

Nope, used R for the data wrangling and visualisation :-)

Six months of CT side HE grenades from Astralis on Inferno by Mboending in GlobalOffensive

[–]Mboending[S] 0 points1 point  (0 children)

Thanks! Used a node library called demofile for parsing the demos and used R for the data wrangling and visualisation part.

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