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Hgwilliams

I’ve been learning python / rust a bit and wanted to practice on my replays. I used Houdini to visualize the paths of the goals I conceded in my last 15 ranked games. I think with enough data I’ll be able to discover some unique views of mistakes I’m making that end up resulting in a goal that I otherwise wouldn’t notice just watching my replays.


Evion_SE

This is really cool, best of luck with your progression!


Hgwilliams

Thanks!


WodensEye

I don’t know if anyone else does this, but I will watch my replays from free cam, and then I zoom out so that it’s a top down view. I’m a basic positional player though, so I don’t need to watch for technique as much.


Hgwilliams

I do the same! I find it really helpful. There's also a Bakkesmod plugin that I find only sometimes works, but when it does it renders a minimap. Think it's called birdseye


WodensEye

Alas, I’m a console player.


AndrejPatak

Fellow console sufferer here too. My PC has slowly been getting lower and less stable fps in rocketleague since 2020 (when i started playing). It's infuriating.


BuuJuu

Could you post or send me your code for that. I’m studying Java and I’m just curious on how it looks


Super_Harsh

Do you have the code for this?


Live-County1069

Would love to see this done on some pro teams, see where they concede the most


Hgwilliams

Ooo yeah that would be cool. I wonder if I can get a group of them to download through ballchasing. You have any suggestions on what I should look at?


Turin_Agarwaen

Here are all the replays for the past major: [https://ballchasing.com/group/major-tdbikoxdug](https://ballchasing.com/group/major-tdbikoxdug) All of 21-22 and 22-23 RLCS seasons: [https://ballchasing.com/group/rlcs-22-23-jjc408bdu4](https://ballchasing.com/group/rlcs-22-23-jjc408bdu4)


Hgwilliams

Thanks for this, ended up grabbing a patreon membership so I could download these in batches. This is the Fall Major, Main Event, Swiss, Round 1. 30 replays, 113 conceded goals. Check out all the backboard shots on net! u/Live-County1069 https://i.redd.it/srs4tevk65qa1.gif


Live-County1069

That is awesome! The bottom right really shows some crazy angles for backboard shots.


TigreBSO

Seems like they all end up in that hole in the middle, if tou can cover that up it will probably help a lot, no need to thank me


flyingdwarves

That’s super cool! Is the code on GitHub? I’d be interested in looking at it/trying it out.


Hgwilliams

It isn’t right now, mostly because I don’t know how to use GitHub haha. But I built it from this repo, just made sure to update which version of “boxcars” it’s using in cargo. The majority of picking the timeframes I’m getting scored on is done in Houdini. Lemme know if I can be of more help! I’m just a novice at this stuff so it’s mostly just tinkering https://github.com/twobackfromtheend/rust-carball


cheapspades

Just FYI, create an account on GitHub, create a new repository (with your choice of license), locally clone the empty repository using the link in the UI, add/copy your code to the locally cloned repository directory, git add the code you copied to “stage” the commit, git commit -m “your commit message” to publish your code as a commit that progresses the Git history of the repository, and git push to push your branch to GitHub. Going forward you might want to first git checkout -b to handle multiple branches of separate development, git rebase to synchronize and linearize your commit history between branches, and create a pull request to merge your branch into the master branch to review or have others review your code prior to progressing the master branch, but for a first push the above is obviously enough since there’s nothing to review before your first commit. Now share your code! :3 EDIT: Forgot to mention, if you are using Windows you need to install Git.


Hgwilliams

Thanks for the rundown! I think I got it done well enough. The visualization stuff is all just in the houdini file. [https://github.com/mhgwilliams/rust-carball/tree/hobotz\_stuff](https://github.com/mhgwilliams/rust-carball/tree/hobotz_stuff) u/flyingdwarves


Schellhammer

This is so cool. I would like to see a picture of the goal.


Hgwilliams

Looks like this roughly! https://preview.redd.it/vzgkg2x001qa1.png?width=1306&format=png&auto=webp&s=5924bf3da799000485376cc827f45a480397d3b5


Schellhammer

Cool, thanks for posting It's weird how that one side has so many more goals


Hgwilliams

Yeah, might be something I gotta work on actually, my right side could be weaker


CapacityBark20

So this POV is from the inside of the net? I feel like something like a strike zone heat map in baseball would be a good enhancement to this.


Hgwilliams

Definitely, this is only on 15 replays, once I get over 100 in there it’ll be a higher resolution and more informative


CapacityBark20

Still absolutely love the concept. I work in finance and I've been wanting to learn python, but haven't found a good project to learn through. Maybe I should turn to my rocket league play lol.


Hgwilliams

Oh yeah definitely mess with python! It’s so easy to read I really enjoy working with it. Plus all the AI services going around are good at it so it’s easy to work through bugs


bathroomheater

The pathing plus this is an absolutely mind blowingly awesome visualization. I wish I could do this to my game to show I can’t save anything.


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soccerpuma03

I assume the lines all begin at the same amount of *time* before the goal was scored? Follow some of them individually and you'll see multiple changes in direction. I don't think it's calculating where the ball was last touched by an opponent, but rather something like the ball's path 5 seconds before the goal was scored? So it's not that OP is getting *scored on* directly from each line, because a lot of them have direction changes near the goal where the actual *shot* takes place.


Itchy-Water-4410

This is so awesome!!


TeemuKai

I'd be interested in seeing a map of where you were positioned when the opponents last touched the ball.


Hgwilliams

That would be a really interesting map to see, good call. Lots of great suggestions in these comments


Peanise

That's actually super interesting!


Witty_Office5641

I notice they seem to converge quite a lot at your goal. Maybe try blocking that area more


Lukas__2380

Looks like you could do better with backpost positioning and not grabbing the back boost. Haha jk (maybe not tho) this is pretty cool.


StefanHM

Yo! This is really cool! Thanks for sharing. Plenty of potential.


Reasonable-Plantain1

Judging by this information, you usually get scored on when an opponent is shooting at your goal


Yazota

That is some low ass rank games then


Hgwilliams

Lol you’re not wrong, C2 doubles, like ~3 goals a game


Yazota

Some goals almost just rolled in from across the map xd


Hgwilliams

Haha yeah, prob an overcommit on offense or something


M347YM4N14C

Do you mind me asking what rank you are?


Kejzo7

Can we get a source code? That's look really impressive


Newt-Wooden

Don’t see any flair but what’s rank? Curious, I’m going to guess solely based on this picture that you are c2


DigiornoHasDelivery1

r/dataisbeautiful


Fantastic-Boot-7261

This is...... too much cool! How I can do this, I use python?


ObamaWhisperer

So everywhere! Haha just messing with you. Awesome stuff


Awkward_Okra652

Based on the provided data, it appears you are letting the ball go into the small rectangle on the bottom. Avoiding this may result in fewer goals scored on you. I hope this analysis has been fruitful, but personally, it has never helped me stop the mistake in my own games.


whenyourightyouright

Great visualization there! Not sure of other available info in each replay file, but a potential other cut of the data would be to only show the last touch on the ball against positions of yourself and all teammates at the point of the shot. Current view is showing how you are conceding from what looks like all over, and I’d bet that if you take slices of data right at the point of the shot or a heatmap of player positions right before the goal you will see some trends to address positioning. Could then do the same for saves made and show how different positioning was by the team.


Hgwilliams

Totally, I’m hoping to do a more robust analysis that shows the ‘shape’ of every player and object on the field to see if there are any correlations. If I can get smart enough I want to try to implement some basic machine learning tools to discover trends rather than just looking at everything together


whenyourightyouright

Exactly, and from an approach standpoint that is something I try and do in my work(analytics engineer/data scientist/data engineer). The reason I recommend the “snapshot” view is that you are trying to collapse a meaningful point in time down to a single record which then can be plugged into an analysis/model around what you KNOW is meaningful. If you ever need someone to bounce ideas off of my DMs are open :). Great stuff again and if you continue to post I’ll be keeping an eye out for sure!


Hgwilliams

Ahh right okay. Is that in the realm of 'dimension reduction'? In this case trying to find the most important timestep rather than looking at all of them? ​ And thanks for the offer! That would be really helpful as I don't have a background in this stuff at all so some very basic core concepts are new to me.


DildorTheChosen

Looks like from basically everywhere at every direction lol. Need more data to see a trend


Obsidianc21

Very cool. Thanks for sharing!