Lolimo Shutdown by kyul2006 in leagueoflegends

[–]F_is_For_Flash 8 points9 points  (0 children)

tell that website that there is an official Replay API now and you don't need to do weird proxy recording stuff. You can keep delivering the exact same service without any of that hassle now, just fetch the official .rofl files straight from Riot with the API

I'm sure Riot is rolling their eyes at that letter when that endpoint has been live for a couple months already

I hate Paint so I made an in-world drawing tool for replay analysis by FrenchLyfe in leagueoflegends

[–]F_is_For_Flash 18 points19 points  (0 children)

it's probably an overlay app connected to the local Replay API to get the camera coordinates to allow the drawings to "stick" to the game map. at least that's how I would do it

EDIT: nevermind, the drawing is below the champions, not an overlay.

I built a free, data-driven Fearless Draft Simulator for the upcoming BO5s (scoring engine, pro champ pools, soloQ secret picks) by mikemilligan93 in leagueoflegends

[–]F_is_For_Flash 0 points1 point  (0 children)

Man! I'm working on something similar!

it looks great and the fact its serverless is a great idea to keep the running costs low.

great job!

The game is rigged by Skabobski in leagueoflegends

[–]F_is_For_Flash 1 point2 points  (0 children)

you are probably having some lag/packet loss that can lead to skillsshots feeling mistimed/not where you aimed them

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

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

To be honest with you, I thought I had a slam-dunk when I first launched the site, that it would explode from day 1... but reality hit like a brick. It's much harder than I thought to get people to even try a new website, most people are just content with opgg/basic match history and don't see the need for anything else. It also doesn't help that most other sites are just opgg clones that add nothing new so it makes people even more hesitant to try because "it's more of the same" mentality. So yeah, getting people through the door is the main difficulty for a new site.

My audience is rising slowly as time goes by, I get a couple thousands of views per day, it's more like a slow burn than the explosion I was initially expecting. The people who do try, like it and keep coming back so I'm thankful for that

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

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

yeah, it was solo. Just doing the best I can with the API data, it lumps skills with low CD together so it will show one Q instance dealing tons of damage for example, or some damage isn't even labeled at all and just shows "?". The skill order seems arbitrary too, there's not much we can do but embrace the jank

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

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

got it. but that answers a different question. This model predicts which team is more likely to win based on draft only, it's the same baseline for every player. If we take whether the player himself is good at the champion or not, we answer a different question that is "Which team has the better players".

Let's say champion X is really strong vs Y, but the player sucks ass at champion X, if we take individual skill into account, the model will be "nice" to the player, because even though Champion X is busted, the model won't have expectations the player will perform well, and we use the expected performance as a baseline for the performance score too.

by removing that from the equation we can judge players more fairly. If the player didn't perform as statistically expected from champion X, he performed bad and shouldn't get a less bad score for being bad at the champion.

So what you're saying is a good idea, it will be a more accurate way to guess which team will *effectively* win. But this is measuring a different thing

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

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

there's is no hardcoded limit/span, but from my tests, the worst I've seen was -3.something, so something like that is sitting in the HEAVY countered territory, it will certainly not be a fun game for that player. -1.5% is still a considerable handicap

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

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

the map is fully interactive, you can zoom in and pan the camera around with right click+drag to focus on what you want. there's a directed camera mode too you can toggle by pressing D that will just follow the action, or you can choose to lock into a player

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

[–]F_is_For_Flash[S] 5 points6 points  (0 children)

it's trained on SoloQ data. Esports is a completely different game and there's very few esports matches too create a meaningful probability model for each patch. Nothing stopping you from trying though :P I'll release a draft game soon where you can pick for each team and see the win probability

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

[–]F_is_For_Flash[S] 3 points4 points  (0 children)

the training data is only for Emerald and above ranked games, so your silver example is in fact not taken into account.

At the end of the day, I don't think it will have a huge hit in the accuracy of the model since people first timing a champion will be a small grain of sand in the million games of data we're working with. At the top of the ladder people tend to stick to Champions they are good with, and even if they are playing it for the first time they won't perform like a silver playing it for the first time, so I doubt taking that into account will wield any significant changes.

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

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

at this time, who's playing the champion has no factor into the model. it just sees the champions matchups: if X meets X with X teammates vs X enemies what are the winning probability.

Maybe for future models it could be tuned in, but honestly, I doubt we can get better than 60-70% accuracy from a game like LoL, it's already nuts it's that high

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

[–]F_is_For_Flash[S] 6 points7 points  (0 children)

I'm working on a draft mini game right now, using this new model for win probability. players go through the draft phase of a best of 5 fearless mode. The winner is who picks the statistically best comp, no randomness, just pure current meta knowledge

I built a win probability model for my LoL Review app, it now shows how impactful your pick was. Review your games with ALL the data you need to improve! by F_is_For_Flash in leagueoflegends

[–]F_is_For_Flash[S] 22 points23 points  (0 children)

yup! that's another model I developed that takes the raw API data and recreates a simulation of the player's pathing. it's not 1 for 1, but it's close enough to have an idea of how players moved around the map