October 19 2022: https://drive.google.com/file/d/1NF0ORHEuiphztKYZdq5GLbTcejkSHUzk/view?usp=share_link
We will use a riot API key for this demo. To register for your own riot API key please go to https://developer.riotgames.com/. The provided key for this demonstration is RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642. Note, this key will only last for 24 hours. Additional keys you can try are:
- Key 1 RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642
- Key 2 RGAPI-1b96e96c-d34a-45b0-b02d-85b35af4bef2
To use the api, there’s two functions that are called in this analysis, Endpoint_func.R and Item_func.R.
source("Endpoint_func.R")## Loading required package: RCurl
## Loading required package: rjson
## Loading required package: stringr
source("Item_func.R")Endpoint_func contains functions that we use to call the Api. Within the Endpoint_func, we have the getRIOT function. This acts as an wrapper to build an URL string. Additional functions such as getSummonerByName calls the getRiot function and appends additional parameters to build endpoints that we can query using the API.
For a list of all endpoints, please go to https://developer.riotgames.com/apis
Within Endpoint_func.R, there are three libraries we need to install. If they are not installed yet, please install them now in your local environment:
Libraries:
- RCurl : Allows us to download data from Riot’s Api into json format using the getURL function
- rjson: Allows us to convert the json format into an R list
- stringr: Allows us to build string transformations to build the request URL
Item_func contains functions built on Endpoint_func to perform basic analysis and return plotting. The analysis provided in Item_func is the ability to see historical item win rates specific to a League of Legends player and character. In order to have this functionality, we call the Endpoint_func.R functions with parameters passed in specific to request such as summoner name, champion and API key. We also use getURL to query static game data such as a repository of all the items in the game. An example of a static json file hosted online is here: http://ddragon.leagueoflegends.com/cdn/10.6.1/data/en_US/champion.json
First, lets get our encrypted_account_id specific to us so we can pull additional data. For those league players here, you can try your own summoner name!:
key = "RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
getSummonerByName('jakeateworld', key = key)## [1] "Parsing from endpoint: https://na1.api.riotgames.com/lol/summoner/v4/summoners/by-name/jakeateworld?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## $id
## [1] "DUkQjvY5ywBY8NA5ECXTJ1ZRkVyqk3FA_CHA8Vexs9KWqoM"
##
## $accountId
## [1] "RQBMGFwFTvqv-FcJOPPPDuFbSa0ZZuyOMroArOHdLC6L6Q"
##
## $puuid
## [1] "xtWDaAvaYuWLXZ7o3Bqn760oXRguy203DBTBk1TlhygxBCTjypKjMEcPybvB_EAXLOPFX_hgUWk5CQ"
##
## $name
## [1] "JAKEATEWORLD"
##
## $profileIconId
## [1] 4918
##
## $revisionDate
## [1] 1.667621e+12
##
## $summonerLevel
## [1] 296
We see that this command returns a list with our accountID, name, profileIconId, and even summonerLevel! Next, let’s call this again and store the accountId as an R object called encrypted_account_id.
encrypted_account_id <- getSummonerByName('jakeateworld', key =key)$puuid## [1] "Parsing from endpoint: https://na1.api.riotgames.com/lol/summoner/v4/summoners/by-name/jakeateworld?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
encrypted_account_id## [1] "xtWDaAvaYuWLXZ7o3Bqn760oXRguy203DBTBk1TlhygxBCTjypKjMEcPybvB_EAXLOPFX_hgUWk5CQ"
We can then use this encrypted_account_id to return a matchID with and obtain a match_list R object. If you explore this R object (matches), in R studio, you can see this contains a plethora of in game data from items to damage dealt.
matchID_example <- getGameByPuuid(encrypted_account_id, key = key)[[1]]## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/by-puuid/xtWDaAvaYuWLXZ7o3Bqn760oXRguy203DBTBk1TlhygxBCTjypKjMEcPybvB_EAXLOPFX_hgUWk5CQ/ids?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
matchID_example## [1] "NA1_4483419198"
matches <- getGameByPuuid(encrypted_account_id, key = key)## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/by-puuid/xtWDaAvaYuWLXZ7o3Bqn760oXRguy203DBTBk1TlhygxBCTjypKjMEcPybvB_EAXLOPFX_hgUWk5CQ/ids?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
Game_example <- getGameByMatchID(matchID_example, key = key)## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4483419198?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
Game_example$metadata## $dataVersion
## [1] "2"
##
## $matchId
## [1] "NA1_4483419198"
##
## $participants
## [1] "Oo3Uyz2AhHHQIT2rJw4O8DaKzDf7Lu6_BGvbuLkzFs_W-mcvxMtpnJQr4z_aMOdBkS8R5cMcDwI_Jg"
## [2] "M6Pumh-JyD_cKsFrSerpdKCx9ncfbQCvyy3IKCQ0YM61CsoRDYmVTB48RnPVkZx0OfmvSJbTDbXeAA"
## [3] "xtWDaAvaYuWLXZ7o3Bqn760oXRguy203DBTBk1TlhygxBCTjypKjMEcPybvB_EAXLOPFX_hgUWk5CQ"
## [4] "TaJVfdMYL3tgmEv8XKbbHN4kQuoecRl_H6txmoTHy6lG8Ry58u8AR-W0Ls4AgJ5ZF7KXzsX-KTGfvQ"
## [5] "r9_4su2hU7CJIb-jg_kaf-HW-CT-6AdsVrE6tDgEKyPmVKBHHCrorVK7NxxUp__6RZ5dOKNshlyxkw"
## [6] "0WC-C8kky8r37FFEzU-xH3ORaQMAamNrXXN8UO4-oi_shXcpMOh7T6rLWV5In9eY1CM6jbadHHaHdw"
## [7] "CPKhtF-86sAsIoy5QaqxkM3475Wp6kdFmvJ-TggGxGauEB7rL1jkWCowrxyAF3nIwuMVUE-HNI9XBg"
## [8] "9hzpOYgoZTAYDWlGu0Yovj2yiQuZAy2ZVluHQQqhOLRIiG7Zhjy72HVmTDEzKy6y_PI2_ggDXNY4OQ"
## [9] "HtHr6YgbBte1U2Vet5Gnm_bxz_wfZHJGdA_uEHUWoEYUnPkf50j31hh7qyxaUa-NXpKeIYOSBBTVQg"
## [10] "8bx3EWLI8Hy1KZTzpXOSCRiK8mVMAQWxYlP2z-j14mZeoD5mGZO05dPgwl4fYCeM_oYIiWJUyj1vOQ"
Finally, we call our item_analysis function. This function takes the match_list and static json data to calculate overall winrates from recent games. Under the hood, item_analysis finds all the matches associated with the player that is passed in and extracts item information for every match. Item_analysis then performs transforms for all the gathered data and consolidates it into a single dataframe.
We can then color code the winrates for further plotting with an item being Green if it is higher than your total recent game winrates and Red if worse than your recent game winrates. The function returns a dataframe called df with the results.
df <- item_analysis(name = "JAKEATEWORLD", key = key)## [1] "Parsing from endpoint: https://na1.api.riotgames.com/lol/summoner/v4/summoners/by-name/jakeateworld?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/by-puuid/xtWDaAvaYuWLXZ7o3Bqn760oXRguy203DBTBk1TlhygxBCTjypKjMEcPybvB_EAXLOPFX_hgUWk5CQ/ids?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4483419198?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4483378651?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4483352687?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4482521261?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4481902384?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4474560824?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4473741426?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4471663083?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4461579134?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4460976734?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4460410705?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4459711148?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4459643794?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4459529560?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4459359923?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4450848550?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4450615083?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4450110952?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4449055069?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Parsing from endpoint: https://americas.api.riotgames.com/lol/match/v5/matches/NA1_4448360060?api_key=RGAPI-67f20909-15ef-4c0e-94bc-9e072d70c642"
## [1] "Current champion win rate is 0.4 at a game count of 20"
df$Status <- ifelse(df$win_percent > df$total_win_rate, "Green", ifelse(df$total_win_rate < df$total_win_rate, "Red", "Yellow"))
df$ID <- 1:nrow(df)
df <- df[order(df$occur, decreasing = TRUE),]
plot_df <- head(df, n = 30)
head(df, n = 30)## name win_percent occur total_win_rate Status ID
## 7 Stealth Ward 0.3529412 17 0.4 Yellow 7
## 1 Goredrinker 0.3846154 13 0.4 Yellow 1
## 3 Doran's Blade 0.3076923 13 0.4 Yellow 3
## 17 Ionian Boots of Lucidity 0.4000000 10 0.4 Yellow 17
## 4 Mercury's Treads 0.0000000 5 0.4 Yellow 4
## 32 Long Sword 0.6000000 5 0.4 Green 32
## 27 Refillable Potion 0.5000000 4 0.4 Green 27
## 2 Maw of Malmortius 0.0000000 3 0.4 Yellow 2
## 8 Hexdrinker 0.3333333 3 0.4 Yellow 8
## 14 Pickaxe 0.6666667 3 0.4 Green 14
## 15 Poro-Snax 0.6666667 3 0.4 Green 15
## 18 Caulfield's Warhammer 0.0000000 3 0.4 Yellow 18
## 20 Blade of The Ruined King 0.0000000 3 0.4 Yellow 20
## 23 Death's Dance 0.6666667 3 0.4 Green 23
## 33 Chain Vest 0.3333333 3 0.4 Yellow 33
## 5 Edge of Night 0.5000000 2 0.4 Green 5
## 6 Serrated Dirk 0.5000000 2 0.4 Green 6
## 10 The Collector 0.5000000 2 0.4 Green 10
## 11 Zhonya's Hourglass 0.5000000 2 0.4 Green 11
## 19 Immortal Shieldbow 0.0000000 2 0.4 Yellow 19
## 22 Null-Magic Mantle 0.0000000 2 0.4 Yellow 22
## 24 Kindlegem 0.5000000 2 0.4 Green 24
## 30 Guardian Angel 0.5000000 2 0.4 Green 30
## 38 Kraken Slayer 0.5000000 2 0.4 Green 38
## 39 Berserker's Greaves 0.5000000 2 0.4 Green 39
## 46 Black Cleaver 1.0000000 2 0.4 Green 46
## 9 Plated Steelcaps 1.0000000 1 0.4 Green 9
## 12 Guardian's Horn 0.0000000 1 0.4 Yellow 12
## 13 Tear of the Goddess 0.0000000 1 0.4 Yellow 13
## 16 Cloth Armor 0.0000000 1 0.4 Yellow 16
Lastly, we can plot our returned dataframe to visualize everything through the ggplot library!
library(ggplot2)
ggplot(data = plot_df, aes(x=ID, y=win_percent, label = name)) +
geom_point(aes(colour = Status, size = occur), alpha = 0.5) +
geom_text(aes(x=ID, y=win_percent, label = name), angle = 45, nudge_y = 0.1, nudge_x = 0.1, size = 3) +
scale_x_continuous(expand = c(.1, .1)) +
scale_y_continuous(expand = c(.1, .1)) +
scale_color_manual(name = "Total Win Rate",
values = c("Red" = "Red", "Green" = "Green", "Yellow" = "Yellow"),
labels = c("Above Total Win Rate", "Below Total Win Rate", "At Total Win Rate")) + theme_bw()