A speedrun.com API wrapper for R https://jemus42.github.io/speedrunr/
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README.md

speedrunr

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The goal of speedrunr is to easily access data from speedrun.com.

Installation

You can install the released version of speedrunr from GitHub with:

remotes::install_github("jemus42/speedrunr")

Example

Let’s say you want to plot the times of all Ocarina of TIme 100% runs.
Let’s get started:

library(speedrunr)
library(dplyr) # Data manip
library(knitr) # Tables

Identifiyng the game you’re looking for

You can either search for “Ocarina of Time”, or supply 'oot', the game’s abbreviation on speedrun.com.

games <- get_games(name = "Ocarina of Time")

games %>% 
  select(id, name_international, name_abbr) %>%
  head() %>%
  kable()
id name_international name_abbr
j1l9qz1g The Legend of Zelda: Ocarina of Time oot
kdkjex1m The Legend of Zelda: Ocarina of Time Master Quest ootmq
268vqkdp The Legend of Zelda: Ocarina of Time 3D oot3d
76rkv4d8 Ocarina of Time Category Extensions ootextras
m1zromd0 Ocarina of Time Beta Quest ootbq
v1pol9m6 SM64: Ocarina of Time sm64oot

Turns out j1l9qz1g is the id we’re looking for.

Get the game’s categories

categories <- get_categories(id = "j1l9qz1g")

categories %>%
  select(id, name, type) %>%
  head() %>%
  kable()
id name type
q255jw2o 100% per-game
824qn3k5 100% per-level
zdnoz72q All Dungeons per-game
q25g198d Any% per-game
02qe4z2y Any% per-level
zd35jnkn Glitchless per-game

So apparently we’re looking for q255jw2o, the full-game 100% category.

Get the runs in that category

Now we can fetch the runs. By default, 100 runs are returned, ordered by submit date in descending order, so newest runs first. This also means you will only be able to fully assess the WR progression if you make sure to get all the runs.

runs <- get_runs(game = "j1l9qz1g", category = "q255jw2o")

glimpse(runs)
#> Rows: 100
#> Columns: 22
#> $ id              <chr> "y9015e2y", "yd55novm", "z5j7l4nm", "zpr4kk8m", "mrke…
#> $ weblink         <chr> "https://www.speedrun.com/oot/run/y9015e2y", "https:/…
#> $ game            <chr> "j1l9qz1g", "j1l9qz1g", "j1l9qz1g", "j1l9qz1g", "j1l9…
#> $ level           <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
#> $ category        <chr> "q255jw2o", "q255jw2o", "q255jw2o", "q255jw2o", "q255…
#> $ videos          <chr> "https://www.twitch.tv/videos/608790240", "https://ww…
#> $ status          <chr> "verified", "verified", "verified", "verified", "veri…
#> $ comment         <chr> NA, "3rd try Dampe", "This run sucks.", NA, "Finally …
#> $ player_id       <chr> "zx73zzvj", "v813d3xp", "pj00zwjw", "v8l62g78", "v8lr…
#> $ player_url      <chr> "https://www.speedrun.com/user/JoeCool", "https://www…
#> $ player_name     <chr> "JoeCool", "glitchymon", "EnNopp112", "EricDaCleric",…
#> $ player_role     <chr> "user", "user", "user", "user", "user", "user", "user…
#> $ player_signup   <dttm> 2019-09-10 02:55:31, 2015-03-05 22:12:19, 2015-06-25…
#> $ date            <date> 2020-05-01, 2020-04-06, 2020-04-12, 2020-04-21, 2020…
#> $ submitted       <dttm> 2020-05-02 04:21:10, 2020-04-28 11:01:30, 2020-04-21…
#> $ time_primary    <int> 18240, 13465, 13805, 13847, 35313, 14660, 20783, 1362…
#> $ time_realtime   <int> 18240, 13465, 13805, 13847, 35313, 14660, 20783, 1362…
#> $ time_ingame     <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
#> $ time_hms        <time> 05:04:00, 03:44:25, 03:50:05, 03:50:47, 09:48:33, 04…
#> $ system_platform <chr> "nzelreqp", "nzelreqp", "nzelreqp", "nzelreqp", "w89r…
#> $ system_emulated <lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALS…
#> $ system_region   <chr> "o316x197", "o316x197", "o316x197", "o316x197", "o316…

And now we can basically re-create the leaderboard, but including obsoleted runs:

library(hms)

runs %>%
  arrange(time_primary) %>%
  head(20) %>%
  select(submitted, time_primary, player_name) %>%
  mutate(time_primary = hms(seconds = time_primary)) %>%
  kable()
submitted time_primary player_name
2020-04-28 11:01:30 03:44:25 glitchymon
2020-04-03 08:26:30 03:45:59 glitchymon
2020-04-12 11:36:02 03:47:00 AxelLarsen
2020-04-11 02:34:15 03:48:01 AxelLarsen
2020-03-19 00:14:45 03:49:23 glitchymon
2020-02-18 18:45:03 03:49:58 glitchymon
2020-04-21 12:30:19 03:50:05 EnNopp112
2020-03-28 11:59:22 03:50:31 AxelLarsen
2020-04-21 10:02:01 03:50:47 EricDaCleric
2020-02-29 09:55:40 03:50:47 Marco
2019-12-20 00:23:32 03:51:34 glitchymon
2020-03-22 10:06:41 03:52:14 AxelLarsen
2019-11-26 11:43:07 03:52:21 glitchymon
2019-12-19 17:59:29 03:53:27 Marco
2019-10-29 02:06:15 03:54:15 glitchymon
2020-03-20 12:07:33 03:54:49 AxelLarsen
2020-03-06 08:34:33 03:55:24 AxelLarsen
2019-11-16 07:33:14 03:55:32 Marco
2019-11-01 18:23:51 03:55:52 Marco
2020-03-30 17:31:17 03:57:18 EricDaCleric

More data

Wanna resolve those platforms? Just join with this table:

get_platforms() %>%
  head() %>%
  kable()
id name released
mr6km09z MS-DOS 1970
8gej2n93 PC 1970
3167od9q Plug & Play 1970
vm9vkn63 Tabletop 1970
w89ryw6l Apple II 1977
o0644863 Atari 2600 1977

Same can be done with regions:

get_regions() %>%
  kable()
id name
ypl25l47 BRA / PAL
mol4z19n CHN / PAL
e6lxy1dz EUR / PAL
o316x197 JPN / NTSC
p2g50lnk KOR / NTSC
pr184lqn USA / NTSC

There are also convenience functions to pipe your runs object into:

  • add_platforms()
  • add_regions()
  • add_players(), which only makes on API call per unique player.

All of them work in the following way:

runs %>% 
  add_regions() %>%
  add_platforms() %>%
  select(time_primary, system_region, system_platform) %>%
  sample_n(5) %>%
  knitr::kable()
time_primary system_region system_platform
16178 JPN / NTSC Wii Virtual Console
27921 JPN / NTSC Wii Virtual Console
13894 JPN / NTSC Wii Virtual Console
17804 JPN / NTSC Wii Virtual Console
13831 JPN / NTSC Wii Virtual Console

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.