squashinformr allows users to easily scrape SquashInfo for data on the Professional Squash Association World Tour and other squash tournaments. The functions within this package scrape, parse, and clean data associated with players, tournaments, and rankings.
Install squashinformr via CRAN:
install.packages("squashinformr")Install the development version of squashinformr from
this GitHub repository via:
if (!require("remotes")) install.packages("remotes")
remotes::install_github("HaydenMacDonald/squashinformr")There are three major families of scraping functions in
squashinformr:
get_players()get_player_recent_results()get_player_recent_matches()get_player_recent_games()get_matchup()get_tournaments()get_tournament_players()get_tournament_matches()get_tournament_games()get_rankings()get_player_recent_matches()This function returns a player’s recent matches.
library(squashinformr)
## Get Mohamed Elshorbagy's most recent match data
get_player_recent_matches(player = "Mohamed Elshorbagy", category = "mens")
#> Scraping http://www.squashinfo.com/rankings/men/1
#> Scraping Mohamed Elshorbagy's recent results
#> # A tibble: 10 x 12
#> rank player opponent result games_won games_lost match_time round date
#> <int> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <date>
#> 1 2 Moham~ Mostafa~ L NA NA NA F 2021-02-01
#> 2 2 Moham~ Lucas S~ W 3 2 NA SF 2021-02-01
#> 3 2 Moham~ Dimitri~ W 3 1 NA QF 2021-02-01
#> 4 2 Moham~ Youssef~ L 2 3 65 R3 2020-11-01
#> 5 2 Moham~ George ~ W 3 1 61 R2 2020-11-01
#> 6 2 Moham~ Karim A~ W 3 1 73 F 2020-09-01
#> 7 2 Moham~ Paul Co~ W 3 2 84 SF 2020-09-01
#> 8 2 Moham~ Joel Ma~ W 3 1 69 QF 2020-09-01
#> 9 2 Moham~ James W~ W 3 0 36 R2 2020-09-01
#> 10 2 Moham~ Raphael~ W 3 0 34 R1 2020-09-01
#> # ... with 3 more variables: event <chr>, country <chr>, psa <chr>get_tournament_games()This function returns a tournament’s game results data.
## Return game data for 2020's Black Ball Open.
get_tournament_games("Black Ball Open", year = 2020, world_tour = TRUE)
#> Scraping http://www.squashinfo.com/results?start=1
#> Scraping http://www.squashinfo.com/results?start=2
#> Scraping http://www.squashinfo.com/results?start=3
#> Scraping http://www.squashinfo.com/events/8425-mens-black-ball-open-2020
#> # A tibble: 119 x 15
#> tournament_name category tournament_date player_1 player_2 player_1_seed
#> <chr> <chr> <date> <chr> <chr> <dbl>
#> 1 CIB Black Ball~ Men's 2020-12-18 Fares D~ Ali Far~ 9
#> 2 CIB Black Ball~ Men's 2020-12-18 Fares D~ Ali Far~ 9
#> 3 CIB Black Ball~ Men's 2020-12-18 Fares D~ Ali Far~ 9
#> 4 CIB Black Ball~ Men's 2020-12-18 Fares D~ Ali Far~ 9
#> 5 CIB Black Ball~ Men's 2020-12-18 Fares D~ Ali Far~ 9
#> 6 CIB Black Ball~ Men's 2020-12-18 Ali Far~ Mostafa~ 1
#> 7 CIB Black Ball~ Men's 2020-12-18 Ali Far~ Mostafa~ 1
#> 8 CIB Black Ball~ Men's 2020-12-18 Ali Far~ Mostafa~ 1
#> 9 CIB Black Ball~ Men's 2020-12-18 Fares D~ Tarek M~ 9
#> 10 CIB Black Ball~ Men's 2020-12-18 Fares D~ Tarek M~ 9
#> # ... with 109 more rows, and 9 more variables: player_2_seed <dbl>,
#> # player_1_nationality <chr>, player_2_nationality <chr>, round <ord>,
#> # match <int>, game <int>, player_1_score <dbl>, player_2_score <dbl>,
#> # game_winner <chr>get_rankings()This function returns data from the most recent PSA rankings tables.
library(dplyr)
## Get the top 5 players in both men's and women's singles competitions
get_rankings(top = 5, category = "both") %>%
arrange(category, rank)
#> # A tibble: 10 x 7
#> rank previous_rank name highest_world_ra~ hwr_date country category
#> <int> <int> <chr> <int> <date> <chr> <chr>
#> 1 1 1 Ali Farag 1 2019-03-01 EGY mens
#> 2 2 2 Mohamed El~ 1 2014-11-01 EGY mens
#> 3 3 3 Tarek Momen 3 2019-02-01 EGY mens
#> 4 4 4 Paul Coll 4 2020-12-01 NZL mens
#> 5 5 5 Karim Abde~ 1 2017-05-01 EGY mens
#> 6 1 1 Nour El Sh~ 1 2016-05-01 EGY womens
#> 7 2 2 Nouran Goh~ 1 2020-07-01 EGY womens
#> 8 3 3 Camille Se~ 2 2017-02-01 FRA womens
#> 9 4 4 Nour El Ta~ 3 2018-02-01 EGY womens
#> 10 5 5 Hania El H~ 5 2020-11-01 EGY womensget_matchup()This function returns recent head-to-head matchup stats between two players. Stats returned include:
## Get tidy matchup stats for Paul Coll vs Fares Dessouky
get_matchup("Paul Coll", "Fares Dessouky", category = "mens", tidy = FALSE)
#> # A tibble: 23 x 2
#> metric value
#> <chr> <chr>
#> 1 player_1_rank 4
#> 2 player_1 Paul Coll
#> 3 player_2_rank 8
#> 4 player_2 Fares Dessouky
#> 5 matches_played 2
#> 6 player_1_matches_won 2
#> 7 player_2_matches_won 0
#> 8 matches_3_2 0
#> 9 matches_3_1 1
#> 10 matches_3_0 1
#> # ... with 13 more rowsSubmit issues here on GitHub.
If you are interested in extending the functionality of this package,
fork this repository, make your changes and submit them as a pull
request. The squashinformr project is released with a
Contributor
Code of Conduct. By contributing to this project, you agree to its
terms.
SquashInfo is a valuable resource for the international squash
community. By creating and sharing this package, I do not intend to
compete with SquashInfo or any of its stakeholders. The
squashinformr package was created to allow individuals to
access data from SquashInfo in an efficient and responsible way, using
polite
principles. Following polite principles incurs
mandatory delays on the scraping process set by SquashInfo. This
prevents the use of this package from incurring unnecessary harm to
SquashInfo servers via overwhelming requests. Therefore, it is important
that users are patient when using this package. SquashInfo currently
offers full access to their data and extra features through a premium
membership. Please consider
signing up
and subscribing to SquashInfo to support their work.
This package was authored by Hayden MacDonald. Feel free to email me at hmd[at]needleinthehay.ca.
The squashinformr package is released under a
GPL-3
license.