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 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_player_rankings_history()get_matchup()get_tournaments()get_tournament_players()get_tournament_matches()get_tournament_games()get_rankings()get_historical_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 profile
#> # A tibble: 75 x 12
#> rank player opponent result games_won games_lost match_time round date event country psa
#> <int> <chr> <chr> <chr> <dbl> <dbl> <dbl> <chr> <date> <chr> <chr> <chr>
#> 1 1 Mohamed Elshorbagy Ali Farag W 3 1 79 F 2020-03-01 Canary Wharf Classic ENG Y
#> 2 1 Mohamed Elshorbagy Tarek Momen W 3 1 49 SF 2020-03-01 Canary Wharf Classic ENG Y
#> 3 1 Mohamed Elshorbagy Saurav Ghosal W 2 1 51 QF 2020-03-01 Canary Wharf Classic ENG Y
#> 4 1 Mohamed Elshorbagy Mathieu Castagnet W 2 1 48 R2 2020-03-01 Canary Wharf Classic ENG Y
#> 5 1 Mohamed Elshorbagy Paul Coll L 0 3 51 QF 2020-03-01 Windy City Open USA Y
#> 6 1 Mohamed Elshorbagy Mazen Hesham W NA NA NA R3 2020-03-01 Windy City Open USA Y
#> 7 1 Mohamed Elshorbagy Daryl Selby W 3 0 30 R2 2020-03-01 Windy City Open USA Y
#> 8 1 Mohamed Elshorbagy Paul Coll L 1 2 NA - 2020-02-01 Premier League 8th Round ENG N
#> 9 1 Mohamed Elshorbagy Peter Creed W 2 0 NA - 2020-01-01 Premier League 7th Round ENG N
#> 10 1 Mohamed Elshorbagy Tarek Momen W 3 1 76 F 2020-01-01 Tournament of Champions USA Y
#> # ... with 65 more rowsget_player_rankings_history()This function returns player ranking histories, given their full names or current PSA ranks and competition category.
library(ggplot2)
## Get the rankings history for the top three women's singles players
top_three <- get_player_rankings_history(rank = 1:3, category = "womens")
ggplot(top_three) +
geom_line(aes(x = exact_date, y = rank, group = name, colour = name)) +
scale_y_reverse() +
theme_light() +
labs(x = "Date", y = "Rank", colour = "Player")
get_tournament_games()This function returns a tournament’s game results data.
## Return game data for 2020's Tournament of Champions.
get_tournament_games("tournament of champions", year = 2020)
#> 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/results?start=4
#> Scraping http://www.squashinfo.com/results?start=5
#> Scraping http://www.squashinfo.com/events/8367-mens-tournament-of-champions-2020
#> Scraping http://www.squashinfo.com/events/8368-womens-tournament-of-champions-2020
#> # A tibble: 388 x 15
#> tournament_name category tournament_date round match game player_1 player_2 game_winner player_1_score player_2_score player_1_seed player_2_seed player_1_nation~ player_2_nation~
#> <chr> <chr> <date> <ord> <int> <int> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 JP Morgan Tourna~ Men's 2020-01-17 F 64 4 Mohamed ~ Tarek Mo~ Mohamed El~ 11 5 2 4 EGY EGY
#> 2 JP Morgan Tourna~ Men's 2020-01-17 F 64 3 Mohamed ~ Tarek Mo~ Mohamed El~ 11 7 2 4 EGY EGY
#> 3 JP Morgan Tourna~ Men's 2020-01-17 F 64 2 Mohamed ~ Tarek Mo~ Mohamed El~ 11 7 2 4 EGY EGY
#> 4 JP Morgan Tourna~ Men's 2020-01-17 F 64 1 Mohamed ~ Tarek Mo~ Tarek Momen 9 11 2 4 EGY EGY
#> 5 JP Morgan Tourna~ Women's 2020-01-17 F 62 3 Camille ~ Nour El ~ Camille Se~ 11 7 5 2 FRA EGY
#> 6 JP Morgan Tourna~ Women's 2020-01-17 F 62 2 Camille ~ Nour El ~ Camille Se~ 11 6 5 2 FRA EGY
#> 7 JP Morgan Tourna~ Women's 2020-01-17 F 62 1 Camille ~ Nour El ~ Camille Se~ 11 8 5 2 FRA EGY
#> 8 JP Morgan Tourna~ Men's 2020-01-17 SF 63 5 Tarek Mo~ Ali Farag Tarek Momen 11 7 4 1 EGY EGY
#> 9 JP Morgan Tourna~ Men's 2020-01-17 SF 63 4 Tarek Mo~ Ali Farag Ali Farag 8 11 4 1 EGY EGY
#> 10 JP Morgan Tourna~ Men's 2020-01-17 SF 63 3 Tarek Mo~ Ali Farag Ali Farag 7 11 4 1 EGY EGY
#> # ... with 378 more rowsget_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_ranking hwr_date country category
#> <int> <int> <chr> <int> <date> <chr> <chr>
#> 1 1 1 Mohamed Elshorbagy 1 2014-11-01 EGY Men's
#> 2 2 2 Ali Farag 1 2019-03-01 EGY Men's
#> 3 3 4 Karim Abdel Gawad 1 2017-05-01 EGY Men's
#> 4 4 3 Tarek Momen 3 2019-02-01 EGY Men's
#> 5 5 5 Paul Coll 5 2019-04-01 NZL Men's
#> 6 1 1 Raneem El Welily 1 2015-09-01 EGY Women's
#> 7 2 2 Nouran Gohar 2 2017-01-01 EGY Women's
#> 8 3 4 Nour El Sherbini 1 2016-05-01 EGY Women's
#> 9 4 3 Camille Serme 2 2017-02-01 FRA Women's
#> 10 5 5 Nour El Tayeb 3 2018-02-01 EGY Women'sget_matchup()This function returns recent head-to-head matchup stats between two players. Stats returned include each player’s rank, name, total matches played, number of matches won, the match results spread (relative to player 1), the average match time, the number of games played, the number of games won, average point advantage in a won game, the average point difference in final scores, the number of tie-break wins, and the percentage of games that go to a tie-breaker.
## Get tidy matchup stats for Paul Coll vs Diego Elias
get_matchup("Paul Coll", "Diego Elias", category = "mens", tidy = TRUE)
#> # A tibble: 1 x 23
#> player_1_rank player_1 player_2_rank player_2 matches_played player_1_matche~ player_2_matche~ matches_3_2 matches_3_1 matches_3_0 matches_0_3 matches_1_3 matches_2_3 avg_match_time
#> <int> <chr> <int> <chr> <int> <int> <int> <int> <int> <int> <int> <int> <int> <dbl>
#> 1 5 Paul Co~ 6 Diego E~ 2 1 1 0 1 0 0 0 1 98
#> # ... with 9 more variables: games_played <int>, player_1_games_won <int>, player_2_games_won <int>, player_1_avg_advantage <dbl>, player_2_avg_advantage <dbl>, avg_point_diff <dbl>,
#> # player_1_tiebreak_wins <int>, player_2_tiebreak_wins <int>, pct_games_tiebreak <dbl>Submit 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 hayden.macdonald.8778 [at] gmail.com.
The squashinformr package is released under a GPL-3 license.