fisdata makes it easy to download data from the FIS webpage into tibbles.
You can install the development version of fisdata from GitHub with:
# install.packages("remotes")
remotes::install_github("stibu81/fisdata")fisdata currently offers four functions to query different types of data:
query_athletes(): query athletes by name and other attributes and obtain a table of matching athletes.query_results(): query all race results for a single athlete.query_race(): obtain the full results for a single race.query_events(): query events by date, place, and other attributes.query_competitions(): obtain all individual competitions that are associated with an event.
Since athletes are identified by a Competitor-ID and races by a Race-ID that are usually not known to the user, it is generally easiest to start a query by finding an athlete. For example, the following call gets the information for Didier Cuche:
library(fisdata)
library(dplyr)
cuche <- query_athletes("cuche", "didier")
cuche %>%
select(active:nation, sector, brand, competitor_id)
#> # A tibble: 1 × 7
#> active fis_code name nation sector brand competitor_id
#> <lgl> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 FALSE 510030 Cuche Didier SUI AL Head 11795The result includes the competitor_id, which is required as input in
order to query an athlete’s results.
With the object returned by query_athletes(), it is now possible to
query all the race result of an athlete. Note that query_results()
must be called with a single athlete. The following query only obtains
the results in downhill races:
cuche_res <- query_results(cuche, discipline = "DH")
cuche_res %>%
select(athlete:place, category:rank, race_id)
#> # A tibble: 303 × 7
#> athlete date place category discipline rank race_id
#> <chr> <date> <chr> <chr> <chr> <int> <chr>
#> 1 Cuche Didier 2012-03-14 Schladming World Cup Downhill 17 66746
#> 2 Cuche Didier 2012-03-13 Schladming Training Downhill 1 66744
#> 3 Cuche Didier 2012-03-03 Kvitfjell World Cup Downhill 10 66811
#> 4 Cuche Didier 2012-03-01 Kvitfjell Training Downhill 2 66809
#> 5 Cuche Didier 2012-02-29 Kvitfjell Training Downhill 3 66810
#> 6 Cuche Didier 2012-02-11 Sochi World Cup Downhill 12 66801
#> 7 Cuche Didier 2012-02-10 Sochi Training Downhill 7 66800
#> 8 Cuche Didier 2012-02-08 Sochi Training Downhill 2 66798
#> 9 Cuche Didier 2012-02-04 Chamonix World Cup Downhill 7 66795
#> 10 Cuche Didier 2012-02-03 Chamonix World Cup Downhill 3 66767
#> # ℹ 293 more rowsThe result includes the race_id, which is required as input in order
to query the full results of a race.
By extracting one of the races from the table, one can now obtain the full results for that race. The following code gets the full result for Didier Cuche’s last victory in Wengen:
wengen_res <- cuche_res %>%
filter(place == "Wengen", rank == 1) %>%
head(n = 1) %>%
query_race()
wengen_res
#> # A tibble: 70 × 8
#> rank bib fis_code name birth_year nation time diff_time
#> <int> <int> <chr> <chr> <int> <chr> <Period> <Period>
#> 1 1 18 510030 Cuche Didier 1974 SUI 1M 50.31S 0S
#> 2 2 12 292514 Heel Werner 1982 ITA 1M 51.17S 0.86S
#> 3 3 15 511313 Janka Carlo 1986 SUI 1M 51.52S 1.21S
#> 4 4 1 560332 Jerman Andrej 1978 SLO 1M 51.58S 1.27S
#> 5 5 3 533866 Nyman Steven 1982 USA 1M 51.67S 1.36S
#> 6 6 14 51005 Scheiber Mario 1983 AUT 1M 51.76S 1.45S
#> 7 7 28 50858 Streitberger Georg 1981 AUT 1M 51.77S 1.46S
#> 8 8 16 50041 Walchhofer Michael 1975 AUT 1M 51.79S 1.48S
#> 9 8 11 50753 Kroell Klaus 1980 AUT 1M 51.79S 1.48S
#> 10 10 25 293006 Innerhofer Christ… 1984 ITA 1M 51.85S 1.54S
#> # ℹ 60 more rowsAlternatively, you may start by querying for an event. This finds the Wengen races from the season 2024/25:
wengen2025 <- query_events(sector = "AL", place = "wengen", season = 2025)
wengen2025
#> # A tibble: 1 × 10
#> start_date end_date place nation sector categories disciplines genders
#> <date> <date> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 2025-01-14 2025-01-19 Wengen SUI AL TRA / WC 4xDH / SL / SG M
#> # ℹ 2 more variables: cancelled <lgl>, event_id <chr>The result includes the event_id, which is required as input in order
to query all the competitions that took place during this event:
wengen_races <- query_competitions(wengen2025)
wengen_races
#> # A tibble: 6 × 9
#> place date time competition sector category gender cancelled race_id
#> <chr> <date> <chr> <chr> <chr> <chr> <chr> <lgl> <chr>
#> 1 Wengen 2025-01-14 12:30 Downhill Tra… AL TRA M FALSE 122804
#> 2 Wengen 2025-01-15 12:30 Downhill Tra… AL TRA M FALSE 122805
#> 3 Wengen 2025-01-16 <NA> Downhill Tra… AL TRA M TRUE 122806
#> 4 Wengen 2025-01-17 12:30 Super G AL WC M FALSE 122807
#> 5 Wengen 2025-01-18 12:45 Downhill AL WC M FALSE 122808
#> 6 Wengen 2025-01-19 10:15 Slalom AL WC M FALSE 122809This table now allows to query for the full race results (similar to the
output from query_results()). For example, the results for the Super G
can be obtained as follows:
sg_res <- wengen_races %>%
filter(competition == "Super G") %>%
query_race()
sg_res
#> # A tibble: 47 × 11
#> rank bib fis_code name brand birth_year nation time diff_time
#> <int> <int> <chr> <chr> <chr> <int> <chr> <Period> <Period>
#> 1 1 3 512471 Von Allmen … Head 2001 SUI 1M 47.65S 0S
#> 2 2 6 53980 Kriechmayr … Head 1991 AUT 1M 47.75S 0.1S
#> 3 3 11 512038 Rogentin St… Fisc… 1994 SUI 1M 48.23S 0.58S
#> 4 4 1 104531 Crawford Ja… Head 1997 CAN 1M 48.27S 0.62S
#> 5 5 9 291459 Paris Domin… Nord… 1989 ITA 1M 48.28S 0.63S
#> 6 6 8 990081 Casse Mattia Ross… 1990 ITA 1M 48.57S 0.92S
#> 7 7 13 512269 Odermatt Ma… Stoe… 1997 SUI 1M 48.69S 1.04S
#> 8 8 16 104537 Alexander C… Ross… 1997 CAN 1M 48.78S 1.13S
#> 9 9 2 512408 Monney Alex… Stoe… 2000 SUI 1M 48.92S 1.27S
#> 10 10 26 54628 Feurstein L… Head 2001 AUT 1M 48.97S 1.32S
#> # ℹ 37 more rows
#> # ℹ 2 more variables: fis_points <dbl>, cup_points <dbl>Note that the objects created by the querying functions always include the URL that was downloaded. This URL can be obtained as follows:
show_url(cuche_res)
#> https://www.fis-ski.com/DB/general/athlete-biography.html?sectorcode=AL&seasoncode=&competitorid=11795&type=result&categorycode=&sort=&place=&disciplinecode=DH&position=&limit=2000You can copy this address into a browser in order to see the same data
as they are presented on the FIS web site. To make this as easy as
possible, show_url() automatically copies the URL into the clip board,
when called from an interactive R session.
Querying athletes and results is expected to work for all sectors and disciplines. Querying races, however, is more difficult, since different types of races have their results rendered in different form on the FIS web site. fisdata is able to handle the results of many common types of races but it is expected to fail for some types that are not yet covered. For example, it usually cannot handle team races:
query_athletes("von allmen", "franjo") %>%
query_results(category = "WSC") %>%
filter(discipline == "Team Combined") %>%
query_race()
#> Warning in query_race(.): ! The data contains some fields unknown to fisdata.
#> ℹ Affected column: 'name'
#> ! These columns might not be processed as expected.
#> Warning in process_race_column(name, race_df): NAs introduced by coercion
#> Warning in process_race_column(name, race_df): NAs introduced by coercion
#> Warning in process_race_column(name, race_df): NAs introduced by coercion
#> Error in `dplyr::as_tibble()`:
#> ! Column names `nation` and `time` must not be duplicated.
#> Use `.name_repair` to specify repair.
#> Caused by error in `repaired_names()`:
#> ! Names must be unique.
#> ✖ These names are duplicated:
#> * "nation" at locations 7 and 8.
#> * "time" at locations 9 and 10.