A comprehensive dataset on stage-races in professional cycling

A comprehensive dataset on race-level information of all Grand Tours and major one-week stage races in professional cycling.

Usage

cyclingdata

A data frame with 11,125 rows and 18 columns:

race: Race name.
year: Year.
stage: Stage name.
stage_id: Stage ID extracted from stage name (e.g., prologue, 1, 2a, 2b).
stage_num: Stage number in order of completion within a given race (e.g., prologue, stage 1, stage 2a, stage 2b are assigned 1, 2, 3, 4, respectively).
stage_type: Stage type (Prologue, Road race, ITT, or TTT).
date: Date of race. Format: YYYY-MM-DD.
departure: Location of departure.
arrival: Location of arrival.
parcours_type: Stage profile type. (Hills uphill finish, Hills flat finish, Flat, Mountains flat finish, Mountains uphill finish).
distance: Race length in kilometers.
vertical_meters: Number of vertical meters.
profile_score: Numeric value of race difficulty. See: https://www.procyclingstats.com/info/profile-score-explained
startlist_quality: Numeric value of the quality of riders at the start of the race. See: https://www.procyclingstats.com/calendar/uci/startlist-quality>
avg_speed_winner: Average speed of winner in km/h.
won_how: Description of how the race was won.
win_type: Category of win type (Solo, Sprint à deux, Large group sprint, Small group sprint, Unknown type). Small group sprint refers to all sizes of reduced pelotons. Refer to won_how for more details on group size.
km_solo: Length of winning solo attack (only applies to solo wins).