{ "data_id": "41022", "name": "Short_Track_Speed_Skating", "exact_name": "Short_Track_Speed_Skating", "version": 2, "version_label": null, "description": "**Author**: xWang \r\n**Source**: [Kaggle](https:\/\/www.kaggle.com\/seniorwx\/shorttrack\/data) \r\n**Please cite**: \r\n\r\n**Short Track Speed Skating Database for Sports Data Analysis** \r\nThe database covers all the international short track games in the last 5 years. Currently it contains only men's 500m.\r\n\r\nDetailed lap data including personal time and ranking in each game from seasons 2012\/2013 to present .\r\nThe final time results, ranking, starting position, qualified or penalized information of each athlete in each game.\r\nAll series of World Cup, World Championship, European Championship and Olympic Games.\r\nOriginal data source\r\nThe data is collected from the ISU's (International Skating Union) official website. I have already done the cleaning procedure.\r\n\r\nPlease make sure that the data are only for personal and non-commercial use.\r\n\r\n**Explore the data** \r\nInteresting questions may be like:\r\n\r\n- What will happen in a game when there are more than one athlete from the same team? Are there performance all improved?\r\n- How does the performance of athletes change within a season and over seasons?\r\n- Do some athletes have special patterns in terms of time allocation and surpassing opportunity?\r\n- What is the influence of the implementation of 'no toe starts' rules on athletes since July 2015?\r\n- Is there also home advantage like in other sports?\r\nWho are the most dangerous guys that always get penalty?", "format": "ARFF", "uploader": "Joaquin Vanschoren", "uploader_id": 2, "visibility": "public", "creator": null, "contributor": null, "date": "2018-01-29 02:42:19", "update_comment": null, "last_update": "2018-01-29 02:42:19", "licence": "Public", "status": "active", "error_message": null, "url": "https:\/\/www.openml.org\/data\/download\/18627029\/m500_lap_time_rank_ver5_corrected.arff", "default_target_attribute": "Time", "row_id_attribute": null, "ignore_attribute": null, "runs": 0, "suggest": { "input": [ "Short_Track_Speed_Skating", "The database covers all the international short track games in the last 5 years. Currently it contains only men's 500m. Detailed lap data including personal time and ranking in each game from seasons 2012\/2013 to present . The final time results, ranking, starting position, qualified or penalized information of each athlete in each game. All series of World Cup, World Championship, European Championship and Olympic Games. Original data source The data is collected from the ISU's (International S " ], "weight": 5 }, "qualities": [], "tags": [ { "tag": "SportsAnalytics", "uploader": "2" }, { "tag": "study_93", "uploader": "2" } ], "features": [ { "name": "Time", "index": "15", "type": "numeric", "distinct": "2953", "missing": "333", "target": "1", "min": "40", "max": "102", "mean": "44", "stdev": "6" }, { "name": "Season", "index": "0", "type": "nominal", "distinct": "5", "missing": "0", "distr": [] }, { "name": "Series", "index": "1", "type": "nominal", "distinct": "4", "missing": "0", "distr": [] }, { "name": "City", "index": "2", "type": "nominal", "distinct": "17", "missing": "0", "distr": [] }, { "name": "Country", "index": "3", "type": "nominal", "distinct": "12", "missing": "0", "distr": [] }, { "name": "Year", "index": "4", "type": "nominal", "distinct": "5", "missing": "0", "distr": [] }, { "name": "Month", "index": "5", "type": "nominal", "distinct": "7", "missing": "0", "distr": [] }, { "name": "Day", "index": "6", "type": "numeric", "distinct": "21", "missing": "0", "min": "1", "max": "30", "mean": "12", "stdev": "8" }, { "name": "Distance", "index": "7", "type": "nominal", "distinct": "3", "missing": "0", "distr": [] }, { "name": "Round", "index": "8", "type": "nominal", "distinct": "11", "missing": "0", "distr": [] }, { "name": "Group", "index": "9", "type": "numeric", "distinct": "21", "missing": "0", "min": "1", "max": "21", "mean": "4", "stdev": "3" }, { "name": "Num_Skater", "index": "10", "type": "numeric", "distinct": "291", "missing": "0", "min": "1", "max": "484", "mean": "125", "stdev": "74" }, { "name": "Name", "index": "11", "type": "string", "distinct": "308", "missing": "0" }, { "name": "Nationality", "index": "12", "type": "nominal", "distinct": "47", "missing": "0", "distr": [] }, { "name": "Rank_In_Group", "index": "13", "type": "nominal", "distinct": "6", "missing": "234", "distr": [] }, { "name": "Start_Position", "index": "14", "type": "nominal", "distinct": "6", "missing": "0", "distr": [] }, { "name": "Qualification", "index": "16", "type": "nominal", "distinct": "10", "missing": "2210", "distr": [] }, { "name": "rank_lap1", "index": "17", "type": "nominal", "distinct": "6", "missing": "84", "distr": [] }, { "name": "time_lap1", "index": "18", "type": "numeric", "distinct": "192", "missing": "93", "min": "7", "max": "24", "mean": "7", "stdev": "1" }, { "name": "rank_lap2", "index": "19", "type": "nominal", "distinct": "6", "missing": "91", "distr": [] }, { "name": "time_lap2", "index": "20", "type": "numeric", "distinct": "282", "missing": "93", "min": "8", "max": "43", "mean": "9", "stdev": "2" }, { "name": "rank_lap3", "index": "21", "type": "nominal", "distinct": "6", "missing": "108", "distr": [] }, { "name": "time_lap3", "index": "22", "type": "numeric", "distinct": "350", "missing": "108", "min": "8", "max": "52", "mean": "9", "stdev": "3" }, { "name": "rank_lap4", "index": "23", "type": "nominal", "distinct": "6", "missing": "143", "distr": [] }, { "name": "time_lap4", "index": "24", "type": "numeric", "distinct": "409", "missing": "145", "min": "8", "max": "49", "mean": "9", "stdev": "3" }, { "name": "rank_lap5", "index": "25", "type": "nominal", "distinct": "7", "missing": "290", "distr": [] }, { "name": "time_lap5", "index": "26", "type": "numeric", "distinct": "545", "missing": "292", "min": "8", "max": "51", "mean": "10", "stdev": "3" } ], "nr_of_issues": 0, "nr_of_downvotes": 0, "nr_of_likes": 0, "nr_of_downloads": 1, "total_downloads": 1, "reach": 1, "reuse": 10, "impact_of_reuse": 0, "reach_of_reuse": 0, "impact": 10 }