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University Competitive Programming Performance Data
Education & Learning Analytics
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About
Data detailing the ICPC World Final ranking results spans from 1999 to the present, with annual updates expected. It offers an extensive overview of performance metrics for university teams worldwide participating in the International Collegiate Programming Contest (ICPC) World Finals. The ICPC, organised by the Association for Computing Machinery (ACM), is an internationally renowned programming competition where student teams tackle algorithmic problems within a set timeframe, progressing through regional and online contests to reach the finals. This resource provides valuable insights into universities that have performed outstandingly since 1999, featuring 21 key attributes.
Columns
The dataset features 21 attributes detailing contest performance:
- Year: The year the World Finals competition was held, covering 1999 up to 2024.
- Date: The specific date the World Finals competition was arranged.
- Host: The host country of the competition, with the United States (19%) and Russia (13%) being the most frequent hosts, across 15 unique nations.
- City: The city where the contest took place (e.g., Luxor, Orlando, FL).
- Venue: The specific location where the contest was held (e.g., Jolie Ville Resort & SPA Kings Island Luxor).
- Rank: The team's final rank in the ICPC World Finals, ranging from 1 to 141 (with 2% missing data). The data type for this column has been converted to integer format.
- University: The name of the university the team represented, with 616 unique institutions listed.
- Country: The country where the university is located, representing 81 unique countries, with the United States (18%) and China (12%) being major contributors.
- Team: The name given to the competing team (2322 unique values).
- Contestant 1, Contestant 2, Contestant 3: The full names of the individual team members. These fields have minor missing data percentages (approximately 14% to 15%).
- Gold: Boolean flag indicating if the team achieved a Gold medal (99 occurrences).
- Silver: Boolean flag indicating if the team achieved a Silver medal (105 occurrences).
- Bronze: Boolean flag indicating if the team achieved a Bronze medal (129 occurrences).
- Honorable: Boolean flag indicating if the team achieved an Honourable mention (2,375 occurrences, 88%).
- Score: The number of problems successfully solved by the team (maximum score is 13, with 1% missing data).
- Total: The total number of problems available in that year's World Finals contest (ranging from 8 to 15 problems).
- Score Percentage: Percentage progress achieved toward solving all problems (a value between 0 and 1, with 1% missing data).
- Penalty: The time penalty accrued in minutes for solved problems (4% missing data).
- Prize: Details regarding world and regional champion titles, though this column has a high rate of missing data (94%).
Distribution
The primary data file,
icpc-full.csv, has a file size of 546.14 kB. The structure consists of 21 columns and holds 2,708 records of valid data for most attributes. The data is available in CSV format, and results have also been segmented by year into separate files (e.g., icpc-xxxx.csv). The usability rating for this resource is 10.00.Usage
This dataset is an invaluable tool for statistical and trend analysis. It is highly suitable for developing machine learning models designed to forecast future contest results based on past achievements. Researchers can utilise the data to pinpoint universities and countries exhibiting consistent high performance over multiple years, or to examine how the distribution of solved problems changes across different contest years. Furthermore, educators and mentors can leverage this information to discern essential concepts necessary for aiding students in their preparation.
Coverage
The dataset covers the International Collegiate Programming Contest World Finals from 1999 up to the latest updates, including the ICPC WF Astana 2024 results. Geographically, it tracks the performance of teams from 81 unique countries globally. While many fields are fully populated, the individual contestant name fields have minor data gaps. Data is expected to be updated annually.
License
CC0: Public Domain
Who Can Use It
- Data Scientists/ML Developers: Creating machine learning models to predict contest outcomes or identify top talent.
- Academic Researchers/Educators: Analysing historical performance trends, understanding contest difficulty, and refining training strategies.
- Competitive Programming Enthusiasts: Seeking insights into which universities or countries are most likely to win future medals or championships.
Dataset Name Suggestions
- ICPC World Finals Historical Rankings
- Global Collegiate Programming Contest Results
- University Competitive Programming Performance Data (1999-Present)
Attributes
Original Data Source: University Competitive Programming Performance Data
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