Name: Esports Performance Rankings And Results
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Esports Performance Rankings And Results

Esports Performance Rankings and Results

Performance Rankings and Results from Multiple Esports Platforms

By [source]

About this dataset

This dataset provides a detailed look into the world of competitive video gaming in universities. It covers a wide range of topics, from performance rankings and results across multiple esports platforms to the individual team and university rankings within each tournament. With an incredible wealth of data, fans can discover statistics on their favorite teams or explore the challenges placed upon university gamers as they battle it out to be the best. Dive into the information provided and get an inside view into the world of collegiate esports tournaments as you assess all things from Match ID, Team 1, University affiliations, Points earned or lost in each match and special Seeds or UniSeeds for exceptional teams. Of course don't forget about exploring all the great Team Names along with their corresponding websites for further details on stats across tournaments!

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How to use the dataset

Download Files
First, make sure you have downloaded the CS_week1, CS_week2, CS_week3 and seeds datasets on Kaggle. You will also need to download the currentRankings file for each week of competition. All files should be saved using their originally assigned name in order for your analysis tools to read them properly (ie: CS_week1.csv).

Understand File Structure
Once all data has been collected and organized into separate files on your desktop/laptop computer/mobile device/etc., it's time to become familiar with what type of information is included in each file. The main folder contains three main data files: week1-3 and seedings. The week1-3 contain teams matched against one another according to university, point score from match results as well as team name and website URL associated with university entry; whereas the seedings include a ranking system amongst university entries which are accompanied by information regarding team names, website URLs etc.. Furthermore, there is additional file featured which contains currentRankings scores for each individual player/teams for an first given period of competition (ie: first week).

Analyzing Data
Now that everything is set up on your end it’s time explore! You can dive deep into trends amongst universities or individual players in regards to specific match performances or standings overall throughout weeks of competition etc… Furthermore you may also jumpstart insights via further creation of graphs based off compiled date from sources taken from BUECTracker dataset! For example let us say we wanted compare two universities- let's say Harvard University v Cornell University - against one another since beginning of event i we shall extract respective points(column),dates(column)(found under result tab) ,regions(csilluminating North America vs Europe etc)general stats such as maps played etc.. As well any other custom ideas which would come along in regards when dealing with similar datasets!

Research Ideas

Analyze the performance of teams and identify areas for improvement for better performance in future competitions.

Assess which esports platforms are the most popular among gamers.

Gain a better understanding of player rankings across different regions, based on rankings system, to create targeted strategies that could boost individual players' scoring potential or team overall success in competitive gaming events

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: CS_week1.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Team 1	Name of the first team in the match. (String)
University	University associated with the team. (String)

File: CS_week1_currentRankings.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Points	Points earned by each team or player in a match. (Integer)

File: CS_week2.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Team 1	Name of the first team in the match. (String)
University	University associated with the team. (String)

File: CS_week2_currentRankings.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Points	Points earned by each team or player in a match. (Integer)

File: CS_week3.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Team 1	Name of the first team in the match. (String)
University	University associated with the team. (String)

File: CS_week3_currentRankings.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Points	Points earned by each team or player in a match. (Integer)

File: seedings.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
University	University associated with the team. (String)
Team Name	Name of the team. (String)
Team url	URL of the team's website. (String)
Seeds	Ranking of the team within the tournament. (Integer)
Uni seeds	Ranking of the university within the tournament. (Integer)

File: Dota_week1.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Team 1	Name of the first team in the match. (String)
University	University associated with the team. (String)

File: Dota_week1_currentRankings.csv

Column name	Description
Match ID	Unique identifier for each match. (Integer)
Points	Points earned by each team or player in a match. (Integer)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Cs Week1

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.cs_week1

6.44 KB
135 rows
3 columns


CREATE TABLE cs_week1 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Cs Week1 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.cs_week1_currentrankings

3.2 KB
63 rows
2 columns


CREATE TABLE cs_week1_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Cs Week2

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.cs_week2

6.55 KB
141 rows
3 columns


CREATE TABLE cs_week2 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Cs Week2 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.cs_week2_currentrankings

3.24 KB
63 rows
2 columns


CREATE TABLE cs_week2_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Cs Week3

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.cs_week3

6.21 KB
124 rows
3 columns


CREATE TABLE cs_week3 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Cs Week3 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.cs_week3_currentrankings

3.11 KB
58 rows
2 columns


CREATE TABLE cs_week3_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Dota Week1

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.dota_week1

4.23 KB
46 rows
3 columns


CREATE TABLE dota_week1 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Dota Week1 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.dota_week1_currentrankings

2.79 KB
33 rows
2 columns


CREATE TABLE dota_week1_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Dota Week2

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.dota_week2

4.19 KB
46 rows
3 columns


CREATE TABLE dota_week2 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Dota Week2 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.dota_week2_currentrankings

2.77 KB
32 rows
2 columns


CREATE TABLE dota_week2_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Dota Week3

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.dota_week3

3.96 KB
39 rows
3 columns


CREATE TABLE dota_week3 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Dota Week3 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.dota_week3_currentrankings

2.68 KB
28 rows
2 columns


CREATE TABLE dota_week3_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Fortnite Finalrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.fortnite_finalrankings

2.64 KB
25 rows
2 columns


CREATE TABLE fortnite_finalrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Fortnite Week 1

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.fortnite_week_1

2.92 KB
32 rows
2 columns


CREATE TABLE fortnite_week_1 (
  "team_1" VARCHAR,
  "university" VARCHAR
);

Fortnite Week1 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.fortnite_week1_currentrankings

2.58 KB
23 rows
2 columns


CREATE TABLE fortnite_week1_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Fortnite Week 2

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.fortnite_week_2

3.02 KB
35 rows
2 columns


CREATE TABLE fortnite_week_2 (
  "team_1" VARCHAR,
  "university" VARCHAR
);

Ggs Week3

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.ggs_week3

3.43 KB
34 rows
3 columns


CREATE TABLE ggs_week3 (
  "unnamed_0" BIGINT,
  "team_1" DOUBLE,
  "university" VARCHAR
);

Ggs Week3 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.ggs_week3_currentrankings

2.52 KB
23 rows
2 columns


CREATE TABLE ggs_week3_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Ggs Week3 Positions

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.ggs_week3_positions

11.68 KB
76 rows
15 columns


CREATE TABLE ggs_week3_positions (
  "guilty_gear" DOUBLE,
  "university" VARCHAR,
  "username" VARCHAR,
  "week_1" DOUBLE,
  "week_2" DOUBLE,
  "week_3" DOUBLE,
  "week_4" VARCHAR,
  "week_5" VARCHAR,
  "overall" DOUBLE,
  "unnamed_9" VARCHAR,
  "unnamed_10" VARCHAR,
  "position" VARCHAR,
  "points_earnt" DOUBLE,
  "unnamed_13" VARCHAR,
  "unnamed_14" VARCHAR
);

Loln Week1

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.loln_week1

5.43 KB
103 rows
3 columns


CREATE TABLE loln_week1 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Loln Week1 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.loln_week1_currentrankings

2.86 KB
36 rows
2 columns


CREATE TABLE loln_week1_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Loln Week2

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.loln_week2

5.38 KB
98 rows
3 columns


CREATE TABLE loln_week2 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Loln Week2 Currentrankings

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.loln_week2_currentrankings

2.93 KB
40 rows
2 columns


CREATE TABLE loln_week2_currentrankings (
  "unnamed_0" VARCHAR,
  "points" DOUBLE
);

Loln Week3

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.loln_week3

4.69 KB
68 rows
3 columns


CREATE TABLE loln_week3 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);

Lols Week1

@kaggle.thedevastator_unlocking_collegiate_esports_performance_with_bu.lols_week1

5.77 KB
122 rows
3 columns


CREATE TABLE lols_week1 (
  "unnamed_0" BIGINT,
  "team_1" VARCHAR,
  "university" VARCHAR
);