This dataset provides a fictional representation of the popularity of cricket, football, and badminton across 100 countries. Each row corresponds to a country, detailing the estimated percentage of the population that engages in or follows each of the three sports. While the dataset includes real country names, the popularity percentages are simulated and should not be used for serious analysis. This dataset can be utilized for educational purposes, testing, or as a placeholder in projects where real-world data is not required.

The FIFA World Cup is the biggest and most prestigious football tournament in the world, featuring the best teams from every corner of the globe. The tournament has been held every four years since 1930, with the exception of 1942 and 1946 due to World War II. Throughout its history, the World Cup has produced countless memorable moments, thrilling matches, and of course, goals.

This dataset containing information about every goal scored in World Cup matches from 1930 to 2022.The dataset contains a wide range of information about each goal, including the match details (such as the teams involved, the scoreline, and the date), the player who scored the goal, and the time at which the goal was scored. It is an invaluable resource for researchers and football enthusiasts alike, providing a wealth of information about the history of the World Cup and the players who have participated in it over the years.

Some of the variables included in the dataset are:

• Year: The year in which the match was played
• Round: The round of the tournament in which the match was played (e.g. group stage, knockout stage)
• Match Number: The number of the match in the tournament
• Home Team Name: The name of the home team
• Away Team Name: The name of the away team
• Home Team Goals: The number of goals scored by the home team
• Away Team Goals: The number of goals scored by the away team
• Goal Type: The type of goal (e.g. penalty, header, free kick)
• Goal Scorer: The name of the player who scored the goal
• Time: The time at which the goal was scored

The dataset can be used to answer a wide range of research questions, such as:

Which team has scored the most goals in World Cup history? Who is the all-time leading goal scorer in World Cup history? What percentage of World Cup goals are scored in the first half versus the second half? How has the frequency of certain types of goals (e.g. penalties, headers) changed over time? The FIFA World Cup All Goals dataset on Kaggle is a fantastic resource for anyone interested in the history of the tournament and the players who have participated in it over the years.

Brazil Team Data From 2022 All Competition including Friendlies, Worldcup Qualifications and other Competition Held in 2022. The Dataset Include Following attributes to Understant Perfect Playing xi,Goals, Assists and defensive Contribution by team.

Attributes For All Competition Dataset Player
Position
Age Match Played
Starts
Min 90s Goals
Assists Goals(not penalty)
Penalty Penalty Kicks
Yellow Card Red Card
Goals(90s)
Assist(90s) G+A(90s)
Not Penalty(90s)
G+A-PK(90s)

Attributes For Shooting Dataset

Player
Position
Age 90s Gls = Goals Sh = Shots in Total, Excluding Penalty Kick SoT = Shots on Target SoT% = Shots on Target Percentage Sh/90 = Shots Per 90min SoT/90= Shots on Target Per 90min G/Sh = Goals Per Shot G/SoT = Goal Per Shot on Target PK = Penalty kick Made PKatt = Penalty Kick Attempted

Attributes In GoalKeeping Dataset

Player
Pos = Position Age Match Played
Starts
Min 90s = Per 90mins GA = Goal Against GA90 = Goal Against Per 90 SoTA = Shots on Target Against Saves
Save% = Save Percentage Win Draw
Loss
CS = Clean Sheet CS% = Clean Sheet Percentage PKatt = Penalty Kicks Attempted PKA = Penalty Kicks Allowed PKsv = Penalty Kick Saved PKm = Penalty Kick Missed

Argentina Team Data From 2022 All Competition including Friendlies, World Cup Qualifications and other Competition Held in 2022. The Dataset Include Following attributes to Understand Perfect Playing xi, Goals, Assists and Defensive Contribution by team

Attributes For All Competition Dataset Player Position Age Match Played Starts Min 90s Goals Assists Goals(not penalty) Penalty Penalty Kicks Yellow Card Red Card Goals(90s) Assist(90s) G+A(90s) Not Penalty(90s) G+A-PK(90s)

Attributes For Shooting Dataset

Player Position Age 90s Gls = Goals Sh = Shots in Total, Excluding Penalty Kick SoT = Shots on Target SoT% = Shots on Target Percentage Sh/90 = Shots Per 90min SoT/90= Shots on Target Per 90min G/Sh = Goals Per Shot G/SoT = Goal Per Shot on Target PK = Penalty kick Made PKatt = Penalty Kick Attempted

Attributes In GoalKeeping Dataset

Player Pos = Position Age Match Played Starts Min 90s = Per 90mins GA = Goal Against GA90 = Goal Against Per 90 SoTA = Shots on Target Against Saves Save% = Save Percentage Win Draw Loss CS = Clean Sheet CS% = Clean Sheet Percentage PKatt = Penalty Kicks Attempted PKA = Penalty Kicks Allowed PKsv = Penalty Kick Saved PKm = Penalty Kick Missed

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Liverpool Football Club's Matches (English League)

Manager Nationality, Games and Odds

By Ryan Estrellado [source]

About this dataset

This dataset reveals the history of Liverpool Football Club's success in the English League matches since 1892. Analyze this data to explore all aspects of their match performance, including their manager's experience, win percentage, and other statistics. Learn how each manager has contributed to the achievement of Liverpool FC in each season they have been at the helm while examining their nationality and tenure at Liverpool. See which managers helped Liverpool secure trophies such as FA Cup, League Cup, European Cup/Champions League and UEFA Super Cup triumphs over time. Study closely how changes in odds calculation were reflected in performances on field or understand how certain trends related to differences between away and home games' results also inform future decisions for any team aspiring to be a part of English football’s elite clubs without fail. Take advantage of this collection today and win more knowledge about the iconic successes that many legendary managers have brought forth from Anfield to delight fans from around world!

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How to use the dataset

This dataset contains the win ratios of Liverpool Football Club in English League matches for the period from 1892. It includes detailed information on each manager's role, tenure, win percentage and other metrics. This data can be used to provide key insights into the team’s performance and the strategies put in place by their managers throughout this time period.

Research Ideas

• Analyzing the tenure of a manager to identify the optimal amount of time for a successful reign. This can be done by plotting win percentages against the duration of their managerial term at Liverpool FC, with information about leagues and cups won or lost as further arguments for success or failure.
• Comparing win ratios from different eras in order to identify significant patterns and possible trends in the long-term history of LFC's performance on English League matches, taking into account factors such as changing legue rules and mentalities on football tactics over time
• Examining correlations between team performance, manager nationality and period in office, to assess whether there is any relationship between them that could help predict team outcomes in future matches based on these characteristics

Acknowledgements

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

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: wiki_lfc_mngrs.csv | Column name | Description | |:----------------|:------------------------------------------------------------------------------| | Name | Name of the manager. (String) | | Nationality | Nationality of the manager. (String) | | From | Start year of the manager's tenure. (Integer) | | To | End year of the manager's tenure. (Integer) | | P | Total number of matches played in the English League season. (Integer) | | W | Total number of wins in the English League season. (Integer) | | D | Total number of draws in the English League season. (Integer) | | Win % | Win percentage of the English League season. (Float) | | L1 | Total number of home wins in the English League season. (Integer) | | L2 | Total number of away wins in the English League season. (Integer) | | FA | Total number of FA Cup wins in the English League season. (Integer) | | **L...