Context

Data set for people who love Football and Data Science. Scraping code at GitHub repo: https://github.com/themlphdstudent/kaggle/blob/master/datasets/Premier%20League%20Player%20Stats/Premier%20League%20Player%20Stats.ipynb

Content

• Rank : Rank of the player
• Player : Player name
• Team : Player team name
• GP : Games played
• GS : Games started
• MIN : Minutes played
• G : Goals
• ASST : Assists
• SHOTS : Total shots
• SOG : Shots on goal

Data Source

The data is scraped from the website https://www.msn.com/en-us/sports/soccer/premier-league/player-stats by extracting the player stats in premier league.

Acknowledgements

The data has been crawled from the https://www.msn.com/en-us/sports/soccer/premier-league/player-stats website. Cover photo credit : Photo by Fachry Zella Devandra on Unsplash.

Context

I had the need to collect Europe's top 5 leagues' dataset for my own undergraduate project. The idea was to eliminate human bias from the player scouting process.

More Details: https://github.com/Suwadith/Winning-Eleven-Scout-Evaluation-and-Analysis-to-Enhance-Football-Player-Recommendations-ML-Flask

Content

This dataset contains individual player statistics from Europe's top 5 leagues 2009 - 2018. Leagues included: La Liga, Bundesliga, Serie A, Ligue 1, Premier League Types of stats: Offensive, Defensive, Passing, Overall Summary

Acknowledgements

This dataset was compiled from the https://www.whoscored.com website

Dataset

This dataset was created by Saswat Sarangi

Contents

Complete data of all IPL 2020 matches is provided in this space for data enthusiasts to aid their flair. The data will be refreshed post every match with the updates. Also historic data of all IPL matches played from 2008 to 2019 is provided here. All the player names are synced in all the 'Deliveries' datasets. Note: If you are interested in the code and tutorial, you can check it out this link- https://dicco89.medium.com/web-scraping-ball-by-ball-data-from-espn-cricinfo-192b36583d4a Happy Analyzing !!!

Context

I collected this data from publicly available source http://www.oddsportal.com. It has all games for 3 sequential seasons listed in chronological order, 20 * 20 - 20 = 380 per season, and 3 seasons = 3 * 380 = 1140 games. Besides scores it has one bookmaker bet record for 1X2 (home, draw, away). The goal of this data is to let people to test hypotheses of money making. The prediction of outcomes based on history is an old and widely tested problem, using bookie's bets for prediction of outcomes too. What I tried with this data was to maximize money gain. For example, you can win easy by betting on favorite, but the winning amount is small. I tried to recognize cases when betting on low probable outcome statistically benefits the gambler assuming large enough number of bets. It was very successful. I used matrix factoring technique for scores and, on the top, my own AI concept as Kolmogorov-Arnold representation, which is generalization of neural network. NN is a particular case of K-A representation.

The data collection consists of: a list of technologies resulting from an online survey of 'bio' products available on the market and the companies marketing them (see Related resources); a collection of bibliographic references and abstracts of published scientific articles on biological therapy topics including Platelet Rich Plasma (PRP), stem cells, and others in trial or sporting contexts; notes made by researchers at sports medicine conferences; transcripts of relevant selected presentations at sports medicine conferences and related fieldwork notes; and interviews with medical members of national and elite UK football clubs and cycling organisations and sports authorities and companies providing products and services to them.Biotechnological medicine and elite sport are two of the most powerful symbolic institutions of the contemporary era. Yet there is no systematic investigation of the intersections of these fields and their significance for society. The project examines the development and application of innovative biomedical technologies relevant to musculoskeletal injury, enabling analysis of two types of questions. Against a mapping of emerging interactions between sports and biomedicine, the research asks, first: What are the effects of sports patronage and collaboration on biomedical innovation, and conversely, how does biomedical research and innovation impact on elite sports and its athletes? Second, the research sets out to clarify the ethical issues raised by these developments and how publics and stakeholders understand and evaluate them (including the 'human enhancement' debate). A multi-method research design sets the study in the context of sports in general, focusing on football (soccer) and cycling as case studies because of their different funding regimes and injury profiles. Data are collected via documents, interviews, and observation methods (eg at sports' medical conferences). We undertake ethical analysis and public engagement comprising deliberative interactive online debate and focus groups to clarify issues of concern, and to inform and elicit public opinion. Observation at sports medicine conferences in UK, Italy, India and Denmark; Published bio-scientific documents collection; Workshop with 20+ expert stakeholders. [Qualitative semi-structured interviews in the UK (orthobiologics companies, surgeons, physiotherapists, medical insurers, sports medicine practitioners affiliated to professional football (mainly English Premier League) and cycling organisations, sports authority medicine section staff) - not available due to unique identities].

WHAT IS CRICSHEET?

Cricsheet is Retrosheet for Cricket. We provide ball-by-ball data for Men’s and Women’s Test Matches, One-day internationals, Twenty20 Internationals, some other international T20s, and various club competitions such as all Indian Premier League seasons, and some Big Bash League, T20 Blast, and Pakistan Super League matches.

At the moment we have ball-by-ball information for 7,470 matches, comprising 628 Test matches, 23 other multi-day matches, 2,033 One-day internationals, 372 other one-day matches, 1,432 T20 internationals, 332 international T20s, 816 Indian Premier League matches, 365 Big Bash League matches, 815 T20 Blast matches, 146 Pakistan Super League matches, 264 Women's Big Bash League matches, and 244 Caribbean Premier League matches, featuring 85 countries, 57 club teams, and 3 representative XIs going back as far as 2007 (for women), and 2004 (for men).

The most recent matches added to the site are the New Zealand vs Pakistan Men’s T20 match that was played on the 22nd of December, 2020, the Perth Scorchers vs Sydney Thunder Big Bash League match that was played on the 22nd of December, 2020, and Pakistan vs New Zealand Men’s T20 match that was played on the 20th of December, 2020.

THE DATA

The data is provided in a number of zip files, one of which contains all of the matches, and the others certain sub-sets of matches, such as for the type of matches, matches for certain countries, teams, or genders, or periods of time. We also provide (as an experiment) CSV and XML versions of all matches. Below is the listing of the data grouped by types of matches (for any gender), or you can see the full set of downloads, in various formats, on the downloads page.

All matches

7,470 matches, 30.7 MB
Test matches
628 matches, 8.2 MB
Multi-day matches
23 matches, 258 KB
One-day internationals
2,033 matches, 9.1 MB
One-day matches
372 matches, 1.6 MB
T20 internationals
1,432 matches, 3.7 MB
Non-official T20 internationals
332 matches, 837 KB
Big Bash League matches
365 matches, 957 KB
Indian Premier League matches
816 matches, 2.2 MB
Caribbean Premier League matches
244 matches, 644 KB
T20 Blast matches
815 matches, 2.1 MB
Pakistan Super League matches
146 matches, 387 KB
Women's Big Bash League matches
264 matches, 689 KB

USING THE DATA

What could you do with the data? Well, t that’s up to you really. You could investigate who are the best and worst value players in the IPL. Or see how much difference different non-strikers make to the scoring rate of the people they bat with. Or come up with something completely new that revolutionizes cricket like finding the equivalent of DIPS (Defense independent pitching statistics) from baseball.

THE DATA FORMAT

The data is provided in YAML format, a human-readable data format. There are libraries available to parse this in multiple languages. As for the structure of the file, hopefully, it is clear enough when you have a look at the data, although a full description of the format is also available.

HOW CAN I HELP?

SPOTTING ERRORS IN THE DATA The first method of helping would be to spot any errors in the data. Ideally, we won’t have any but there’s always the chance and if we can spot the errors we can fix them and write further validation to ensure that further examples don’t slip through.

HELPING WITH MISSING DATA

The second method of helping is to help us get ball-by-ball data for our missing games. This doesn’t even have to involve finding the data, it’s possible you know a contact who may be able to shed light on some matches, or you know of someone who has the commentary for a match on tape. Even small bits of info might be enough to put us on the right track.

BLOG ENTRIES

We do have an infrequent blog to which we occasionally post about updates to the data format, additions to the site, or random musings. The most recent entry was “Hello again” on the 17th of April, 2019.

GETTING IN TOUCH

You can contact the project at stephen (at) cricsheet (dot) org. Feel free to get in touch, we love hearing about what people are doing with the data.

Context

The Indian Premier League (IPL) is a professional men's Twenty20 cricket league, contested by ten teams based out of ten Indian cities. The league was founded by the Board of Control for Cricket in India (BCCI) in 2007. It is usually held between March and May of every year and has an exclusive window in the ICC Future Tours Programme.

The IPL is the most-attended cricket league in the world and in 2014 was ranked sixth by average attendance among all sports leagues. In 2010, the IPL became the first sporting event in the world to be broadcast live on YouTube. The brand value of the IPL in 2019 was ₹47,500 crores (6.3 billion US dollars), according to Duff & Phelps. According to BCCI, the 2015 IPL season contributed ₹1,150 crores (150 million US dollars) to the GDP of the Indian economy. The 2020 IPL season set a massive viewership record with 31.57 million average impressions and with an overall consumption increase of 23 percent from the 2019 season.

The previous IPL title holders are the Chennai Super Kings, winning the 2021 season. The venue for the 2020 season was moved due to the COVID-19 pandemic and games were played in the United Arab Emirates. There have been fifteen seasons of the IPL tournament. The current IPL title holder franchise is Gujarat Titans, winning the 2022 season.

Data Description:

This Datasets has 2 files: the first datasets IPL_finals_ball_by_ball.csv has following columns:

1. batter
2. bowler
3. non_striker
4. runs.batter
5. runs.extras
6. runs.total
7. extras.legbyes
8. wickets
9. extras.wides
10. team
11. powerplays

The second datasets `final_info.csv' has folowing columns:

balls_per_over city dates gender match_type overs player_of_match season team_type teams venue event.name event.stage officials.match_referees officials.reserve_umpires officials.tv_umpires officials.umpires outcome.winner outcome.by.wickets players.Rajasthan Royals players.Gujarat Titans registry.people.AK Chaudhary registry.people.CB Gaffaney registry.people.D Padikkal registry.people.DA Miller registry.people.HH Pandya registry.people.J Srinath registry.people.JC Buttler registry.people.KN Ananthapadmanabhan registry.people.LH Ferguson registry.people.M Prasidh Krishna registry.people.MS Wade registry.people.Mohammed Shami registry.people.Nitin Menon registry.people.OC McCoy registry.people.R Ashwin registry.people.R Parag registry.people.R Sai Kishore registry.people.R Tewatia registry.people.Rashid Khan registry.people.SO Hetmyer registry.people.SV Samson registry.people.Shubman Gill registry.people.TA Boult registry.people.WP Saha registry.people.YBK Jaiswal registry.people.YS Chahal registry.people.Yash Dayal toss.decision toss.winner

Acknolowdegement:

1. source: cricsheet