This dataset was created by Jaseem Mohammed
It contains the following files:
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Detailed analysis of the business of the English Premier League, focusing on sponsorship and the media landscape Read More
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
This dataset was created by MHumph
Released under CC BY-SA 4.0
In 2022/23, broadcasting revenue was worth over three billion euros to clubs in the Premier League, representing their most significant source of income. Meanwhile, revenue from matchdays totaled nearly 870 million euros.
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License information was derived automatically
This dataset contains 2022-2023 football player stats per 90 minutes. Only players of Premier League, Ligue 1, Bundesliga, Serie A and La Liga are listed.
+2500 rows and 124 columns. Columns' description are listed below.
Data from Football Reference. Image from Sky Sports.
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Results for group 1 v group 2 balanced data set (Best Average Test Performance = 61.5% and Best Average Test Error = 11.6% with a combination of seven variables) and group 1 v group 2 model variables as means and standard deviations for player groupings.
In 2023/24, Aston Villa had more time added on to matches than any other Premier League club, with an average of 14 minutes and 33 seconds being added on to games. Meanwhile, Luton Town typically only had around eight minutes and 26 seconds of added time.
As of March 17, 2024, Nottingham Forest had the highest net VAR decision score in the Premier League with four. Meanwhile, three clubs had a net VAR decision score of -3: Liverpool, Sheffield United, and Wolverhampton Wanderers.
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Indian Premier League Dataset
This dataset contains info on all of the IPL(Indian Premier League) cricket matches. Ball-by-Ball level info and scorecard info to be added soon. The dataset was scraped in July-2022.
Mantainers:
Somya Gautam Kondrolla Dinesh Reddy Keshaw Soni
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about book series and is filtered where the books is The ups and downs of the Premier League, featuring 10 columns including authors, average publication date, book publishers, book series, and books. The preview is ordered by number of books (descending).
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This dataset was created by Plavak Das
Released under CC0: Public Domain
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
2024-2025 Spanish Ladies Premier League schedule information, for more league information please click: https://www.footballant.com/football-data/league/1186
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The Premier League agrees to roll over its existing domestic broadcast rights agreements for the 2022 to 2025 rights cycle, avoiding what was anticipated to be a further depreciation in the value of the league's domestic media rights. Read More
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La Liga, Spain’s top soccer competition, is widely considered the second biggest domestic soccer property in the world behind the Premier League, with its top sides Barcelona and Real Madrid the most followed and supported around the world. Having been able to ensure a completed season, a worst case scenario of a $1.16 billion loss has been avoided, but challenges still remain in ensuring La Liga’s product remains competitive and desirable to an international audience Read More
This dataset was created by Dean Patel
The displayed data on the interest in Premier League clubs shows results of the Statista European Football Benchmark conducted in England in 2018. Some 26 percent of respondents stated that they are interested in Liverpool F.C..
In the 2023/24 season, the opening month of the Premier League saw the most player injuries, with a total of 100 across all clubs. Meanwhile, peaks were also seen in November and December 2023.
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This dataset was created by zark muckerberg
Released under CC0: Public Domain
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Indian Premier League Hindistan Premier Ligi veya sponsorluk anlaşması gereği TATA IPL Hindistan ın en üst düzey e
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While forecasting football match results has long been a popular topic, a practical model for football participants, such as coaches and players, has not been considered in great detail. In this study, we propose a generalized and interpretable machine learning model framework that only requires coaches’ decisions and player quality features for forecasting. By further allowing the model to embed historical match statistics, features that consist of significant information, during the training process the model was practical and achieved both high performance and interpretability. Using five years of data (over 1,700 matches) from the English Premier League, our results show that our model was able to achieve high performance with an F1-score of 0.47, compared to the baseline betting odds prediction, which had an F1-score of 0.39. Moreover, our framework allows football teams to adapt for tactical decision-making, strength and weakness identification, formation and player selection, and transfer target validation. The framework in this study would have proven the feasibility of building a practical match result forecast framework and may serve to inspire future studies.
This dataset was created by Jaseem Mohammed
It contains the following files: