The statistic shows the share of Generation Xers who are committed sports fans in the United States as of *********, by sport. During the survey, ** percent of responding Generation Xers stated that they were committed NFL fans.

This statistic shows data on the share of sports fans who watched sports coverage or highlights online in the last month worldwide as of the fourth quarter of 2017, by region. During the survey, ** percent of sports fans from North America stated that they had watched sports coverage or highlights online in the last month.

This statistic shows the leading characteristics of a sports fan, according to NASCAR fans in the United States in 2017. In 2017, ** percent of respondents stated that they believed regularly watching sports on television was a characteristic of a sports fan.

According to a survey conducted in September 2023, Japan's professional basketball had a fandom of about *** million people. Basketball is one of the most popular professional team sports in Japan, after baseball and football. The official league for professional basketball in Japan is called the B-League.

The statistic shows how many of the survey respondents consider themselves a current or former fan of professional football, if at all. During the survey, ** percent of respondents said that they are current fans.

This graph shows the ticket purchase intentions of French sports fans in 2017 for the Olympic Games (OG) 2024 in case of organization in Paris. It can thus be observed that nearly ** percent of French sports enthusiasts intended to obtain places for one of the Olympic disciplines of the Olympic Games 2024 if organized in Paris that year. In addition, in 2016, **% of French people wanted the 2024 Olympics to be organized in Paris .

Context

Most publicly available football (soccer) statistics are limited to aggregated data such as Goals, Shots, Fouls, Cards. When assessing performance or building predictive models, this simple aggregation, without any context, can be misleading. For example, a team that produced 10 shots on target from long range has a lower chance of scoring than a club that produced the same amount of shots from inside the box. However, metrics derived from this simple count of shots will similarly asses the two teams.

A football game generates much more events and it is very important and interesting to take into account the context in which those events were generated. This dataset should keep sports analytics enthusiasts awake for long hours as the number of questions that can be asked is huge.

Content

This dataset is a result of a very tiresome effort of webscraping and integrating different data sources. The central element is the text commentary. All the events were derived by reverse engineering the text commentary, using regex. Using this, I was able to derive 11 types of events, as well as the main player and secondary player involved in those events and many other statistics. In case I've missed extracting some useful information, you are gladly invited to do so and share your findings. The dataset provides a granular view of 9,074 games, totaling 941,009 events from the biggest 5 European football (soccer) leagues: England, Spain, Germany, Italy, France from 2011/2012 season to 2016/2017 season as of 25.01.2017. There are games that have been played during these seasons for which I could not collect detailed data. Overall, over 90% of the played games during these seasons have event data.

The dataset is organized in 3 files:

• events.csv contains event data about each game. Text commentary was scraped from: bbc.com, espn.com and onefootball.com
• ginf.csv - contains metadata and market odds about each game. odds were collected from oddsportal.com
• dictionary.txt contains a dictionary with the textual description of each categorical variable coded with integers

Past Research

I have used this data to:

• create predictive models for football games in order to bet on football outcomes.
• make visualizations about upcoming games
• build expected goals models and compare players

Inspiration

There are tons of interesting questions a sports enthusiast can answer with this dataset. For example:

• What is the value of a shot? Or what is the probability of a shot being a goal given it's location, shooter, league, assist method, gamestate, number of players on the pitch, time - known as expected goals (xG) models
• When are teams more likely to score?
• Which teams are the best or sloppiest at holding the lead?
• Which teams or players make the best use of set pieces?
• In which leagues is the referee more likely to give a card?
• How do players compare when they shoot with their week foot versus strong foot? Or which players are ambidextrous?
• Identify different styles of plays (shooting from long range vs shooting from the box, crossing the ball vs passing the ball, use of headers)
• Which teams have a bias for attacking on a particular flank?

And many many more...

The statistic displays the results of a survey, what traditional sports eSports fans are interested in, in Germany in 2017. During the survey it was found that the majority of responding eSports fans stated that they are interested in football.

This statistic illustrates the travel propensity of Italian sports fans who regularly travelled to sporting events in 2017, broken down by sport type. According to the survey results, about half of respondents (** percent) had travelled or were willing to travel to attend a soccer match, while about *** in **** respondents (** percent) had travelled or were willing to travel to a major sporting event such as the Olympic Games.

The statistic illustrates the types of content accessed on second screen devices by sports fans whilst watching TV in United States in 2017. Of those surveyed, ** percent stated that they used social networks on a second screen whilst watching television.

This graph shows the average age of the TV audience for selected sports in the United States in 2017. According to the source, the average age of the audience watching NHL on television in 2017 was 49 years old.

The statistic shows the share of Generation X who check sports scores and news updates in the United States as of *********, by platform. During the survey, ** percent of responding Generation Xers stated that they checked sports scores and news updates on Facebook.

This statistic shows the result of a survey on the national sport in Denmark in 2017. That year, the majority of respondents stated that they would describe football as the Danish national sport to a foreigner. Compared to that, the share of surveyed Danes naming handball was close, amounting to ** percent.

This statistic displays the share of football fans in China who purchased football or club related products as of 2017. According to the survey result, ** percent of Chinese football fans have purchased brand products associated with football.

This statistic displays the most popular football clubs among Chinese football fans as of 2017, by share of respondents. During the surveyed time period, with ** percent the majority of the respondents stated that their favorite football club was Guangzhou Evergrande Taoabo.

This statistic displays the distribution of the online audience of sportinglife.com in Great Britain (GB) in 2017, by age group. In 2017, ten percent of the online audience of sportinglife.com was aged between 25 and 34 years.

The statistic shows the distribution of the Super Bowl final audience in Italy in 2016 and 2017. As of the survey period, the number of individuals watching the final match increased from about *** percent of the audience in 2016, to *** percent in 2017.

Baseball in South Korea has been popular since the *****, and as of ********, around ** percent of the population stated baseball was their favorite sport. Football or soccer followed closely behind in terms of popularity, with just over half of the population considering themselves fans of the sport.

The KBO League

The KBO League, the most popular sports league in South Korea, includes *** franchises and offers the highest level of baseball in the country. Earning a place in a team in this league is considered very prestigious, with the highest paid players earning between *** to *** billion South Korean won in 2019. The Kia Tigers are the most successful team overall, winning the most championships in the leagues’ almost 40-year history. During the 2018 season, the Doosan Bears had the highest win rate in the league.

Sport spectatorship

The number of people who attended a KBO League match was over **** times greater than those who attended a K-league football match in 2018. This could be largely due to the fact that there were significantly more baseball matches – around *** – during this season compared to soccer matches. As larger and more modern sports complexes are built in South Korea, the attendance numbers for both baseball and football matches in the country looks set to continue to increase.

Jim Rome has the highest net worth of all TV and radio sports commentators. The host of CBS sports radio’s “The Jim Rome Show” has accumulated around 75 million U.S. dollars in his years of commentating. With sports leagues such as the NFL averaging millions of television viewers per year and events like the World Cup ranking among the most watched broadcasts in the world, it’s easy to see how the commentators that discuss these events stand to benefit greatly from their close proximity to the events and the athletes themselves.

Popularity of sports

Whether viewing the games on TV or participating in them first-hand, sports are undoubtedly one of the most popular hobbies in the world. Tens of millions of people participate in organized team sports each year in the U.S., and millions more view or attend games as fans or spectators. The most popular sports differ from country to country, with places like Canada being most interested in ice hockey, while India and Bangladesh prefer cricket.

The sports media industry

The way in which fans view and follow sports has changed drastically from the days where people gathered around a radio to listen to play by play commentators describing the events. Wildly successful sports television networks like ESPN fill their entire 24 hour schedules with sports content, no matter the day or time of year. In more recent years, social media has changed the industry even further. Fans are no longer satisfied with simply watching the sporting events, but also eager to follow the daily lives of their favorite athletes. Famous sports stars are now truly global celebrities, with soccer players like Cristiano Ronaldo, Leo Messi, and Neymar accumulating over 100 million followers on Instagram alone, and hundreds of millions more across various other platforms.

This graph shows the share of TV viewers who are under ** for selected sports the United States in 2017. According to the source, ** percent of the MLS television audience in 2017 was under the age of **.