A big data analysis of Twitter data during premier league matches: do tweets contain information valuable for in-play forecasting of goals in football?

Data-related analysis in football increasingly benefits from Big Data approaches and machine learning methods. One relevant application of data analysis in football is forecasting, which relies on understanding and accurately modelling the process of a match. The present paper tackles two neglected facets of forecasting in football: Forecasts on the total number of goals and in-play forecasting (forecasts based on within-match information). Sentiment analysis techniques were used to extract the information reflected in almost two million tweets from more than 400 Premier League matches. By means of wordclouds and timely analysis of several tweet-based features, the Twitter communication over the full course of matches and shortly before and after goals was visualized and systematically analysed. Moreover, several forecasting models including a random forest model have been used to obtain in-play forecasts. Results suggest that in-play forecasting of goals is highly challenging, and in-play information does not improve forecasting accuracy. An additional analysis of goals from more than 30,000 matches from the main European football leagues supports the notion that the predictive value of in-play information is highly limited compared to pre-game information. This is a relevant result for coaches, match analysts and broadcasters who should not overestimate the value of in-play information. The present study also sheds light on how the perception and behaviour of Twitter users change over the course of a football match. A main result is that the sentiment of Twitter users decreases when the match progresses, which might be caused by an unjustified high expectation of football fans before the match.

Career patterns of marketing managers in top European football clubs

PurposeThe goal of this research was to explore career patterns of senior marketing managers in the best European football clubs (SMMEFCs).Design/methodology/approachThe data came from the LinkedIn profiles of current and past SMMEFCs. Firstly, the optimal matching algorithm was used to determine clusters of pathways leading to a first SMMEFC position based on the main activity of the employing organisation. Secondly, these patterns were compared in terms of variables depicting the career paths, clubs and managers. Finally, the evolution of the post-SMMEFC careers was analysed.FindingsPeople in their first SMMEFC positions are mainly male with a university degree in business and marketing, and with a predominantly functional experience in marketing. There are five ways to become an SMMEFC: through business (40% of the sample), football (32%), other sports (11%), marketing and communication (11%), and media (6%). As the majority of SMMEFCs come to their positions from outside the sporting world, the specificity of the football industry is not a serious obstacle. Instead, the careers are bounded by functional marketing experience. Among the individual sequences leading to a first SMMEFC position, only around half of the football cluster may be considered traditional careers. Football, and sports in general, seem attractive for post-SMMEFC career development for the majority of managers coming from all pathways.Originality/valueThe study is the first one to quantify career patterns in professional sports management. It provides new insights about marketing careers and practice in European club football.

On-Match Impact and Outcomes of Scoring First in Professional European Female Football

Background: Scoring first seems to be a determinant in professional football playing; several factors could influence the development of the match and the outcome. This study aimed to identify which factors could influence scoring first and impact match outcomes in professional European female football. Methods: There were 504 official matches held on 74 match days during the 2018–2019 professional female European football seasons (Primera Iberdrola, D1 Féminine, and Frauen-Bundesliga), analysed using a notational and inferential assessment. Results: There was a direct positive relationship (p < 0.05) between scoring first and winning the match; 75.9% of the winning teams scored first. Moreover, those teams that usually scored first had a better final league classification (p < 0.05). These relationships were not influenced by home or away conditions. Conclusions: Scoring first is a determinant in the outcomes of professional European female football matches. Physical and tactical training and programming should focus on those variables, leading female teams to score first.

Analyzing the Behavior and Financial Status of Soccer Fans from a Mobile Phone Network Perspective: Euro 2016, a Case Study

In this study, Call Detail Records (CDRs) covering Budapest for the month of June in 2016 were analyzed. During this observation period, the 2016 UEFA European Football Championship took place, which significantly affected the habit of the residents despite the fact that not a single match was played in the city. We evaluated the fans’ behavior in Budapest during and after the Hungarian matches and found that the mobile phone network activity reflected the football fans’ behavior, demonstrating the potential of the use of mobile phone network data in a social sensing system. The Call Detail Records were enriched with mobile phone properties and used to analyze the subscribers’ devices. Applying the device information (Type Allocation Code) obtained from the activity records, the Subscriber Identity Modules (SIM), which do not operate in cell phones, were omitted from mobility analyses, allowing us to focus on the behavior of people. Mobile phone price was proposed and evaluated as a socioeconomic indicator and the correlation between the phone price and the mobility customs was found. We also found that, besides the cell phone price, the subscriber age and subscription type also had effects on users’ mobility. On the other hand, these factors did not seem to affect their interest in football.

Domestic League Competitive Balance and UEFA Performance

This paper investigates the relationship between European football league competitive balance and the performance of that league’s participants in UEFA competitions. The evidence suggests that competitive balance measured using performance points fits the performance coefficients of countries participating in the Champions League and Europa League and that a reciprocal model fits the data best. The evidence suggests that marginal improvements in competitive balance can lead to increase of one-third a win for a league’s participants in the Champions League. The increased rewards for UEFA success suggest policies that promote competitive balance have both public and private benefits for clubs.

Examining Stakeholder Outlooks on Football Policing and Security: The Case of Euro 2020

In the case of the 2020 Union of European Football Associations European Championship in men's football (‘Euro 2020’), this article investigates stakeholder perceptions on the ‘policing’ of fans. On a European-wide scale, the policing of fans is a contested topic. Meanwhile, the policing and security efforts required for sport mega-events like Euro 2020, uniquely planned to be staged in 12 different countries, require years of planning and enormous resources. Adding to this, the Championship's timeline was prolonged following the coronavirus disease-2019-related event postponement. Drawing from original insights from documentary research and qualitative interviews conducted before the postponement, this article argues that stakeholders strongly advocated for a communication and dialogue-based approach to fans. More specifically for Euro 2020, consistency in the policing approaches across all 12 countries was highlighted by stakeholders as being of paramount importance for fans’ security perceptions. The study thus extends existing insights into football policing and the wider understanding of security and policing in the present-day world.

Investigation into the efficiencies of European football clubs with bi-objective multi-criteria data envelopment analysis

A financially successful football club can achieve sporting achievements as well as become financially stable. From this point of view, in this study, the efficiencies of clubs were investigated with the Bi-Objective Multi-Criteria Data Envelopment Analysis (BiO-MCDEA) model by using financial and sporting data of the 2015-2016, 2016-2017 and 2017-2018 seasons of 10 football clubs in the Big-Five League which is the locomotive of the football industry. In the study, the number of social media followers, the average number of viewers and total market value were used as input, and the UEFA club score and total revenues were used as output. As a result, Arsenal, Paris Saint-Germain, and Juventus were determined as efficient in the 2015-2016 season, Paris Saint-Germain and Liverpool in the 2016-2017 season, Manchester United, Paris Saint-Germain and Chelsea in the 2016-2017 season. The reasons as to why Paris Saint-Germain was efficient in all three seasons were also examined. In addition, in the sensitivity analysis conducted to determine the effect of inputs and outputs on the model, it was concluded that efficiency was highly related to financial data.

Downtrends in Offside Offenses Among ‘The Big Five’ European Football Leagues

This study examined the evolution of offside offenses and pass performance across a 10-season period in the top five European soccer leagues. Match performance observations (n = 18 259) were analysed for emergent trends. Two-way ANOVA analyses revealed significant league and seasonal differences among the five leagues (medium effect size). The total offside offenses committed during a match experienced a clear decline during the 10 seasons. In contrast, moderate increases were evident for all passing differential variables. Offside offenses per match were higher in the German Bundesliga and Spanish La Liga than in the English Premier League and France Ligue 1. However, the English Premier League had the greatest value in the touch differential, pass differential, successful pass differential, and key pass differential among all leagues. It is important to note that the number of offside offenses fell after the implementation of VAR.