The obligation to succeed when it matters the most-The influence of skill and pressure on the success in football penalty kicks.

In order to gain a more comprehensive understanding of the influence of skill and pressure on the success in football penalty kicks, we analyzed 1711 penalties taken over a 15-year period in major international tournaments. We conducted a multiple correspondence analysis in order to reduce six variables that are associated with skill and pressure to two dimensions that reflect our target concepts. Then, we used these two factors as independent variables in a logistic regression and fit different models using three binary dependent variables. The results show that high situational pressure significantly increases the probability of missing the goal entirely by about 6%, independent of the player's skill level. The probability that the goalkeeper saves a penalty significantly decreases by roughly 4% when a highly skilled player takes the shot. In general, high situational pressure decreases the probability of scoring a penalty kick. Furthermore, the probability to score a penalty increases if a highly skilled player takes the kick which indicates that a high skill level can act as a kind of buffer against debilitating effects caused by performance pressure.

Substitutions in football - what coaches think and what coaches do.

Substitutions are probably the most important opportunity for football coaches to actively influence a match in progress. The present article presents two studies investigating substitutions in football from two different methodological perspectives: Study I, a survey reporting the opinions of 73 licensed coaches, and Study II, data-based analysis of a total of 41,301 substitutions from 7,230 matches in seasons 2014/15 to 2018/19 of the top four European football leagues. The coaches stated to prefer offensive substitutions over defensive substitutions and additionally indicated that changing the current score was more likely to be a reason for substitution than keeping the score. The analysis of the data revealed that not offensive, but neutral substitutions, where the player is replaced by a player of the same playing position, were most frequent. However, offensive players participated significantly more frequently in substitutions. In addition, a high level of score dependence was found, as more than half of the defensive substitutions were made while winning and more than half of the offensive substitutions were made while losing. The present study sheds light on the substitution behaviour of coaches in football and intends to stimulate discussion on the optimal timing and the type of substitutions.

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.

In-play forecasting in football using event and positional data.

Two highly relevant aspects of football, namely forecasting of results and performance analysis by means of performance indicators, are combined in the present study by analysing the value of in-play information in terms of event and positional data in forecasting the further course of football matches. Event and positional data from 50 matches, including more than 300 million datapoints were used to extract a total of 18 performance indicators. Moreover, goals from more than 30,000 additional matches have been analysed. Results suggest that surprisingly goals do not possess any relevant informative value on the further course of a match, if controlling for pre-game market expectation by means of betting odds. Performance indicators based on event and positional data have been shown to possess more informative value than goals, but still are not sufficient to reveal significant predictive value in-play. The present results are relevant to match analysts and bookmakers who should not overestimate the value of in-play information when explaining match performance or compiling in-play betting odds. Moreover, the framework presented in the present study has methodological implications for performance analysis in football, as it suggests that researchers should increasingly segment matches by scoreline and control carefully for general team strength.

The influence of randomness on goals in football decreases over time. An empirical analysis of randomness involved in goal scoring in the English Premier League.

Performance analysis in football predominantly focuses on systematic contributions to success, thus neglecting the role of randomness. The present paper pursues a direct approach to quantify and analyse randomness in football by identifying random influences in the goal scoring process. The dataset includes all matches from the seasons 12/13 to 18/19 of the English Premier League, adding up to a total of 7,263 goals, that were checked for the occurrence of six variables of random influence. Additionally, the influence of nine situational variables was investigated. Results show that randomness was present for almost 50% of all goals. Moreover, it was demonstrated that the proportion of random goals decreased over the seven seasons (p < .001), is more pronounced for weaker teams (p < .05) as well as if the current scoreline is a draw (p < .05) and depends on the match situation (open play, freekick, corner, penalty). An improved understanding of randomness in football has important implications for both researchers and practitioners. Performance analysts should acknowledge randomness as a crucial factor to distinguish clearly between performance and success. Coaches could even consider the conscious creation of uncontrollable situations as a possible tactic to provoke random influences on goal scoring.

How does spectator presence affect football? Home advantage remains in European top-class football matches played without spectators during the COVID-19 pandemic.

The present paper investigates factors contributing to the home advantage, by using the exceptional opportunity to study professional football matches played in the absence of spectators due to the COVID-19 pandemic in 2020. More than 40,000 matches before and during the pandemic, including more than 1,000 professional matches without spectators across the main European football leagues, have been analyzed. Results support the notion of a crowd-induced referee bias as the increased sanctioning of away teams disappears in the absence of spectators with regard to fouls (p < .001), yellow cards (p < .001), and red cards (p < .05). Moreover, the match dominance of home teams decreases significantly as indicated by shots (p < .001) and shots on target (p < .01). In terms of the home advantage itself, surprisingly, only a non-significant decrease is found. While the present paper supports prior research with regard to a crowd-induced referee bias, spectators thus do not seem to be the main driving factor of the home advantage. Results from amateur football, being naturally played in absence of a crowd, provide further evidence that the home advantage is predominantly caused by factors not directly or indirectly attributable to a noteworthy number of spectators.

Forecasting the outcomes of sports events: A review.

In the scientific community a large literature on sports forecasting exists, covering a wide range of different sports, methods and research questions. At the same time a lack of general literature such as reviews or meta-analyses on aspects of sports forecasting can be attested, partly attributable to characteristics of forecasting in sports that make it difficult to present through systematic approaches. The present study contributes to filling this gap by providing a narrative review about forecasting related to the outcomes of sports events. An overview about relevant topics in forecasting the outcomes of sports events is presented, a basic methodology is discussed and a categorization of methods is introduced. Having a specific focus on forecasting from ratings, we shed light on the difference between systematic and unsystematic effects influencing the outcomes of sports events. Finally an outlook on the expected impact of the increasing amount and complexity of available data on future sports forecasting research is presented. The present review can serve as a valuable starting point for researchers aiming at the investigation of sports-related forecasts, both helping to find appropriate methods and classify their work in the context of the state of research.

Situational and Positional Effects on the Technical Variation of Players in the UEFA Champions League.

This study aimed to identify the situational and positional effects on the variation of players' technical performance in the UEFA Champions League from a long-term perspective. The technical performance of full match observations from outfield players in the UEFA Champions League from season 2009/2010 to 2016/2017 was analysed. The coefficient of variation of each variable of each player in each season was calculated to evaluate the match-to-match variation of technical performance. The variation of technical performance between players was compared across five playing positions and five situational variables using the non-clinical magnitude-based inference. Results showed that variables related to goal scoring, passing and organising from five playing positions showed a relatively higher variation among five competing contexts (ES: -0.72 ± 0.38 - 0.82 ± 0.61). Quality of team, quality of opponent and match outcome showed relatively greater influences than competition stage and match location on the variation of a player's technical performance (ES: -0.72 ± 0.38 - 0.57 ± 0.56). The technical performances of wide players (full backs and wide midfielders) were more variable between the group and knockout stage (ES: -0.37 ± 0.32 - 0.28 ± 0.19). This study provides an important understanding of the associations among the variation of technical indicators, playing positions and situational variables. These profiles of technical variation could be used by coaches and analysts for talent identification, player recruitment, pre-match preparation and post-match evaluation.

Evaluation of the Technical Performance of Football Players in the UEFA Champions League.

This study aimed to assess the technical match performance of top-class football players in a long-term perspective. Technical performance profiles of players according to five playing positions (central defender, full back, wide midfielder, central midfielder, forward) and five situational variables (competition stage, match location, quality of team, quality of opponent, match outcome) were established. Technical match data of players in the UEFA Champions League from season 2009-2010 to 2016-2017 were analyzed. The true effects of positional and situational variables on players' technical performance were evaluated by the non-clinical magnitude-based inference. Results showed that the effect of competition stage on player's performance was negligible. Quality of team, quality of opponent and match outcome revealed the strongest effects on player's performance (ES: -0.42 ± 0.10-0.59 ± 0.10) while the effect of match location was relatively lower (ES: -0.32 ± 0.10-0.23 ± 0.07). The number of variables that showed statistical differences under five competing contexts for wide midfielders and forwards were higher than those of central defenders, full backs, and central midfielders. Differences of players' match performance could mainly be identified in variables related to goal scoring, passing, and organizing, these findings may provide important insights for coaches and analysts during the match preparation and training session.

A serial-position curve in high-performance darts: The effect of visuomotor calibration on throwing accuracy.

The aim of the present research was to test if the fine-tuning of skilled motor actions benefits from proximate previous actions via a visuomotor calibration process. In professional darts, each player cycles through different activities: three darts are thrown with a rather smooth sequence of movements, the darts are retrieved from the dartboard, the other player throws his or her darts and retrieves them, the next three darts are thrown, retrieved, etc. We hypothesized that these cycles give rise to a serial-position curve for the precision of darts as a result of a particular kind of warm-up decrement. Even though the interruptions of actually throwing darts are only in the order of seconds, walking away from the throw line should lead to a loss of fine-tuning of the calibration of movement parameters with respect to targets defined in the external frame of reference of the dartboard. For the players of the 2017 Professional Darts Corporation World Darts Championship (N = 36,168 scores) we confirmed that the first dart of a series of three is indeed less accurate than the subsequent two. This warm-up decrement is particularly pronounced for vertical errors, for which the relation to movement parameters is more complex than for horizontal errors. Fine-tuning of visuomotor calibration is a neglected facet of warm-up that is also important for various other sports such as tennis, basketball, handball, and football.

The Betting Odds Rating System: Using soccer forecasts to forecast soccer.

Betting odds are frequently found to outperform mathematical models in sports related forecasting tasks, however the factors contributing to betting odds are not fully traceable and in contrast to rating-based forecasts no straightforward measure of team-specific quality is deducible from the betting odds. The present study investigates the approach of combining the methods of mathematical models and the information included in betting odds. A soccer forecasting model based on the well-known ELO rating system and taking advantage of betting odds as a source of information is presented. Data from almost 15.000 soccer matches (seasons 2007/2008 until 2016/2017) are used, including both domestic matches (English Premier League, German Bundesliga, Spanish Primera Division and Italian Serie A) and international matches (UEFA Champions League, UEFA Europe League). The novel betting odds based ELO model is shown to outperform classic ELO models, thus demonstrating that betting odds prior to a match contain more relevant information than the result of the match itself. It is shown how the novel model can help to gain valuable insights into the quality of soccer teams and its development over time, thus having a practical benefit in performance analysis. Moreover, it is argued that network based approaches might help in further improving rating and forecasting methods.

Analysis of the predictive qualities of betting odds and FIFA World Ranking: evidence from the 2006, 2010 and 2014 Football World Cups.

The present study aims to investigate the ability of a new framework enabling to derive more detailed model-based predictions from ranking systems. These were compared to predictions from the bet market including data from the World Cups 2006, 2010, and 2014. The results revealed that the FIFA World Ranking has essentially improved its predictive qualities compared to the bet market since the mode of calculation was changed in 2006. While both predictors were useful to obtain accurate predictions in general, the world ranking was able to outperform the bet market significantly for the World Cup 2014 and when the data from the World Cups 2010 and 2014 were pooled. Our new framework can be extended in future research to more detailed prediction tasks (i.e., predicting the final scores of a match or the tournament progress of a team).