The aim of this study was to examine the effects of match location, quality of opposition, and match status on possession strategies in a professional Spanish football team. Twenty-seven matches from the 2005–2006 domestic league season were notated post-event using a computerized match analysis system. Matches were divided into episodes according to evolving match status. Linear regression analysis showed that possession of the ball was greater when losing than when winning (P < 0.01) or drawing (P < 0.05), and playing against strong opposition was associated with a decrease in time spent in possession (P < 0.01). In addition, weighted mean percentage time spent in different zones of the pitch (defensive third, middle third, attacking third) was influenced by match status (P < 0.01) and match location (P < 0.05). A combination of these variables and their interactions can be used to develop a model to predict future possession in football. The findings emphasize the need for match analysts and coaches to consider independent and interactive potential effects of match location, quality of opposition, and match status during assessments of technical and tactical components of football performance. In particular, the findings indicate that strategies in soccer are influenced by match variables and teams alter their playing style during the game accordingly.

The Use of Match Statistics that Discriminate Between Successful and Unsuccessful Soccer Teams: Three soccer World Cups were analysed with the aim of identifying the match statistics which best discriminated between winning, drawing and losing teams. The analysis was based on 177 matches played during the three most recent World Cup tournaments: Korea/Japan 2002 (59), Germany 2006 (59) and South Africa 2010 (59). Two categories of variables were studied: 1) those related to attacking play: goals scored, total shots, shots on target, shots off target, ball possession, number of off-sides committed, fouls received and corners; and 2) those related to defence: total shots received, shots on target received, shots off target received, off-sides received, fouls committed, corners against, yellow cards and red cards. Discriminant analysis of these matches revealed the following: (a) the variables related to attacking play that best differentiated between winning, drawing and losing teams were total shots, shots on target and ball possession; and (b) the most discriminating variables related to defence were total shots received and shots on target received. These results suggest that winning, drawing and losing national teams may be discriminated from one another on the basis of variables such as ball possession and the effectiveness of their attacking play. This information may be of benefit to both coaches and players, adding to their knowledge about soccer performance indicators and helping to guide the training process.

A Review on the Effects of Soccer Small-Sided Games: Over the last years there has been a substantial growth in research related to specific training methods in soccer with a strong emphasis on the effects of small-sided games. The increase of research in this topic is coincident with the increase of popularity obtained by specific soccer conditioning, which involves training players to deal with soccer match situations. Given the limited time available for fitness training in soccer, the effectiveness of small-sided games as a conditioning stimulus needs to be optimized to allow players to compete at the highest level. Available studies indicate that physiological responses (e.g. heart rate, blood lactate concentration and rating of perceived exertion), tactical and technical skill requirements can be modified during small-sided games by altering factors such as the number of players, the size of the pitch, the rules of the game, and coach encouragement. However, because of the lack of consistency in small-sided games design, player fitness, age, ability, level of coach encouragement, and playing rules in each of these studies, it is difficult to make accurate conclusions on the influence of each of these factors separately.

Identifying match statistics that strongly contribute to winning in football matches is a very important step towards a more predictive and prescriptive performance analysis. The current study aimed to determine relationships between 24 match statistics and the match outcome (win, loss and draw) in all games and close games of the group stage of FIFA World Cup (2014, Brazil) by employing the generalised linear model. The cumulative logistic regression was run in the model taking the value of each match statistic as independent variable to predict the logarithm of the odds of winning. Relationships were assessed as effects of a two-standard-deviation increase in the value of each variable on the change in the probability of a team winning a match. Non-clinical magnitude-based inferences were employed and were evaluated by using the smallest worthwhile change. Results showed that for all the games, nine match statistics had clearly positive effects on the probability of winning (Shot, Shot on Target, Shot from Counter Attack, Shot from Inside Area, Ball Possession, Short Pass, Average Pass Streak, Aerial Advantage and Tackle), four had clearly negative effects (Shot Blocked, Cross, Dribble and Red Card), other 12 statistics had either trivial or unclear effects. While for the close games, the effects of Aerial Advantage and Yellow Card turned to trivial and clearly negative, respectively. Information from the tactical modelling can provide a more thorough and objective match understanding to coaches and performance analysts for evaluating post-match performances and for scouting upcoming oppositions.

In research on the importance of the possession of the ball in soccer, little attention has been paid to its determinants. Using data from 170 matches of the 2003 – 2004 Spanish Soccer League, we explain why differences in the possession of the ball among teams are so great. In particular, four variables are examined: evolving match status (i.e. whether the team is winning, losing or drawing), venue (i.e. playing at home or away), and the identities of the team and the opponent in each match. Results of linear regression analysis show that these four variables are statistically significant and together explain most of the variance in possession. In short, home teams have more possession than away teams, teams have more possession when they are losing matches than when winning or drawing, and the identity of the opponent matters – the worse the opponent, the greater the possession of the ball. Combinations of these variables could be used to develop a model that predicts possession in soccer.

Ball Possession Strategies in Elite Soccer According to the Evolution of the Match-Score: the Influence of Situational Variables: In soccer, the ability to retain possession of the ball for prolonged periods of time has been suggested to be linked to success. The accuracy of this assertion was investigated by examining 380 matches involving Spanish League First Division teams during the 2008-2009 season. Possession of the ball, according to the status of the match (winning, drawing and losing), was recorded during the different matches using a multiple-camera match analysis system (Gecasport®). The results suggest that the best classified teams maintained a higher percentage of ball possession and that their pattern of play was more stable. The coefficient of variation, with respect to ball possession per match, was smaller for the best placed teams. Indeed, first placed F.C. Barcelona had the smallest coefficient of variation for possession time (8.4%), while bottom placed Recreativo showed the highest values with 17.1%. Linear regression analysis showed that possession strategies were influenced by situation variables. Team possession was greater when losing than when winning (p<0.01) or drawing (p<0.01), home teams enjoyed greater possession than visiting teams (p<0.01), and playing against strong opposition was associated with a reduction in time spent in possession (p<0.01). The findings indicate that strategies in soccer are influenced by situational variables and that teams alter their playing style accordingly during the match.