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.

Recent research suggests that match-to-match variation adds important information to performance descriptors in team sports, as it helps measure how players fine-tune their tactical behaviours and technical actions to the extreme dynamical environments. The current study aims to identify the differences in technical performance of players from strong and weak teams and to explore match-to-match variation of players' technical match performance. Performance data of all the 380 matches of season 2012-2013 in the Spanish First Division Professional Football League were analysed. Twenty-one performance-related match actions and events were chosen as variables in the analyses. Players' technical performance profiles were established by unifying count values of each action or event of each player per match into the same scale. Means of these count values of players from Top3 and Bottom3 teams were compared and plotted into radar charts. Coefficient of variation of each match action or event within a player was calculated to represent his match-to-match variation of technical performance. Differences in the variation of technical performances of players across different match contexts (team and opposition strength, match outcome and match location) were compared. All the comparisons were achieved by the magnitude-based inferences. Results showed that technical performances differed between players of strong and weak teams from different perspectives across different field positions. Furthermore, the variation of the players' technical performance is affected by the match context, with effects from team and opposition strength greater than effects from match location and match outcome.

The aim of the present study was to identify the importance of basketball performance indicators in predicting the effectiveness of ball possessions in men's and women's basketball, when controlling for situational variables and game periods. The sample consisted of 7234 ball possessions, corresponding to 40 games from the Spanish professional leagues. The effects of the predictor variables on successful ball possessions according to game period were analysed using binary logistic regressions. Results from men's teams show interactions with number of passes and ending player during the first five minutes, with starting and ending zone, defensive systems, screens used and possession duration during the middle thirty minutes, and there were interactions with passes used, possession duration and players involved during the last five minutes. Results from women's teams show interactions with starting and ending zone, passes used, defensive systems and ending player during the first five minutes, and with starting and ending zone, and screens used during the middle thirty minutes. The results show no interaction with situational variables in men's basketball, while league stage was important during the middle thirty minutes and last five minutes in women's basketball, whereas match status was only important during the last five minutes.

Ensuring adequate levels of training and recovery at the elite level of professional soccer to maximise player performance has continued to drive the necessity to monitor the training load and physical training output of soccer players. The aim of this investigation was to analyse a training mesocycle whilst quantifying positional demands imposed on elite European soccer players. Sixteen players were assessed using global positioning systems and ratings of perceived exertion over a competitive training six-week mesocycle period. The positional demands and training loads were analysed in addition to match conditions (match location, match score) and player's age. Results from the investigation revealed that typical daily training loads (i.e. total distance, high-intensity distance, sprint distance, average speed, ratings of perceived exertion) did not differ throughout each week of the mesocycle in-season period. Further analysis revealed training loads were significantly lower on match day-1 when compared to training loads on match day-2, match day-3 and match day-4 preceding a match (p < 0.05). Significant differences in physical outputs were also found between match day-2, match day-3 and match day-4 highlighting a structured periodised tapered approach (p < 0.05). Lower average speeds were reported in training post-successful matches compared to defeats (p < 0.05), and more specifically when a match was played away compared to home fixtures (p < 0.05). To conclude, practitioners can maintain a uniformed and structured training load mesocycle whilst inducing variation of the physical outputs during the microcycle phase. Additionally, the investigation also provides a tapering approach that may induce significant variation of the positional demands.

Identifying match events that are related to match outcome is an important task in football match analysis. Here we have used generalised mixed linear modelling to determine relationships of 16 football match events and 1 contextual variable (game location: home/away) with the match outcome. Statistics of 320 close matches (goal difference ≤ 2) of season 2012-2013 in the Spanish First Division Professional Football League were analysed. Relationships were evaluated with magnitude-based inferences and were expressed as extra matches won or lost per 10 close matches for an increase of two within-team or between-team standard deviations (SD) of the match event (representing effects of changes in team values from match to match and of differences between average team values, respectively). There was a moderate positive within-team effect from shots on target (3.4 extra wins per 10 matches; 99% confidence limits ±1.0), and a small positive within-team effect from total shots (1.7 extra wins; ±1.0). Effects of most other match events were related to ball possession, which had a small negative within-team effect (1.2 extra losses; ±1.0) but a small positive between-team effect (1.7 extra wins; ±1.4). Game location showed a small positive within-team effect (1.9 extra wins; ±0.9). In analyses of nine combinations of team and opposition end-of-season rank (classified as high, medium, low), almost all between-team effects were unclear, while within-team effects varied depending on the strength of team and opposition. Some of these findings will be useful to coaches and performance analysts when planning training sessions and match tactics.