Tactical Metrics Research Articles

Professional soccer practitioners' perceptions of using performance analysis technology to monitor technical and tactical player characteristics within an academy environment: A category 1 club case study.

This study aimed to identify professional soccer practitioners' perceptions of the application of performance analysis technology within a single academy club. Secondary aims were to understand the importance that practitioners place on monitoring technical and tactical player characteristics, current practices, and barriers to implementing wearable technology. Utilising a mixed method design, forty-four professional soccer academy practitioners (Age = 32 ± 5.8; Years of experience = 8.5 ± 6.2) completed an online survey intended to examine present trends, professional practices, and perceptions regarding the monitoring of technical and tactical metrics. Frequency and percentages of responses for individual items were calculated. Subsequently, eleven participants who were directly involved with the monitoring of players were recruited to participate in a semi-structured interview. Interview data was transcribed and analysed using a combination of deductive and inductive approaches to identify key themes. The main findings across both phases of the study were that (1) technical and tactical metrics are monitored more frequently in matches (Technical: 89%; tactical: 91%) than training (Technical: 80%; Tactical 64%), predominantly due to time constraints and staffing numbers. Accordingly, practitioners believe that it would be beneficial to have an automated way of tracking technical (79%) and tactical (71%) metrics and would consider using a foot-mounted IMU to do so (technical (68%) and tactical (57%)). (2) Monitoring technical and tactical metrics is beneficial to assist with player development and to enrich feedback provision (3) Key stake holders, coaches and players should be informed of the relevance and rationale for monitoring. (4) For successful implementation and continued uptake, the information delivered needs to be both meaningful and easy to understand. Findings suggest that although participants appreciate the need to collect technical and tactical metrics, they are keen to ensure that wearable-derived data does not replace experiential and contextual knowledge. Accordingly, practitioners need to work closely with coaches to determine the contexts in which metrics may or may not prove useful. However, as the sample comprised of participants from a single academy, further studies including more practitioners are warranted. Likewise, future research could also extend to include academy soccer players perceptions too.

Team Dynamics, Running, and Skill-Related Performances of Brazilian U11 to Professional Soccer Players During Official Matches.

Palucci Vieira, LH, Aquino, R, Moura, FA, Barros, RMLd, Arpini, VM, Oliveira, LdP, Bedo, BLdS, and Pereira Santiago, PR. Team dynamics, running, and skill-related performances of Brazilian U11 to professional soccer players during official matches. J Strength Cond Res 33(8): 2202-2216, 2019-Analyses of movements during soccer competition have been used previously to help develop conditioning programs. However, this has not been extensively studied in youth populations. Therefore, the purposes of this study were to examine (1) dynamics of collective tactical movements, (2) running, and (3) skill-related performances during soccer matches disputed by children to senior players. A total of 120 Brazilian players in the age groups U11, U13, U15, U17, U20, and professional (PRO) were monitored during official competition matches (N = 12). Using semiautomatic video-based tracking (30 Hz), match running variables including total distance traveled, average speed, maximum sprint speed, and high-intensity activities were evaluated. Tactical metrics were computed as team surface area, spread, and median frequency. Through notational analysis, technical skills such as involvements with the ball, passes, ball touches, duels, and goal attempts were also recorded. One-way analysis of variance and magnitude-based inferences were used to detect differences between ages. Although the average speed, team surface area, and spread tended to present stabilized increases from the U15 (e.g., U15 > U13 > U11), maximal sprinting speed (PRO > U17 > U15, U13, U11) and percentage at very high-intensity activities (U20 > PRO, U17 > U15 > U13 > U11) demonstrated continuous gains. Median frequencies were higher in the younger groups (U13, U15, U17 > U20, PRO), although the percentage of successful passes was higher in the older groups (PRO > U17, U15 > U13, U11). We concluded that Brazilian U11 to PRO players present different performance profiles for running, collective movement dynamics, and technical skills, and that the rate of development regarding these components varies. Coaches should be aware of these differences to select and adapt training content for each age group.

Linear vs. non-linear classification of winners, drawers and losers at FIFA World Cup 2014

ABSTRACTPurpose: Tactical analyses to distinguish between football teams that were more or less successful have been conducted up to now only by means of linear methods (like discriminant analysis). Concerning the non-linear relationships between performance related conditions, performance and success in sports games, a non-linear method could be more appropriate.Methods & Results: Therefore, all knockout matches played during FIFA World Cup 2014 were analysed using tactical metrics. Results lead to 4 different dimensions (Transition play, Creating scoring opportunities, Defense and Scoring) from which especially the latter was essential to differentiate between winners, drawers and losers. Linear discriminant analysis identified 43.30% of the cases correctly whereas a non-linear artificial neural network (ANN) lead to a successful classification of 57.85% all together.Conclusion: Considering that the differences concerning the tactical behaviour between more and less successful teams were small due to the homogeneous level of performance, the results of the discrimination by means of artificial neural networks indicate non-linear to be more adequate compared to linear methods for future analyses of sports games.Practical Implications: For sport scientists: The results of our study indicate a superior classification by means of the non-linear model of Artificial Neural Networks compared to the linear model of Discriminant Analysis. Therefore, it is suggested that these kind of analyses may be suited better to model the complex relations between performance indicators and match success in sports games.For sport practitioners: It is shown that the behaviour during scoring is by far most important for differentiating between more or less successful teams in FIFA World Cup 2014. Different teams used different playing styles, that were equally successful, to create scoring opportunities. But there is no way around a good ratio between goals and scoring opportunities. This implies that either successful teams take shots only from situations that are more promising or they are more successful in scoring in equally promising opportunities.

Tactical metrics that discriminate winning, drawing and losing teams in UEFA Euro 2012®

ABSTRACTThe objectives of this article are twofold: first, an innovative approach to notational analysis in football is outlined. By considering the important theoretical requirements for the analysis of sports games (like the interaction between two parties, the procedural sequence of action or the significance of tactical behaviour) the meaning of the introduced parameters, called tactical metrics, is illustrated. In a second step, the validity of this approach is tested using matches of the Union of European Football Associations (UEFA) Euro 2012® to investigate a connection between these metrics and success. The results show that 11 tactical metrics model tactical behaviour in 4 different dimensions (game speed, transition play after ball recovery, transition play after ball loss and offence efficiency (OE)). Discriminant analysis based on the factor values leads to a correct classification of 64.8% identifying winners, losers and drawers. This successful discrimination reveals a connection between match success and the presented metrics. Especially, the transition play after losing the ball and the OE seem to be factors connected directly with the result of a match, since those were important values for a successful discrimination. Furthermore, the procedural description of tactical behaviour provides the opportunity to conduct meaningful recommendations for the training and coaching process.

Developing a tactical metric to estimate the defensive area of soccer teams: The defensive play area

This study proposes a computational method to inspect the tactical position of players during the match and a new metric to analyse the defensive pressure made by a soccer team. These metrics only require Cartesian information about the players’ positions on the field. As a case study, three matches played by the same professional soccer team were considered, including variables computed for the half of the match (first half vs second half) and the final score of the game for an analysis of variance of tactical performance, trying to identify the influence of such variables on the collective organisation. The data were collected at 1 Hz and from this process, 9218 instances of useful time were collected. The results revealed that the different kinds of final scores had significant effects on the tactical performance. The comparison between two halves of the match revealed significant differences with a small effect size on tactical performance. In summary, this study showed that these new tactical metrics can be a computational option to increase a coaches’ knowledge about the defensive organisation of soccer teams, giving them the possibility to augment their own perception with metrics that can provide specific information.

Soccer team’s tactical behaviour: Measuring territorial domain

New tactical metrics have been introduced in the last years to allow an understanding on the collective behaviour behind the results provided by notational analysis. Thus, the aim of this article was to propose a new application developed on MATLAB to understand the territorial domain of teams during the game based on players’ position and using such data analyse sectors with more variability considering the advantage or disadvantage of team players during a single match as proof of concept. As methodological approach, a total of 1508 instants of a 7-a-side soccer game were analysed. The herein proposed MATLAB application allows obtaining the differences between players from Team A and Team B. Moreover, the approximate entropy is used to assess the variability of each of the 12 field sectors. The results show that the sector with higher variability is the central offensive midfield (1.114), closely followed by the central defensive midfield (1.033). A more dynamic rapport of strength within the central sectors may be the explanation for such a higher variability. In conclusion, this study presented a new and effective application to analyse the territorial domain that can be matched with automatic tracking systems to improve their online potential.

Measuring Tactical Behaviour Using Technological Metrics: Case Study of a Football Game

In football, the tactical behaviour of a team is related to the state of ball possession, i.e., the defensive and offensive phases. The aim of this study was to measure the tactical responses of two opposing teams in the moments with and without ball possession, thus trying to identify differences in results arising from tactical metrics such as weighted centroid position, weighted stretch index, surface area and effective area of play. The herein presented results show statistical differences in both teams, either with or without the ball possession, for the -axis centroid ( p-value ≤ 0.001), -axis centroid ( p-value ≤ 0.001), stretch index ( p-value ≤ 0.001), surface area ( p-value ≤ 0.001) and effective area of play ( p-value ≤ 0.001). Such results confirm that teams react depending upon ball's possession, respecting the tactical principles of width and length, as well as the unit in the offensive phase with ball possession, and also the concentration and defensive unit in the moments without ball possession.

An Online Tactical Metrics Applied to Football Game

In collective sports, the match analysis is fundamental in order to improve the quality of coaches’ intervention. Nevertheless, the generality of the systems are based on notational analysis which does not allow a deep understanding about the collective behaviour of the team. Therefore, the main goal of this study is to update and design new tactical metrics that allows an improved online knowledge about the teams’ behaviour. Tactical metrics such as the teams’ centroid, teams’ stretch index and teams’ effective play area will be presented throughout this study, validated by means of a single match experimental case study. Results suggest the potential of the herein proposed tactical metrics, providing relevant and online information to the coaches over time, thus allowing new opportunities to improve the quality of their intervention.

Towards A New Method to Analyze The Soccer Teams Tactical Behaviour: Measuring The Effective Area of Play

Recently, new tactical metrics have been developed to increase the match analysis' potential. Naturally, innovate metrics need some updates in order to improve the utility to the soccer coaches. Thus, this paper aims to update the surface area metric, proposing the effective area of play given some efficacy information's about team players' positioning. Furthermore, aim analyzes the effective area of play of each team depending on the state of ball possession and a full match of 7-a-side soccer game in the district final was also analysed. Results showed an inverse correlation between teams' opposite effective areas of play(r p = -0.681), suggesting the expansion-contraction relationship. Furthermore, was analyzed statistical differences with large effect between the moments with and without ball possession for the team A (F (1; 1506) = 1343.893; p-value ≤ 0.001; η 2 = 0.472; Power = 1.000) and B (F (1; 1506) = 968.500; p-value ≤ 0.001; η 2 = 0.391; Power = 1.000).

Performance Metric Portfolios: A Framework and Empirical Analysis

The widespread adoption of supply chain management principles suggests that managers recognize the importance of evaluating operational decisions holistically. However, it is often difficult to link specific operational practices to strategic level outcomes and in turn to corporate financial results. This presents problems for both managers and academic researchers attempting to justify the often high cost of operational improvement initiatives in terms of objective accounting metrics. This study provides evidence that it is possible to demonstrate linkages between carefully chosen portfolios of tactical, strategic, and financial metrics. Survey data from 118 manufacturers are used to evaluate hypotheses linking multilevel metrics of performance across three well‐established strategic foci. We present portfolios of metrics drawn from the literature and from the Supply Chain Counciľs supply‐chain operations reference model and related design and customer chain models. Our analysis suggests that metric portfolios in which tactical metrics are designed to match strategic‐level metrics, based on alignment with a specific strategic focus, provide clearer mechanisms for understanding performance linkages.