Practical Applications to Team Sports

Until a couple of years ago, coaching staffs and researchers only could annotate data by hand after observation to evaluate their team or to prepare the following matches through an examination of their opponents’ performance (Lutz et al., 2020; Mackenzie & Cushion, 2013). Today, due to the advanced time-motion EPTS developed jointly by sports scientists and computer science experts (Goes et al., 2020; Memmert et al., 2017; Rein & Memmert, 2016), tactical behavior can be assessed objectively and faster than the time-consuming and outdated manual methods that suffer from analyst’s subjective perceptions (Lutz et al., 2020). EPTS gather positional data that measure movement patterns and inter-player coordination to obtain linear and nonlinear outcomes capable of describing and understanding the tactical behavior and the dynamics of sports teams (Low et al., 2020; Sampaio & Maçãs, 2012). Several authors (Coito et al., 2020; Low et al., 2020; Rein & Memmert, 2016; Sarmento et al., 2018) highlight the growing interest in and the importance of appraising tactical behavior as a step forward in the understanding of the complex, nonlinear, and chaotic organizations of different sports teams. Furthermore, sports scientists and team analysts should go beyond burgeoning academic and scientific research (Sarmento et al., 2018) to apply theoretical knowledge to satisfy coaches’ real-world context needs (Fullagar et al., 2019) and assess tactical competence during the game or the training session (Lutz et al., 2020).

Match collective tactical behavior references can help team managers and research heads assess team performance. The measurement of tactical variables during matches provides the team’s mean reference and the level of order of the dynamics of tactical patterns or the interpersonal coordination pattern synchronization that allows comparison between matches. In addition, team values can be compared with the references of other teams, competition levels, and leagues (Alexander et al., 2019; Fradua et al., 2013; Korte & Lames, 2019;

Rico-González et al., 2021a, 2021b). Coaching staffs and sports scientists should

assess their collective tactical references depending on contextual variables (e.g.,

match status, venue, quality of opposition, or match period) because these factors

constrain the tactical response of the teams (Fernandes et al., 2020; Fernandez-

Navarro et al., 2020; Santos et al., 2017b). In addition, it should be considered that

the coaches’ strategies (e.g., the selection of the team formation) also condition

team tactical behavior (Memmert et al., 2019). As several studies have suggested

(Alexander et al., 2019; Fradua et al., 2013; Korte & Lames, 2019; Rico-González

et al., 2021a, 2021b), the assessment of the team’s tactical response during

weekend official matches serves as a reference to design and select adequate

match-related training strategies and tasks to optimize team performance and prepare them for the next match during the following week.

In regards to the training setting, coaching staffs and sports scientists should

attempt to build representative training environments for players. Taking into

account the prior match reference values, the training tactical response should be

in tune with competitive tactical behavior: to play how you train, you should train

how you want to play. The design of the training tasks (i.e., the structural traits of

the training strategies) should oblige players and the team to tactically respond in

a similar way to the match. For example, coaching staffs should employ match-

derived relative pitch area during SSGs to bring training tasks closer to official

soccer game situations, with larger intra-team distances and more tactical

variability than with traditional small pitch (Olthof et al., 2018). Likewise, in

order to appraise the adequacy of designed training strategies, they could estimate

the consequences (e.g., manipulating soccer players’ space of interaction; Ric et

al., 2017) of wide-ranging interacting constraints (i.e., performer, environment,

and task constraints; Newell, 1986) or the effects of different training programs

(e.g., Skills4Genius; Santos et al., 2017a) on tactical behavior. After all, coaching

staffs and sports scientists could assess tactical behavior during weekly practice

and in weekend matches, so the next step should be to link training and

competition. Despite its complexity, they should assess the effects of the training

process on the match performance with respect to the collective tactical behavior.

Concluding Remarks and Lessons Learned

To optimize the data recorded by EPTS to assess tactical performance, the main criteria to classify tactical behavior should be the social structure of the game, specifically the instrumental motor interaction type and the number of players.

Three type of motor relationships can be assessed during team sports:

Cooperative Motor Interaction (C) Antagonistic Motor Interaction (A)

Cooperative and Antagonistic Motor Interactions (CA)

In addition, other structural traits such as space (e.g., subspace, target, or boundaries) and equipment (i.e., the mobile) parameters should be considered to assess collective tactical behavior.

On a practical level, coaching staffs and sports scientists could assess tactical

behavior during competition and training process by EPTS to link them both,

in order to improve team performance.

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11 Neuromuscular Variables

Carlos D. Gómez-Carmona, José Pino-Ortega and Markel

Rico-González