At the beginning of the 20th century, the American naturalist William Beebe encountered a strange sight in the jungle of Guyana. A group of soldier ants moved in a large circle. The circle had a circumference of more than 365 meters. Each ant took two and a half hours to complete the circuit. All the ants went round and round the circle for more than two days until most of them fell dead.

This phenomenon is called ant mill. When the ants lose track of pheromones, they begin to follow each other, forming a spinning circle. The ants in this circle will walk until they die of exhaustion. This is a side effect of the self-organized structure of ant colonies. Each ant only knows how to follow the ant in front of it. This will work until something goes wrong and a swirl of ants forms.

Self-organization is a process in which the pattern at the global level arises only from numerous interactions between the components of the lower levels of the system. Furthermore, the rules that specify the interactions between system components are executed using only local information, without reference to the global pattern (Glacier and Robins, 2013)

In this type of process, the members of the system work with some kind of understanding between them, without external orders. The patterns observed at the higher levels of organization (brain, thinking, etc.) emerge only from the numerous, non-linear interactions between the individuals or subsystems that make up the lower levels (neurons).

Unlike ants, athletes are capable of acquiring information both from the environment where they act, and from the global system, although this information can be interpreted incorrectly. Self-organization results in a structure that does not come from a single plane, is not pre-designed and is strongly affected by local interactions. The term self-organization can be confusing in human systems. This idea enhances the figure of other actors in the system (such as coaches) who would generate information channels that can condition the athlete’s performance. A wide range of factors contribute to the athletic outcome: leadership, history, context, relationships and existing relationships. patterns and processes (Boulton, Allen and Bowman, 2015).

In a self-organized system, the work of the feedback loops is key. Thus, positive feedback loops well coupled with negatives function as a powerful mechanism to create structures and patterns in many physical, biological, economic, etc. systems. (García-Manso et al, 2010)

Each athlete is unique and their techniques sometimes radically differ from those considered conventional. This particularity is an example of an organized chaos caused by the characteristics of an athlete, in interaction with the environment and in response to a specific task (constraints). Athletes need repetitions without repetition (according to the classic Bernstein concept) in a realistic context to learn to move technically to all their possibilities. In this way they learn to couple their perception (information) and action (movement) and can reflect on their mistakes and successes. They must be able to (inter) act under pressure in a limited time when there is less time for analysis.

When the environment changes, the behavior increases its chances of changing as well, and when the environment remains stable (eg, similar opponents, similar constraints), exploratory behavior ceases and so does the emergence of new synergies. The diversification / complexification process is self-organized and cannot be pre-programmed. (Pol et al 2020)

This phenomenon represents an inherent quality of athletes with the best achievements and records. The human body has self-organized physiological systems at different levels, including the level of brain activity, providing visual perception of harmonious movements in periods of training and competition and representing the basis for the implementation of pedagogical ideas, receiving a powerful tool for the achievement of the purposes.

In a recent study, Limonta et al (2020) sought to compare the performance between on sight and red point routes and to evaluate how its interpretation varies before and after each modality.

On Sight climbing is the most demanding as it involves a greater physiological and psychological commitment. The ability to interpret the route and the ability to solve pre-ascent problems are essential skills necessary to optimize performance.

16 advanced climbers (OS 7a + / 7b +, RP 7b + / 8a) were evaluated in a on sight route and the repetition of the same the following week. Before and after each ascent, the climbers were evaluated on the ability to interpret the route (RI) and sequence of movements to measure their state of anxiety through a questionnaire (CSAI-2). In turn, performance was measured through climbing time, perceived exercise sensation (RPE), lactate, and heart rate.

As expected, there was an improvement in the performance of res point in relation to on sight when reaching higher (more holds) and for a shorter ascent time. There were fewer exploratory movements and inappropriate stops. The prediction of the amount of movements prior to the two climbing modalities was consistent with the result obtained.

Peak heart rate was significantly lower, as was blood lactate. This may be due to better optimization of movements. The perceptual parameters followed the same pattern: the RPE was lower in the red point modality, the cognitive and somatic anxiety were lower and the self-confidence higher.

The collection of information in lead climbing and in the different stages of a bouldering competition, in which the rotation periods are stipulated by regulation is a fundamental aspect to take into account in training, expanding the repertoire and improving the ability to self-organize in the most diverse situations.

References:

Boulton, JG., Allen PM, and Bowman C. (2015). Embracing complexity: strategic perspectives for an age of turbulence. OUP Oxford, 2015. 

García-Manso, J.M., & Martín-González, J.M., & Da Silva-Grigoletto, M.E. (2010). Los sistemas complejos y el mundo del deporte. Revista Andaluza de Medicina del Deporte, 3(1),13-22

Khadartsev A, A, Nesmeyanov A, A, Eskov V, M, Filatov M, A, Pan W (2017) Fundamentals of Chaos and Self-Organization Theory in Sports. Integr Med Int 2017;4:57-65. doi: 10.1159/000458153

Limonta, E., Fanchini, M., Rampichini, S., Cé, E., Longo, S., Coratella, G., & Esposito, F. (2020). On-Sight and Red-Point Climbing: Changes in Performance and Route-Finding Ability in Male Advanced Climbers. Frontiers in psychology, 11, 902.

Passos, P., Araújo, D., & Davids, K. (2013). Self-organization processes in field-invasion team sports : implications for leadership. Sports medicine (Auckland, N.Z.), 43(1), 1–7.

Pol, R., Balagué, N., Ric, A. et al. (2020) Training or Synergizing? Complex Systems Principles Change the Understanding of Sport Processes. Sports Med – Open 6, 28