Design and Validation of a New Tennis-Specific Reactive Agility Test-A Pilot Study

Agility is an important ability for tennis players, but there is an evident lack of studies focusing on the applicability of tennis-specific agility tests that capture a combination of the physical and cognitive agility performance. Therefore, the main aim of this study was to design and test measurement properties of the tennis-specific reactive agility test that would be feasible and practical for regular implementation. A total of 32 youth tennis players (21 males and 11 females; 10.85 ± 1.50 years) participated in this study. The measurement characteristics of the newly designed reactive agility tennis-specific (TS-RAN) test have been established by comparing it with two generic agility tests and with two tennis-specific pre-planned agility tests. The overall reliability of the new TS-RAN test can only be considered "moderate to good", as although the results of participants showed good internal consistency, the within-subject reliability of the test proved to be unsatisfactory, since the participants showed a lack of performance consistency. This is not unexpected considering the very young age of the participants who performed the test for the very first time. The new TS-RAN test was highly projected (0.91) on the same single latent dimension, with the variance predominately explained by the tennis-specific agility tests. The test's greatest strength is its high feasibility, since the test does not require any special set-up nor technical equipment, and that makes it practical for regular implementation in a practical setting. Further research studies are needed in order to confirm the test's potential to be widely accepted and used.

A Review of Methods for Estimating Algorithmic Complexity: Options, Challenges, and New Directions

Some established and also novel techniques in the field of applications of algorithmic (Kolmogorov) complexity currently co-exist for the first time and are here reviewed, ranging from dominant ones such as statistical lossless compression to newer approaches that advance, complement and also pose new challenges and may exhibit their own limitations. Evidence suggesting that these different methods complement each other for different regimes is presented and despite their many challenges, some of these methods can be better motivated by and better grounded in the principles of algorithmic information theory. It will be explained how different approaches to algorithmic complexity can explore the relaxation of different necessary and sufficient conditions in their pursuit of numerical applicability, with some of these approaches entailing greater risks than others in exchange for greater relevance. We conclude with a discussion of possible directions that may or should be taken into consideration to advance the field and encourage methodological innovation, but more importantly, to contribute to scientific discovery. This paper also serves as a rebuttal of claims made in a previously published minireview by another author, and offers an alternative account.