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2023
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Open Access
Editorial: factors affecting performance and recovery in team sports: a multidimensional perspective, Volume II
Trecroci A., Formenti D., Moran J., Pedreschi D., Cavaggioni L., Rossi A.
Source: Frontiers in physiology 14 (2023). doi:10.3389/fphys.2023.1166761
DOI: 10.3389/fphys.2023.1166761
Project(s): SoBigData-PlusPlus
Metrics:
Trecroci A., Formenti D., Moran J., Pedreschi D., Cavaggioni L., Rossi A.
Source: Frontiers in physiology 14 (2023). doi:10.3389/fphys.2023.1166761
DOI: 10.3389/fphys.2023.1166761
Project(s): SoBigData-PlusPlus
Metrics:
See at:
ISTI Repository 
| www.frontiersin.org | CNR ExploRA
2011
Report
Unknown
A1.1.1 Lo stato dell'arte: tecnologia ed utenti
Falchi Fabrizio, Ippolito Valentina, Loschiavo Domenico, Lucchese Claudio, Lungarotti Francesca, Melani, Alessio, Minelli, Sam, Pialli Saverio, Rossi Silvia, Salvadori Sauro, Scartoni Rita, Scopigno Roberto, Tavanti Francesca, La Torre Francesco, Venturini Rossano
This document reports the state of the art related to the technologies of interest of the VISITO Tuscany projectSource: Project report, VISITO Tuscany, 2011
Falchi Fabrizio, Ippolito Valentina, Loschiavo Domenico, Lucchese Claudio, Lungarotti Francesca, Melani, Alessio, Minelli, Sam, Pialli Saverio, Rossi Silvia, Salvadori Sauro, Scartoni Rita, Scopigno Roberto, Tavanti Francesca, La Torre Francesco, Venturini Rossano
This document reports the state of the art related to the technologies of interest of the VISITO Tuscany projectSource: Project report, VISITO Tuscany, 2011
See at: CNR ExploRA
2022
Journal article
Open Access
Extended energy-expenditure model in soccer: evaluating player performance in the context of the game
Skoki A., Rossi A., Cintia P., Pappalardo L., Stajduhar I.
Every soccer game influences each player's performance differently. Many studies have tried to explain the influence of different parameters on the game; however, none went deeper into the core and examined it minute-by-minute. The goal of this study is to use data derived from GPS wearable devices to present a new framework for performance analysis. A player's energy expenditure is analyzed using data analytics and K-means clustering of low-, middle-, and high-intensity periods distributed in 1 min segments. Our framework exhibits a higher explanatory power compared to usual game metrics (e.g., high-speed running and sprinting), explaining 45.91% of the coefficient of variation vs. 21.32% for high-, 30.66% vs. 16.82% for middle-, and 24.41% vs. 19.12% for low-intensity periods. The proposed methods enable deeper game analysis, which can help strength and conditioning coaches and managers in gaining better insights into the players' responses to various game situations.Source: Sensors (Basel) 22 (2022). doi:10.3390/s22249842
DOI: 10.3390/s22249842
Metrics:
Skoki A., Rossi A., Cintia P., Pappalardo L., Stajduhar I.
Every soccer game influences each player's performance differently. Many studies have tried to explain the influence of different parameters on the game; however, none went deeper into the core and examined it minute-by-minute. The goal of this study is to use data derived from GPS wearable devices to present a new framework for performance analysis. A player's energy expenditure is analyzed using data analytics and K-means clustering of low-, middle-, and high-intensity periods distributed in 1 min segments. Our framework exhibits a higher explanatory power compared to usual game metrics (e.g., high-speed running and sprinting), explaining 45.91% of the coefficient of variation vs. 21.32% for high-, 30.66% vs. 16.82% for middle-, and 24.41% vs. 19.12% for low-intensity periods. The proposed methods enable deeper game analysis, which can help strength and conditioning coaches and managers in gaining better insights into the players' responses to various game situations.Source: Sensors (Basel) 22 (2022). doi:10.3390/s22249842
DOI: 10.3390/s22249842
Metrics:
See at:
Sensors | ISTI Repository | www.mdpi.com | CNR ExploRA
2022
Journal article
Open Access
Regional lean soft tissue and intracellular water are associated with changes in lower-body neuromuscular performance: a pilot study in elite soccer players
Bongiovanni T., Tinsley G., Martera G., Orlandi C., Genovesi F., Puleo G., Rossi A., Trecroci A.
The assessment of body composition over a competitive season provides valuable information that can help sports professionals to evaluate the efficacy of training and nutritional strategies, as well as monitoring athletes' health status. The purpose of this study was to examine the association of changes in body composition and hydration status with changes in lower-body neuromuscular performance in soccer. Twenty-two male professional soccer players (mean ± SD; age: 26.4 ± 4.8 years; height: 184.3 ± 5.7 cm; body mass: 81.1 ± 6.5 kg; body fat: 11.6 ± 1.5%) took part in the study, for which they were tested at the initial and final stage of the competitive season. Total (whole body) and regional (arms and legs) lean soft tissue (LST) were estimated to obtain the body composition profile. Total body water (TBW) content, including extracellular (ECW) and intracellular (ICW) water, was obtained to monitor players' hydration status. Countermovement jump (CMJ) height, power, and strength were used to derive players' lower-body neuromuscular performance. The results showed that changes in legs LST and ICW significantly (p < 0.01) explained (r2 = 0.39) the improvements in CMJ height, power, and strength from the initial to the final stage of the season. Given the high demand imposed on the lower limbs during a soccer season, being more susceptible to change compared to whole-body LST, assessing regional LST and ICW would be more appropriate to provide extended information on players' readiness.Source: European journal of investigation in health, psychology and education (Online) 12 (2022): 882–892. doi:10.3390/ejihpe12080064
DOI: 10.3390/ejihpe12080064
Project(s): SoBigData-PlusPlus
Metrics:
Bongiovanni T., Tinsley G., Martera G., Orlandi C., Genovesi F., Puleo G., Rossi A., Trecroci A.
The assessment of body composition over a competitive season provides valuable information that can help sports professionals to evaluate the efficacy of training and nutritional strategies, as well as monitoring athletes' health status. The purpose of this study was to examine the association of changes in body composition and hydration status with changes in lower-body neuromuscular performance in soccer. Twenty-two male professional soccer players (mean ± SD; age: 26.4 ± 4.8 years; height: 184.3 ± 5.7 cm; body mass: 81.1 ± 6.5 kg; body fat: 11.6 ± 1.5%) took part in the study, for which they were tested at the initial and final stage of the competitive season. Total (whole body) and regional (arms and legs) lean soft tissue (LST) were estimated to obtain the body composition profile. Total body water (TBW) content, including extracellular (ECW) and intracellular (ICW) water, was obtained to monitor players' hydration status. Countermovement jump (CMJ) height, power, and strength were used to derive players' lower-body neuromuscular performance. The results showed that changes in legs LST and ICW significantly (p < 0.01) explained (r2 = 0.39) the improvements in CMJ height, power, and strength from the initial to the final stage of the season. Given the high demand imposed on the lower limbs during a soccer season, being more susceptible to change compared to whole-body LST, assessing regional LST and ICW would be more appropriate to provide extended information on players' readiness.Source: European journal of investigation in health, psychology and education (Online) 12 (2022): 882–892. doi:10.3390/ejihpe12080064
DOI: 10.3390/ejihpe12080064
Project(s): SoBigData-PlusPlus
Metrics:
See at:
European Journal of Investigation in Health, Psychology and Education | ISTI Repository | www.mdpi.com | CNR ExploRA
2023
Journal article
Open Access
Match load physical demands in U-19 professional soccer players assessed by a wearable inertial sensor
Pillitteri G., Giustino V., Petrucci M., Rossi A., Leale I., Bellafiore M., Thomas E., Iovane A., Palma A., Battaglia G.
Background: Wearable inertial sensors are poorly used in soccer to monitor external load (EL) indicators. However, these devices could be useful for improving sports performance and potentially reducing the risk of injury. The aim of this study was to investigate the EL indicators (i.e., cinematic, mechanical, and metabolic) differences between playing positions (i.e., central backs, external strikers, fullbacks, midfielders, and wide midfielder) during the first half time of four official matches (OMs). Methods: 13 young professional soccer players (Under-19; age: 18.5 ± 0.4 years; height: 177 ± 6 cm; weight: 67 ± 4.8 kg) were monitored through a wearable inertial sensor (TalentPlayers TPDev, firmware version 1.3) during the season 2021-2022. Participants' EL indicators were recorded during the first half time of four OMs. Results: significant differences were detected in all the EL indicators between playing positions except for two of them (i.e., distance traveled in the various metabolic power zones (<10 w) and the number of direction changes to the right >30° and with speed >2 m). Pairwise comparisons showed differences in EL indicators between playing positions. Conclusions: Young professional soccer players showed different loads and performances during OMs in relation to playing positions. Coaches should consider the different physical demands related to playing positions in order to design the most appropriate training program.Source: Journal of functional morphology and kinesiology 8 (2023). doi:10.3390/jfmk8010022
DOI: 10.3390/jfmk8010022
Metrics:
Pillitteri G., Giustino V., Petrucci M., Rossi A., Leale I., Bellafiore M., Thomas E., Iovane A., Palma A., Battaglia G.
Background: Wearable inertial sensors are poorly used in soccer to monitor external load (EL) indicators. However, these devices could be useful for improving sports performance and potentially reducing the risk of injury. The aim of this study was to investigate the EL indicators (i.e., cinematic, mechanical, and metabolic) differences between playing positions (i.e., central backs, external strikers, fullbacks, midfielders, and wide midfielder) during the first half time of four official matches (OMs). Methods: 13 young professional soccer players (Under-19; age: 18.5 ± 0.4 years; height: 177 ± 6 cm; weight: 67 ± 4.8 kg) were monitored through a wearable inertial sensor (TalentPlayers TPDev, firmware version 1.3) during the season 2021-2022. Participants' EL indicators were recorded during the first half time of four OMs. Results: significant differences were detected in all the EL indicators between playing positions except for two of them (i.e., distance traveled in the various metabolic power zones (<10 w) and the number of direction changes to the right >30° and with speed >2 m). Pairwise comparisons showed differences in EL indicators between playing positions. Conclusions: Young professional soccer players showed different loads and performances during OMs in relation to playing positions. Coaches should consider the different physical demands related to playing positions in order to design the most appropriate training program.Source: Journal of functional morphology and kinesiology 8 (2023). doi:10.3390/jfmk8010022
DOI: 10.3390/jfmk8010022
Metrics:
See at:
Journal of Functional Morphology and Kinesiology | ISTI Repository | www.mdpi.com | CNR ExploRA
2023
Journal article
Open Access
How do football playing positions differ in body composition? A first insight into white Italian Serie A and Serie B players
Bongiovanni T., Rossi A., Genovesi F., Martera G., Puleo G., Orlandi C., Spedicato M., Iaia F. M., Del Vescovo R., Gallo S., Cannataro R., Ripari P., Levi Micheli M., Cataldi S., Trecroci A.
The present study aimed to investigate how playing positions differ in specific body composition variables in professional soccer players with respect to specific field zones and tactical lines. Five hundred and six Serie A and B professional soccer players were included in the study and analyzed according to their playing positions: goalkeepers (GKs), central backs (CBs), fullbacks (FBs), central midfielders (MIDs), wide midfielders (WMs), attacking midfielders (AMs), second strikers (SSs), external strikers (ESs), and central forwards (CFs), as well as their field zones (central and external) and tactical lines (defensive, middle, and offensive). Anthropometrics (stature and body mass) of each player were recorded. Then, body composition was obtained by means of bioelectric impedance analysis (BIA). GKs and CFs were the tallest and heaviest players, with no differences from each other. Likewise, GKs and CFs, along with CBs, were apparently more muscular (for both upper and lower limbs) and fatter at the same time compared with the other roles. Overall, players of the defensive line (CBs and FBs), along with those playing in central field zones (CBs, MIDs, AMs, SSs, and CFs), were significantly (p < 0.05) superior in almost all anthropometric and body composition variables than those of middle and offensive line and external zones, respectively.Source: Journal of functional morphology and kinesiology 8 (2023). doi:10.3390/jfmk8020080
DOI: 10.3390/jfmk8020080
Project(s): SoBigData-PlusPlus
Metrics:
Bongiovanni T., Rossi A., Genovesi F., Martera G., Puleo G., Orlandi C., Spedicato M., Iaia F. M., Del Vescovo R., Gallo S., Cannataro R., Ripari P., Levi Micheli M., Cataldi S., Trecroci A.
The present study aimed to investigate how playing positions differ in specific body composition variables in professional soccer players with respect to specific field zones and tactical lines. Five hundred and six Serie A and B professional soccer players were included in the study and analyzed according to their playing positions: goalkeepers (GKs), central backs (CBs), fullbacks (FBs), central midfielders (MIDs), wide midfielders (WMs), attacking midfielders (AMs), second strikers (SSs), external strikers (ESs), and central forwards (CFs), as well as their field zones (central and external) and tactical lines (defensive, middle, and offensive). Anthropometrics (stature and body mass) of each player were recorded. Then, body composition was obtained by means of bioelectric impedance analysis (BIA). GKs and CFs were the tallest and heaviest players, with no differences from each other. Likewise, GKs and CFs, along with CBs, were apparently more muscular (for both upper and lower limbs) and fatter at the same time compared with the other roles. Overall, players of the defensive line (CBs and FBs), along with those playing in central field zones (CBs, MIDs, AMs, SSs, and CFs), were significantly (p < 0.05) superior in almost all anthropometric and body composition variables than those of middle and offensive line and external zones, respectively.Source: Journal of functional morphology and kinesiology 8 (2023). doi:10.3390/jfmk8020080
DOI: 10.3390/jfmk8020080
Project(s): SoBigData-PlusPlus
Metrics:
See at:
ISTI Repository | www.mdpi.com | CNR ExploRA
2023
Journal article
Open Access
XAI in affective computing: a preliminary study
Sajno E., Rossi A., De Gaspari S., Sansoni M., Brizzi G., Riva G.
Affective computing is a rapidly growing field that aims to understand human emotions through Artificial Intelligence. One of the most promising ways to achieve this goal is the use of physiological data (e.g. electrocardiogram - ECG) and Machine Learning (ML) algorithms to classify affective states. ECG correlates, such as Heart Rate Variability (HRV) and its features, are reported as viable indicators in both dimensional approaches, especially for valence, and in detecting discrete emotions. In this preliminary study, we used the ECG data from the open-source HCI Tagging Database, which includes physiological data and self-referred feedback from 30 subjects who watched videos designed to elicit different emotions. The subjects evaluated their reactions using a three-dimensional affective space defined by arousal, valence, and dominance levels and reported the emotions they felt. To classify the affective states, we trained and tested different classification algorithms on the HRV features, using as labels, each self-reported feedback (i.e., valence, arousal, dominance, and emotions). The results showed that HRV features, when combined with normalization methods and ML algorithms, were effective in recognizing emotions as experienced by individuals. In particular, the study showed that Decision Tree was the best-performing algorithm for predicting emotions based on HRV data. Additionally, an Explainable AI (XAI) model provided insights into the weight of these features in the ML discrimination phases. Overall, the study highlights the potential of HRV as a valid and unobtrusive source for detecting emotional states.Source: Annual review of cybertherapy and telemedicine 21 (2023): 40–46.
Sajno E., Rossi A., De Gaspari S., Sansoni M., Brizzi G., Riva G.
Affective computing is a rapidly growing field that aims to understand human emotions through Artificial Intelligence. One of the most promising ways to achieve this goal is the use of physiological data (e.g. electrocardiogram - ECG) and Machine Learning (ML) algorithms to classify affective states. ECG correlates, such as Heart Rate Variability (HRV) and its features, are reported as viable indicators in both dimensional approaches, especially for valence, and in detecting discrete emotions. In this preliminary study, we used the ECG data from the open-source HCI Tagging Database, which includes physiological data and self-referred feedback from 30 subjects who watched videos designed to elicit different emotions. The subjects evaluated their reactions using a three-dimensional affective space defined by arousal, valence, and dominance levels and reported the emotions they felt. To classify the affective states, we trained and tested different classification algorithms on the HRV features, using as labels, each self-reported feedback (i.e., valence, arousal, dominance, and emotions). The results showed that HRV features, when combined with normalization methods and ML algorithms, were effective in recognizing emotions as experienced by individuals. In particular, the study showed that Decision Tree was the best-performing algorithm for predicting emotions based on HRV data. Additionally, an Explainable AI (XAI) model provided insights into the weight of these features in the ML discrimination phases. Overall, the study highlights the potential of HRV as a valid and unobtrusive source for detecting emotional states.Source: Annual review of cybertherapy and telemedicine 21 (2023): 40–46.
See at:
ISTI Repository | www.arctt.info | CNR ExploRA
2023
Journal article
Open Access
External load profile during different sport-specific activities in semi-professional soccer players
Pillitteri G., Giustino V., Petrucci M., Rossi A., Bellafiore M., Thomas E., Iovane A., Bianco A., Palma A., Battaglia G.
Background: Global Positioning System (GPS) devices are widely used in soccer for monitoring external load (EL) indicators with the aim of maximizing sports performance.The aim of this study was to investigate the EL indicators differences in players of different playing positions (i.e., central backs, external strikers, fullbacks, midfielders, strikers, wide midfielder) between and within different sport-specific tasks and official matches. Methods: 1932 observations from 28 semi-professional soccer players (age: 25 ± 6 years, height: 183 ± 6 cm, weight: 75.2 ± 7 kg) were collected through GPS devices (Qstarz BT-Q1000EX, 10 Hz) during the season 2019-2020. Participants were monitored during Official Match (OM), Friendly Matches (FM), Small Sided Games (SSG), and Match-Based Exercises (MBE). Metabolic (i.e., metabolic power, percentage of metabolic power > 35w, number of intense actions per minute, distance per minute, passive recovery time per minute) and neuromuscular indicators (i.e., percentage of intense accelerations, percentage of intense decelerations, change of direction per min > 30°) were recorded during each task. Results: Statistically significant differences were detected in EL indicators between playing positions within each task and between tasks. In particular, results from the two-way ANOVA tests showed significant interaction, but with small effect size, in all the EL indicators between playing positions for each task and within tasks. Moreover, statistical differences, but with small effect size, between playing positions were detected in each task and for each EL indicator. Finally, the strongest statistical differences (with large effect size) were detected between tasks for each EL indicator. Details of the Tukey post-hoc analysis reporting the pairwise comparisons within and between tasks with playing positions are also provided. Conclusion: In semi-professional soccer players, different metabolic and neuromuscular performance were detected in different playing position between and within different tasks and official matches. Coaches should consider the different physical responses related to different physical tasks and playing position to design the most appropriate training program.Source: BMC sports science, medicine & rehabilitation 15 (2023). doi:10.1186/s13102-023-00633-3
DOI: 10.1186/s13102-023-00633-3
Metrics:
Pillitteri G., Giustino V., Petrucci M., Rossi A., Bellafiore M., Thomas E., Iovane A., Bianco A., Palma A., Battaglia G.
Background: Global Positioning System (GPS) devices are widely used in soccer for monitoring external load (EL) indicators with the aim of maximizing sports performance.The aim of this study was to investigate the EL indicators differences in players of different playing positions (i.e., central backs, external strikers, fullbacks, midfielders, strikers, wide midfielder) between and within different sport-specific tasks and official matches. Methods: 1932 observations from 28 semi-professional soccer players (age: 25 ± 6 years, height: 183 ± 6 cm, weight: 75.2 ± 7 kg) were collected through GPS devices (Qstarz BT-Q1000EX, 10 Hz) during the season 2019-2020. Participants were monitored during Official Match (OM), Friendly Matches (FM), Small Sided Games (SSG), and Match-Based Exercises (MBE). Metabolic (i.e., metabolic power, percentage of metabolic power > 35w, number of intense actions per minute, distance per minute, passive recovery time per minute) and neuromuscular indicators (i.e., percentage of intense accelerations, percentage of intense decelerations, change of direction per min > 30°) were recorded during each task. Results: Statistically significant differences were detected in EL indicators between playing positions within each task and between tasks. In particular, results from the two-way ANOVA tests showed significant interaction, but with small effect size, in all the EL indicators between playing positions for each task and within tasks. Moreover, statistical differences, but with small effect size, between playing positions were detected in each task and for each EL indicator. Finally, the strongest statistical differences (with large effect size) were detected between tasks for each EL indicator. Details of the Tukey post-hoc analysis reporting the pairwise comparisons within and between tasks with playing positions are also provided. Conclusion: In semi-professional soccer players, different metabolic and neuromuscular performance were detected in different playing position between and within different tasks and official matches. Coaches should consider the different physical responses related to different physical tasks and playing position to design the most appropriate training program.Source: BMC sports science, medicine & rehabilitation 15 (2023). doi:10.1186/s13102-023-00633-3
DOI: 10.1186/s13102-023-00633-3
Metrics:
See at:
bmcsportsscimedrehabil.biomedcentral.com | ISTI Repository | CNR ExploRA
2023
Journal article
Open Access
Association between internal load responses and recovery ability in U19 professional soccer players: a machine learning approach
Pillitteri G., Rossi A., Simonelli C., Leale I., Giustino V., Battaglia G.
Background: The objective of soccer training load (TL) is enhancing players' performance while minimizing the possible negative effects induced by fatigue. In this regard, monitoring workloads and recovery is necessary to avoid overload and injuries. Given the controversial results found in literature, this study aims to better understand the complex relationship between internal training load (IL) by using rating of perceived exertion (RPE), recovery, and availability (i.e., subjective players' readiness status). Methods: In this cross-sectional study, twenty-two-professional soccer players (age: 18.5 ± 0.4 years, height: 177 ± 6 cm, weight: 67 ± 6.7 kg) competing in the U19 Italian Championship were monitored using RPE scale to assess IL, and TreS scale to detect information about recovery and training/match availability during an entire season (2021-2022). Results: Autocorrelation analysis showed a repeated pattern with 7 days lag (weekly microcycle pattern) for all the variables considered (i.e., TL, recovery, and availability). For recovery (r = 0.64, p < 0.001) and availability (r = 0.63, p < 0.001) the best lag for both of them is 1 day. It indicates that recovery and availability are related to the past day value. Moreover, TL was found to be negatively affected by recovery and availability of the current day (lag = 0 day). Cross-correlation analysis indicates that TL is negatively affected by recovery (r = 0.46, p < 0.001) and availability (r = 0.42, p < 0.001) of the current day (lag = 0 day). In particular, lower recovery and availability will result in following lower TL. Furthermore, we found that TL negatively affects recovery (r = 0.52, p < 0.001) and availability (r = 0.39, p < 0.01) of the next day (lag = 1 day). In fact, the higher the TL in a current day is, the lower the recovery and availability in the next day will be. Conclusion: In conclusion, this study highlights that there is a relationship between TL and recovery and that these components influence each other both on the same day and on the next one. The use of RPE and TreS scale to evaluate TL and recovery/availability of players allows practitioners to better adjust and schedule training within the microcycle to enhance performance while reducing injury risk.Source: Heliyon (Londen) 9 (2023). doi:10.1016/j.heliyon.2023.e15454
DOI: 10.1016/j.heliyon.2023.e15454
Project(s): SoBigData-PlusPlus
Metrics:
Pillitteri G., Rossi A., Simonelli C., Leale I., Giustino V., Battaglia G.
Background: The objective of soccer training load (TL) is enhancing players' performance while minimizing the possible negative effects induced by fatigue. In this regard, monitoring workloads and recovery is necessary to avoid overload and injuries. Given the controversial results found in literature, this study aims to better understand the complex relationship between internal training load (IL) by using rating of perceived exertion (RPE), recovery, and availability (i.e., subjective players' readiness status). Methods: In this cross-sectional study, twenty-two-professional soccer players (age: 18.5 ± 0.4 years, height: 177 ± 6 cm, weight: 67 ± 6.7 kg) competing in the U19 Italian Championship were monitored using RPE scale to assess IL, and TreS scale to detect information about recovery and training/match availability during an entire season (2021-2022). Results: Autocorrelation analysis showed a repeated pattern with 7 days lag (weekly microcycle pattern) for all the variables considered (i.e., TL, recovery, and availability). For recovery (r = 0.64, p < 0.001) and availability (r = 0.63, p < 0.001) the best lag for both of them is 1 day. It indicates that recovery and availability are related to the past day value. Moreover, TL was found to be negatively affected by recovery and availability of the current day (lag = 0 day). Cross-correlation analysis indicates that TL is negatively affected by recovery (r = 0.46, p < 0.001) and availability (r = 0.42, p < 0.001) of the current day (lag = 0 day). In particular, lower recovery and availability will result in following lower TL. Furthermore, we found that TL negatively affects recovery (r = 0.52, p < 0.001) and availability (r = 0.39, p < 0.01) of the next day (lag = 1 day). In fact, the higher the TL in a current day is, the lower the recovery and availability in the next day will be. Conclusion: In conclusion, this study highlights that there is a relationship between TL and recovery and that these components influence each other both on the same day and on the next one. The use of RPE and TreS scale to evaluate TL and recovery/availability of players allows practitioners to better adjust and schedule training within the microcycle to enhance performance while reducing injury risk.Source: Heliyon (Londen) 9 (2023). doi:10.1016/j.heliyon.2023.e15454
DOI: 10.1016/j.heliyon.2023.e15454
Project(s): SoBigData-PlusPlus
Metrics:
See at:
ISTI Repository | www.sciencedirect.com | CNR ExploRA