Authors: Peter Byers1, Antonella Schwarz2, Lauren Stern3, Gabriel J. Sanders4, Corey A. Peacock1
1Department of Health and Human Performance, Nova Southeastern University, Davie FL USA
2Department of Health Promotion and Clinical Practice, Barry University, Miami Shores FL USA
3Health Professions Division, Nova Southeastern University, Davie FL USA
4Exercise Science, University of Cincinnati, Cincinnati OH USA
Corresponding Author:
Peter Byers, MS
3300 S. University Drive
Fort Lauderdale-Davie, FL 33328-2004
618-210-9891
Peter Byers, MS, is a sports science researcher and adjunct professor at Nova Southeastern University. His research interests include mixed martial arts and sports science.
Antonella V. Schwarz, PhD, is an assistant professor of Sport & Exercise Science in the College of Health and Wellness at Barry University in Miami, FL. Her research interests focus on hypertrophy and sport performance.
Lauren Stern, MPH, is a second-year medical student at Nova Southeastern University Dr. Kiran C Patel College of Osteopathic Medicine in Ft. Lauderdale, FL.
Gabriel J. Sanders, PhD, is an assistant professor in the Exercise Science Department at the University of Cincinnati. His research interests focus on wearable technology, daily workloads and fatigue in athletes.
Corey A. Peacock, PhD, is a professor, chair, and program director of Health and Human Performance at Nova Southeastern University. His research focuses on mixed martial arts performance.
Comparing the differences in PlayerLoad during kickboxing and sparring in professional MMA athletes
ABSTRACT
Purpose: MMA involves the combination of grappling and striking combat sports with short, explosive movements and rapid change of direction that can be monitored through Catapult GPS units to quantify external load of MMA training. The primary aim of this study is to provide data on the differences between external load and internal load in MMA athletes using Catapult Sports Playerload and Heart Rate during MMA sparring and kickboxing sessions. Methods: Eighteen male (n=18) MMA competitors (30.6 ± 0.8 years, 180.8 ± 5.0 cm, 89.5 ± 12.8 kg) participated in the study. Subjects must have competed in 4 professional or amateur MMA bouts. Subjects participated in one MMA sparring session and one kickboxing session. Paired t-tests were performed to compare the means of ratings of perceived exertion (RPE), session duration (Duration), average heart rate (HRavg), maximum heart rate (HRmax), Player Load (au) (PL), and Player Load per Min (au/min) (PL/Min) metrics between the kickboxing and sparring sessions. Pearson correlation coefficients were calculated to explore the relationships between variables. Multiple regression analysis was used to examine the effect of age, height, and weight on internal and external training load variables (RPE, Duration, HRavg, HRmax, Player Load, PL/Min) during both practice sessions. All data was analyzed using SPSS version 29 and significance was set at p ≤ 0.05. Results: The paired t-tests revealed significant (p ≤ 0.05) differences between kickboxing and sparring for multiple variables including RPE, Duration, and Player Load Min. Player Load/Min was significantly greater during MMA sparring compared to kickboxing (p = 0.040). Conclusion: In conclusion, PL/Min is significantly higher during MMA sessions compared to kickboxing sessions alone. Understanding these differences can inform MMA trainers and sports scientists to properly adjust training regimens with their athletes. This study adds to the growing body of evidence of reliability and practical application of Catapult Sports to quantify external load in MMA athletes during MMA and kickboxing sessions. Application in Sport: Currently, there are no methods to track external workload in MMA athletes. Tracking PL for preparation of an upcoming bout may enhance the training protocols of MMA skill coaches by planning training load distribution in advance. The volume of MMA training sessions can be quantified via external workload and can be used as a baseline for MMA skill coaches and trainers to dictate future training sessions.
Key Words: Catapult Sports, GPS, LPS, combat sports, training load, external load
INTRODUCTION
Tracking athletes’ external load using microelectromechanical systems (MEMS) has become commonplace in sports (13). The MEMS contain inertial sensors such as accelerometers, gyroscopes, and magnetometers in single player worn units that connect to global positioning systems (GPS) and local positioning systems (LPS) to accurately track external load in athletes (14). Catapult Sports (Catapult Innovations, Melbourne, Australia), provides wearable MEMS units with tri-axial accelerometry, tri-axial gyroscopes, and tri-axial magnetometers (1). These qualities of Catapult MEMS units help quantify the magnitude of change in acceleration. Catapult Sports proposed the idea of Playerload® (PL) an arbitrary unit (au) of external load that quantifies the sum of accelerations and magnitude of change in acceleration across the medial-lateral (X), anterior-posterior (Y), and vertical (Z) planes (1). These systems allow insight into distance and speed-oriented metrics that accumulate over a training session to quantify external load through PL. Given the accessibility of GPS and LPS to record outdoor signal, GPS-based wearable tracking devices typically assess outdoor sports and have an array of data to support their use (2, 11, 16). Previous research has reported sports that occur indoors will have difficulty recording speed and distance-oriented metrics, and that older GPS units have low inter-unit reliability across various GPS models (1, 14). However, a paper by Luteberget and colleagues (2018) set out to determine the validity of position, distance traveled, and instantaneous speed of a commercially available LPS (Catapult ClearSky T6, Catapult Sports, Australia) for indoor use. The researchers found that for indoor sports, LPS raw data compared with the gold standard reference system (infrared light-based camera system), showed measures of position, distance traveled, and instantaneous speed had low errors and can be used in pair with time-motion analysis. A paper in 2020 by Theodoropoulos et al. supports the use of GPS units for indoor sports claiming the LPS technological advancements from Catapult Sports has improved accuracy by increasing sampling rate to 100-120 Hz to become more sensitive to rapid changes in velocity and direction. With the improvements in technology of the GPS units, recording indoor in elite and professional athletes has become popular, with data on but not limited to basketball and mixed martial arts (MMA) (3-7, 16). Body worn accelerometry has been used to measure external load in multiple combat sports, including MMA, taekwondo (TKD), and submission grappling (3-7, 10, 18).
MMA involves the combination of grappling and striking combat sports with short, explosive movements and rapid change of direction that can be monitored through Catapult GPS units to quantify external load of MMA training (6). The reliability of Catapult GPS units appears to be satisfactory. Hurst et al. (2014) examined the intra-unit reliability of portable accelerometry using Catapult Sports and found the units could be reliable to determine the external workload (PL) of isolated MMA striking and grappling techniques. Further research has been completed in submission grapplers as well as comparing MMA sparring to isolated MMA techniques to provide intra-unit reliability data (4-5). There appears to be a gap in the literature between unit reliability and providing data for MMA coaches and practitioners to utilize PL. Del Vecchio et al. (2018) found utilization for PL in TKD athletes, providing evidence that striking martial arts can be monitored through GPS. Currently, there are minimal studies to examine PL accumulation in MMA sparring using Catapult Sports GPS units (3, 6). Kirk et al. (2020) investigated the pacing of MMA sparring with Catapult Sports accelerometers during 3 x 5-minute rounds and accumulating PL throughout each round as well as total mean PL. Blood lactate analysis and PL showed significant correlations over the 3 x 5-minute rounds, providing evidence for a relationship between PL and physiological response. In another study, Kirk et al. (2023) examined the relationship between internal and external loads of weekly MMA training. However, measuring external load and internal load in competition for MMA athletes is not feasible, and methods are needed to assess physiological responses to the demands of MMA (15). Replicating the intensity of an MMA bout is difficult, however, MMA sparring can mimic the intensity seen in the cage and is a feasible way to understand the external workload of MMA athletes. Furthermore, because MMA requires training in various disciplines, such as kickboxing, understanding the external workload differences in MMA sparring and kickboxing can enlighten sports scientistss who work with MMA athletes and trainers. Therefore, methods such as PL need to be further understood to provide practitioners with data on how to replicate the demands of MMA training and competition.
Based on previous literature on external and internal load in MMA, the primary aim of this study is to provide GPS metrics during MMA training that may be a viable option for allowing coaches to plan training load distribution in advance. The researchers hypothesize that differences will exist between external and internal load in MMA athletes using Catapult Sports PL and PL/min during MMA sparring and kickboxing sessions.
The current study investigated internal and external load metrics in MMA athletes. The researchers utilized Catapult Sports GPS accelerometers by measuring PL, PL/min, HR, and RPE to compare the differences between MMA and kickboxing training sessions. The methods section details the participants, procedures, data collection and statistical analysis used. The results of this study present statistical comparisons between MMA and kickboxing training sessions, while the discussion and application of sports section attempt to outline how MMA trainers and sports scientists may incorporate Catapult Sports GPS into MMA training sessions to enhance training protocols.
METHODS
Participants
Eighteen male MMA competitors participated in the study. Subjects’ height and weight were measured by a stadiometer. Inclusion criteria for this study includes active fighters who have taken part in at least 4 professional or amateur MMA bouts and medically cleared to fight. Exclusion criteria for this study includes fighters with 4 or fewer MMA bouts and those not medically cleared to participate. Analysis of this deidentified dataset underwent institutional review and was approved (2015-156-NSU).
Procedures
Participants wore 8-ounce MMA sparring gloves, shin pads, MMA shorts, a groin protector, and a t-shirt or rash guard for MMA sparring. For the kickboxing session, participants wore 16-ounce kickboxing gloves, shin pads, MMA shorts, a groin protector, mouthpiece and a t-shirt or rash guard. Vector S7 (Catapult Innovations, Australia) triaxial accelerometers with a sampling rate of 100 Hz provided at 1kHz were used to record external load. The accelerometers were placed in the manufacturer’s garment on the upper torso, positioning the unit at the T3-T4 vertebrae. Each unit was calibrated during the morning of data collection in line with Catapult Sports recommendations. The accelerometers were used to determine the mean total player load and the mean player load per minute for MMA and kickboxing sessions. Player Load data from the accelerometers were recorded in arbitrary units (au). Average heart rate (HRavg) and maximum heart rate (HRmax) were collected. Data collection of Player Load, HRavg, and HRmax was recorded via Openfield v1.14.0 software (Catapult, Canberra, Australia). The accelerometers are connected via Bluetooth to one Vector Receiver from Catapult. The Vector Receiver was strategically placed just outside the mats to not interfere with the participants training session. The study took place at a professional MMA gym supervised by professional MMA coaches. The duration of the kickboxing and MMA sessions were up to the MMA coach’s discretion. The researchers began recording data in the OpenField app when the coaches began the MMA and kickboxing sessions and stopped recording when the coaches ended the sessions. Participants were instructed to train as they would under normal conditions. Participants were asked their rating of perceived exertion (RPE) (1-10) of the training session and were recorded following each session.
Data Analyses
Descriptive statistics were calculated for mean and standard deviations of all the demographic variables (height, weight, age). Paired t-tests were performed to compare the means of ratings of perceived exertion (RPE), session duration (Duration), average heart rate (HRavg), maximum heart rate (HRmax), Player Load, and Player Load per Min (PL/Min) metrics between the kickboxing and sparring sessions. Pearson correlation coefficients were calculated to explore the relationships between variables. Multiple regression analysis was used to examine the effect of age, height, and weight on internal and external training load variables (RPE, Duration, HRavg, HRmax, Player Load, PL/Min) during both practice sessions. All data was analyzed using SPSS version 29 and significance was set at p ≤ 0.05.
RESULTS
Eighteen male, MMA (30.6 ± 0.8 years, 180.8 ± 5.0 cm, 89.5 ± 12.8 kg) competing professionally were used for this within-subjects design study comparing kickboxing and sparring practice sessions. The paired t-tests revealed significant (p ≤ 0.05) differences between kickboxing and sparring for multiple variables including RPE, Duration, and Player Load Min (Table 1). The RPE during MMA sparring was significantly higher than during kickboxing (p = 0.008). Player Load Min was also significantly greater during MMA sparring compared to kickboxing (p = 0.040). Interestingly, the duration for sparring was significantly shorter than for kickboxing (p = 0.002). No additional significant differences (p ≥ 0.05) were found between sessions.
Table 1: Paired t-test results comparing kickboxing and sparring (Mean ± SD)
Kickboxing Sparring t-statistic p-value RPE 6.0 ± 1.6 7.6 ± 1.9 -3.245 0.008* Duration (min) 67.8 ± 6.7 52.0 ± 11.3 3.992 0.002* HRavg (bpm) 155.0 ± 3.4 143.5 ± 0.7 2.217 0.059 HRmax (bpm) 182.5 ± 5.5 176.5 ± 2.5 1.223 0.269 Player Load 444.6 ± 153.4 373.8 ± 102.5 1.943 0.083 Player Load per Min 6.49 ± 1.80 7.23 ± 1.72 2.395 0.040*
*Significance set at p ≤ 0.05.
Additionally, correlations were utilized to establish relationships. Correlational analysis demonstrated a strong, positive correlation between RPE and HRavg during kickboxing (r = 0.87, p < 0.01). Similarly, the analysis demonstrated a moderate, positive correlation between Player Load and HRavg during sparring (r = 0.65, p < 0.05). A non-significant weak negative correlation (r = – 0.230, p = 0.410) exists between weight and PlayerLoad kickboxing (PLkick), and between weight and PlayerLoad/min kickboxing (PL/mkick) (r = -0.213, p = 0.447). A non-significant weak negative correlation (r = -0.431, p = 0.335) exists between weight and PlayerLoad sparring (PLspar), and between weight and PlayerLoad/min sparring (PL/mspar) (r = -0.485, p = 0.270). No additional significant correlations (p ≥ 0.05) exist between variables during kickboxing or sparring. Finally, a multiple regression analysis was utilized to predict internal and external training load variables. The regression analysis indicated that age, height, and weight provided non-significant results as predictors of internal and external training loads during both kickboxing and sparring. Specifically, for player load during kickboxing, the coefficients for age, height, and weight were -10.91 (p = 0.109), 2.08 (p = 0.717), and -2.39 (p = 0.475), respectively (R² = 0.290). For Player Load during sparring, the coefficients were -2.67 (p = 0.512), 1.97 (p = 0.473), and -0.29 (p = 0.910), respectively (R² = 0.195). For PL/min during kickboxing, the coefficients were -0.24 (p = 0.205), 0.05 (p = 0.804), and -0.03 (p = 0.716), respectively (R² = 0.371). For PL/min during sparring, the coefficients were -0.16 (p = 0.236), 0.04 (p = 0.716), and -0.03 (p = 0.616), respectively (R² = 0.264). For HRavg during kickboxing, the coefficients were -1.67 (p = 0.180), -0.14 (p = 0.871), and -0.01 (p = 0.974), respectively (R² = 0.503). For HRavg during sparring, the coefficients were -0.12 (p = 0.493), 0.19 (p = 0.089), and -0.01 (p = 0.776), respectively (R² = 0.251). For HRmax during kickboxing, the coefficients were -2.33 (p = 0.127), 0.02 (p = 0.985), and 0.08 (p = 0.888), respectively (R² = 0.423). For HRmax during sparring, the coefficients were -0.49 (p = 0.662), 0.13 (p = 0.808), and 0.17 (p = 0.722), respectively (R² = 0.138).
I
DISCUSSION
As wearable devices are becoming more popular in sports science, knowledge about the reliability and application of these metrics is essential to providing recommendations to optimize MMA athlete performance. Existing research has shown that body-worn accelerometric devices are reliable in determining the external workload for a range of mixed martial arts (MMA) techniques (10). However, to the authors’ knowledge, this is the first study to provide descriptive statistics comparing wearable device data in specifically a kickboxing session and an MMA sparring session. With the use of a Catapult Sports GPS accelerometer, the current study of 18 mixed-martial arts athletes focused on comparing different metrics including RPE, duration of session, HR, and PL during the two separate sessions. Overall findings found significant differences in RPE, duration, and player load per minute between the kickboxing and sparring sessions.
Although PL did not show any significant difference between the training sessions, PL/min was significantly greater in the sparring session than during the kickboxing session (p = 0.040). During the kickboxing sessions, the average PL/min amongst the 18 athletes was 6.49 ± 1.80 while during the sparring sessions, the average PL/min was 7.23 ± 1.72. Vector magnitude (VM), a measurement of external workload and a variant of PL, was recorded in a study completed on TKD athletes. A 45-minute training session produced a mean VM accumulation of 322.7±309.5 au with a VM of 6.8±6.5 au/min (18). Similarly, the kickboxing session from the current study produced a PL/min of 6.49 ± 1.80, however, the total VM of the TKD athletes was closer to the MMA sessions producing 373.8 ± 102.5. Kirk et al. (2020) reported a single 15-minute (3 x 5-minute round) simulated MMA bout produced accumulated PL of 224.32 ± 26.59 au with round 1 accumulating PL 77.61 ± 9.92 (PL/min 15.37 ± 1.71), round 2 accumulating PL 71.48 ± 10.56 (PL/min 14.30 ± 2.11), round 3 accumulating 65.39 ± 8.61 (PL/min 13.08 ± 1.72). In the same study, Kirk and colleagues found a direct negative non-significant relationship between PL/min and blood lactate, suggesting that PL can be used to identify when a MMA athlete is fatiguing. The results of the current study found one MMA session to accumulate PL of 373.8 ± 102.5 au, while MMA training sessions (striking, grappling and MMA) has shown a mean PL of 310.6±112 au (6).
In the current study, the durations of the sparring sessions were significantly shorter compared to the kickboxing sessions, but MMA sparring was accompanied with higher PL/min. The sparring sessions were full contact MMA sparring including kickboxing, grappling, and overall, more movement compared to the kickboxing session which was solely kickboxing. While session durations were made at the discretion of the coaches, the intensity and rigor displayed during sparring sessions may explain the significant difference in duration. Furthermore, the higher PL/min in MMA sparring compared to kickboxing may be explained by the variety of movements and techniques used in MMA sparring compared to kickboxing alone (i.e. wrestling, jiu-jitsu). This notion is supported by the higher RPE observed in MMA sparring (7.6 ± 1.9) compared to the kickboxing session (6 ± 1.6). Interestingly, HRavg was higher in the kickboxing session (155 ± 3.4) compared to the MMA session (143 ± 0.7), suggesting that sparring is subjectively harder than kickboxing, even at lower heart rates. This may be explained by the array of attacks that can be used in sparring compared to kickboxing, making sparring more cognitively fatiguing. In an existing study, PL showed capability of quantifying external load of grappling-based training sessions (5). While measurements of external load are specific to the sport being studied, it is described as the physical work during a training session (8). RPE exertion in the current study was also significantly higher during sparring compared to kickboxing (p = 0.008).
Previous research has also examined PL metrics in different ways. In a study conducted by Kirk et al. (2015), amongst 8 MMA fighters, the PL was compared for over 20 specific sparring techniques, both in isolation and in a sparring bout. Results found that during the sparring bout, intensity used for punches was significantly greater than intensity used for kicks. Amongst other significant data, PL for single-leg takedowns was significantly higher compared to double-leg takedowns. Understanding the intensity of movements can be beneficial to coaches and athletes in managing fatigue and developing training protocols (4, 7).
Outside of MMA, wearable accelerometric devices have been used in a variety of other sports including rugby, soccer, and basketball (9). Semi-professional soccer players had their PL monitored over the course of 44 training sessions with an average duration of 90.4 ± 23.0 minutes per session. The researchers found a mean PL of 789.2 ± 224.9, much higher than the kickboxing or MMA sessions, although the duration of the training sessions was almost twice as long. In a study of 17 professional basketball players of different positions, PL/min data was used to compare the intensity of the players and noted specific physical demands of each position (16). The PL/min was the highest in guards (12.1 ± 2.0 au), then forwards (10.5 ± 1.5 au) and centers (10.7 ± 1.8 au). Our data adds to this growing body of research as it supports the predictive capability of PL metrics on intensity of workout and enhancing training protocols for MMA athletes.
This study comes with limitations. Recording GPS signal indoors can become obstructed as walls and corners can disturb the quality of the signal. The participants have a large discrepancy in experience in MMA bouts, with some subjects having 4 amateur bouts and other subjects having competed in 30 professional bouts. The experience difference with the small sample size makes it difficult to apply the results throughout the MMA population given the variation in performance levels. The data was also limited to only two training sessions.
CONCLUSIONS
In conclusion, Catapult Sports accelerometry can be a useful method for measuring external load in MMA athletes. MMA sparring appears to produce a greater external workload and perceived exertion compared to kickboxing sessions alone, indicating a higher intensity for the MMA training session. Previous research in mock MMA sparring bouts has found higher PL/Min than the MMA sparring and kickboxing sessions from the current study, however, TKD athletes produce similar relative external workloads compared to MMA athletes in kickboxing sessions. To our knowledge, this study was the first of its kind to compare external load during MMA and kickboxing sessions. Future research should explore tracking external load in MMA athletes over multiple training sessions or a fight camp to allow MMA skill coaches to better implement Catapult Sports into their programming.
APPLICATIONS IN SPORT
This study, as well as previous research, continues to highlight the reliability and practical applications of GPS tracking in MMA. The evidence supports the notion that GPS wearables can monitor external load in MMA sparring, kickboxing, taekwondo, and submission grappling. Determining external load normative values in MMA athletes can enhance sports scientists understanding of adequate volumes of training. Based on external load values from previous training sessions, MMA skill coaches can allocate workload volumes to the various skill development aspects of the sport. This may improve the programming of training schedules for an upcoming bout. Furthermore, the MMA athletes in the present study did not report discomfort while training with the accelerometers, pointing to the capability of GPS tracking in high-performance MMA environments.
REFERENCES
Bredt, S. da G. T., Chagas, M. H., Peixoto, G. H., Menzel, H. J., & Andrade, A. G. P. de. (2020). Understanding Player Load: Meanings and Limitations. Journal of Human Kinetics, 71(1), 5–9.
Casamichana, D., Castellano, J., Calleja-Gonzalez, J., San Román, J., & Castagna, C. (2013). Relationship Between Indicators of Training Load in Soccer Players. Journal of Strength and Conditioning Research, 27(2), 369–374.
Kirk, C., Atkins, S., & Hurst, H. T. (2020). The pacing of Mixed Martial Arts Sparring Bouts: A secondary investigation with new analyses of previous data to support accelerometry as a potential method of monitoring pacing. Human Movement, 21(4), 88–96.
Kirk C, Hurst H, Atkins S. (2015). Comparison of the training loads of mixed martial arts techniques in isolated training and open sparring. Journal of Combat Sports and Martial Arts, 1(2), 1-6.
Kirk, C., Malone, J., & Angell, P. (2023). Intra-unit reliability and movement variability of submission grappling external load as measured by Torso Mounted Accelerometery. Biology of Sport, 40(2), 457–464.
Kirk C, Morton J, Clark D, Langan-Evans C. (2023). The relationships between internal and external training loads in mixed martial artists. International Journal of Sports Physiology and Performance, 19(2), 173-184.
Kirk, C., Hurst, H. T., & Atkins, S. (2015). Measuring the workload of mixed martial arts using accelerometry, time motion analysis and lactate. International Journal of Performance Analysis in Sport, 15(1), 359–370.
Impellizzeri, F. M., Marcora, S. M., & Coutts, A. J. (2019). Internal and external training load: 15 years on. International Journal of Sports Physiology and Performance, 14(2), 270–273.
Gómez-Carmona, C. D., Bastida-Castillo, A., Ibáñez, S. J., & Pino-Ortega, J. (2020). Accelerometry as a method for external workload monitoring in invasion team sports. A systematic review. PLOS ONE, 15(8), e0236643.
Hurst, H. T., Atkins, S., Kirk C. (2014). Reliability of a portable accelerometer for measuring workload during mixed martial arts. Journal of Athletic Enhancement, 03(05).
Ehrmann, F. E., Duncan, C. S., Sindhusake, D., Franzsen, W. N., & Greene, D. A. (2016). GPS and injury prevention in professional soccer. Journal of Strength and Conditioning Research, 30(2), 360–367.
Luteberget, L. S., Spencer, M., & Gilgien, M. (2018). Validity of the catapult clearsky T6 local positioning system for team sports specific drills, in indoor conditions. Frontiers in Physiology, 9(115).
Malone, J. J., Lovell, R., Varley, M. C., & Coutts, A. J. (2017). Unpacking the black box: Applications and considerations for using GPS devices in sport. International Journal of Sports Physiology and Performance, 12(s2), S2-18S2-26.
Nicolella, D. P., Torres-Ronda, L., Saylor, K. J., & Schelling, X. (2018). Validity and reliability of an accelerometer-based player tracking device. PLOS ONE, 13(2), e0191823.
Sanders, G. J., Howard, M., Carpenter, R., Peacock, C. A., & Byers, P. (2024). Heart rate, oxygen uptake and anaerobic thresholds during a maximal treadmill test with world class mixed martial arts fighters. Sports Innovation Journal, 5(5), 38–48.
Salazar, H., Castellano, J., & Svilar, L. (2020). Differences in external load variables between positions in elite basketball match-play. Journal of Human Kinetics, 75(1), 257–266.
Theodoropoulos, J. S., Bettle, J., & Kosy, J. D. (2020). The use of GPS and inertial devices for player monitoring in team sports: A review of current and future applications. Orthopedic Reviews, 12(1).
Del Vecchio, F. B., Bartel, C., Galliano, L. M., & Fukuda, D. H. (2018). Accelerometry use to study external load in combat sports: An example from Taekwondo. Journal of Physical Fitness & Treatment & Sports, 3(2), 555608.
