RESEARCH PAPER
 
KEYWORDS
TOPICS
ABSTRACT
Introduction and objective:
In recent years, load monitoring and analysis have become increasingly important in athletic training. The aim of this study was to provide a background for businesses and institutes to prepare for the implementation of load training and analysis in sports training, utilizing visual analysis of CiteSpace (CS) software.

Material and methods:
A total of 169 original publications were obtained from Web of Science using a comprehensive list for analysis with the CS scientometrics program. The parameters included range (2012–2022), visualization (display of completely integrated networks), precise collection criteria (top 10%), node form (institution, author, area, reference cited; referenced author, key words, and journal), and trimming (pathfinder, slice network).

Results:
Visual analysis of load monitoring and analysis for use in athletic training showed that ‘questionnaire’ was the most popular topic area in 2017 with 51 citations, while ‘training programmes’ emerged as a new area of study with 8 citations. In 2021 and 2022, the terms ‘energy expenditure’, ‘responses’, ‘heart rate’, and ‘validity’ gained popularity, increasing from a strength of 1.81 to 1.1. Liverpool John Moores University was the top institution, collaborating with 14 other organizations. The leading authors in this field were Close, Graeme L., and Gastin, Paul B. Most publications were found in the ‘SPORTS MED’ journal, with authors primarily based in the United Kingdom, the United States, and Australia.

Conclusions:
The findings of the study highlight the potential frontiers of load training analysis in the research and management of sports, emphasizing the importance of preparing businesses and institutes for the implementation of load training, and analysis in athletic training.

ABBREVIATIONS
CS – CiteSpace; WOS – Web of Science; WOSCC – Web of Science Core Collections; PCA – Principal Component Analysis; GPS – Global Positioning System; SPORTS MED – Sports Medicine (Journal); LLR – Log-Likelihood Ratio; MI – Mutual Information; VO(2)max – Maximum Oxygen Uptake
REFERENCES (46)
1.
Jiménez-García M, Ruiz-Chico J, Peña-Sánchez AR, et al. A Bibliometric Analysis of Sports Tourism and Sustainability (2002–2019). Sustainability [Internet]. 2020;12. Available from: https://www.mdpi.com/2071-1050....
 
2.
Hu K-H, Chen F-H, Tzeng G-H. Evaluating the Improvement of Sustainability of Sports Industry Policy Based on MADM. Sustainability [Internet]. 2016;8. Available from: https://www.mdpi.com/2071-1050....
 
3.
Ryan S, Kempton T, Impellizzeri FM, et al. Training monitoring in professional Australian football: theoretical basis and recommendations for coaches and scientists. Sci Med Football. 2020;4:52–58.
 
4.
Saw AE, Main LC, Gastin PB. Impact of Sport Context and Support on the Use of a Self-Report Measure for Athlete Monitoring. J Sports Sci Med. 2015;14:732–739.
 
5.
Song H. Application of embedded wearable devices in football training injury prevention. Microprocess Microsyst. 2021;82:103915.
 
6.
Sousa H, Gouveia ER, Marques A, et al. The Influence of Small-Sided Football Games with Numerical Variability in External Training Load. Sustainability. 2022;14:1000.
 
7.
Neupert E, Gupta L, Holder T, et al. Athlete monitoring practices in elite sport in the United Kingdom. J Sports Sci. 2022;40:1450–1457.
 
8.
Piras A, Raffi M, Atmatzidis C, et al. The Energy Cost of Running with the Ball in Soccer. Int J Sports Med. 2017;38:877–882.
 
9.
Hannon MP, Parker LJF, Carney DJ, et al. Energy Requirements of Male Academy Soccer Players from the English Premier League. Med Sci Sports Exerc. 2021;53:200–210.
 
10.
Wang Y, Mushtaq RT, Ahmed A, et al. Additive manufacturing is sustainable technology: citespace based bibliometric investigations of fused deposition modeling approach. Rapid Prototyp J [Internet]. 2022;28:654–675.
 
11.
Wang Y, Ahmed A, Azam A, et al. Applications of additive manufacturing (AM) in sustainable energy generation and battle against COVID-19 pandemic: The knowledge evolution of 3D printing. J Manuf Syst. 2021;60:709–733.
 
12.
Mushtaq RT, Iqbal A, Wang Y, et al. Parametric Effects of Fused Filament Fabrication Approach on Surface Roughness of Acrylonitrile Butadiene Styrene and Nylon-6 Polymer. Materials [Internet]. 2022;15:5206.
 
13.
Ahmed A, Azam A, Wang Y, et al. Additively manufactured nano-mechanical energy harvesting systems: advancements, potential applications, challenges and future perspectives. Nano Converg [Internet]. 2021;8:37.
 
14.
Azam A, Ahmed A, Wang H, et al. Knowledge structure and research progress in wind power generation (WPG) from 2005 to 2020 using CiteSpace based scientometric analysis. J Clean Prod. 2021;126496.
 
15.
Puce L, Trabelsi K, Trompetto C, et al. A Bibliometrics-Enhanced, PAGER-Compliant Scoping Review of the Literature on Paralympic Powerlifting: Insights for Practices and Future Research. Healthcare [Internet]. 2022;10.
 
16.
Chen C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. J Am Socr Infor Sci TechnoL. [Internet]. 2006;57:359–377.
 
17.
Morehen JC, Rosimus C, Cavanagh BP, et al. Energy Expenditure of Female International Standard Soccer Players: A Doubly Labeled Water Investigation. Med Sci Sports Exerc. 2022;54:769–779.
 
18.
Colosio AL, Pedrinolla A, Da Lozzo G, et al. Heart Rate-Index Estimates Oxygen Uptake, Energy Expenditure and Aerobic Fitness in Rugby Players. J Sports Sci Med. 2018;17:633–639.
 
19.
Clubb J, McGuigan M. Developing Cost-Effective, Evidence-Based Load Monitoring Systems in Strength and Conditioning Practice. Strength Cond J. 2018;40:75–81.
 
20.
Salagaras BS, Mackenzie-Shalders KL, Nelson MJ, et al. Comparisons of Daily Energy Intake vs. Expenditure Using the GeneActiv Accelerometer in Elite Australian Football Athletes. J Strength Cond Res. 2021;35:1273–1278.
 
21.
Roe M, Blake C, Gissane C, et al. Injury Scheme Claims in Gaelic Games: A Review of 2007–2014. J Athl Train. 2016;51:303–308.
 
22.
Zhang S, Mao H. Optimization Analysis of Tennis Players’ Physical Fitness Index Based on Data Mining and Mobile Computing. Wirel Commun Mob Comput. 2021;2021.
 
23.
Xie R, Xie Y, Lopez-Barron CR, et al. Ultra-stretchable conductive iono-elastomer and motion strain sensor system developed therefrom. Technol Innov. 2018;19:613–626.
 
24.
Van Reijen M, Vriend I, van Mechelen W, et al. Preventing recurrent ankle sprains: Is the use of an App more cost-effective than a printed Booklet? Results of a RCT. Scand J Med Sci Sports. 2018;28:641–648.
 
25.
Nouni-Garcia R, Rosario Asensio-Garcia M, Orozco-Beltran D, et al. The FIFA 11 programme reduces the costs associated with ankle and hamstring injuries in amateur Spanish football players: A retrospective cohort study. Eur J Sport Sci. 2019;19:1150–1156.
 
26.
Zhang J, Liu J, Chen Y, et al. Knowledge Mapping of Machine Learning Approaches Applied in Agricultural Management – A Scientometric Review with CiteSpace. 2021.
 
27.
Bradley WJ, Cavanagh BP, Douglas W, et al. Quantification of training load, energy intake, and physiological adaptations during a rugby preseason: a case study from an elite European rugby union squad. J Strength Cond Res. 2015;29:534–544.
 
28.
Beato M, Drust B. Acceleration intensity is an important contributor to the external and internal training load demands of repeated sprint exercises in soccer players. Res Sports Med. 2021;29:67–76.
 
29.
Anderson L, Drust B, Close GL, et al. Physical loading in professional soccer players: Implications for contemporary guidelines to encompass carbohydrate periodization. J Sports Sci. 2022;40:1000–1019.
 
30.
Anderson T, Adams WM, Martin KJ, et al. Examining Internal and External Physical Workloads Between Training and Competitive Matches Within Collegiate Division I Men’s Soccer. J Strength Cond Res. 2021;35:3440–3447.
 
31.
Gastin PB, Hunkin SL, Fahrner B, et al. Deceleration, acceleration, and impacts are strong contributors to muscle damage in professional Australian football. J Strength Cond Res. 2019;33:3374–3383.
 
32.
Bourdon PC, Cardinale M, Murray A, et al. Monitoring Athlete Training Loads: Consensus Statement. Int J Sports Physiol Perform. 2017;12:S2161–S2170.
 
33.
Akenhead R, Nassis GP. Training load and player monitoring in high-level football: Current practice and perceptions. Int J Sports Physiol Perform. 2016;11:587–593.
 
34.
Halson SL. Sleep in elite athletes and nutritional interventions to enhance sleep. Sports Med. 2014;44:13–23.
 
35.
Buchheit M, Manouvrier C, Cassirame J, et al. Monitoring Locomotor Load in Soccer: Is Metabolic Power, Powerful? Int J Sports Med. 2015;36:1149–1155.
 
36.
Bartlett JD, O’connor F, Pitchford N, et al. “Relationships Between Internal and External Training Load in Team Sport Athletes: Evidence for an Individualised Approach” by Bartlett JD et al. International Journal of Sports Physiology and Performance Section: Original Investigation Article. Journal: International Journal of Sports Physiology and Performance [Internet]. 2016; Available from: http://dx.doi.org/10.1123/ijsp....
 
37.
Anderson L, Orme P, Naughton RJ, et al. Energy Intake and Expenditure of Professional Soccer Players of the English Premier League: Evidence of Carbohydrate Periodization. Int J Sport Nutr Exerc Metab. 2017;27:228–238.
 
38.
Yu D, Xu Z, Pedrycz W, et al. Information sciences 1968–2016: A retrospective analysis with text mining and bibliometric. Inf Sci (NY). 2017;418–419:619–634.
 
39.
Salagaras BS, Mackenzie-Shalders KL, Slater GJ, et al. Increased carbohydrate availability effects energy and nutrient periodisation of professional male athletes from the Australian Football League. Appl Physiol Nutrition Metab. 2021;46:1510–1516.
 
40.
Highton J, Mullen T, Norris J, et al. The Unsuitability of Energy Expenditure Derived From Microtechnology for Assessing Internal Load in Collision-Based Activities. Int J Sports Physiol Perform. 2017;12:264–267.
 
41.
Hebert-Losier K, Yin NS, Beaven CM, et al. Physiological, kinematic, and electromyographic responses to kinesiology-type patella tape in elite cyclists. J Electromyography Kinesiol. 2019;44:36–45.
 
42.
Looney DP, Santee WR, Blanchard LA, et al. Cardiorespiratory responses to heavy military load carriage over complex terrain. Appl Ergon. 2018;73:194–198.
 
43.
Rabbani A, Clemente FM, Kargarfard M, et al. Match Fatigue Time-Course Assessment Over Four Days: Usefulness of the Hooper Index and Heart Rate Variability in Professional Soccer Players. Front Physiol. 2019;10.
 
44.
García-Ceberino JM, Gamero MG, Ibáñez SJ, et al. Are Subjective Intensities Indicators of Player Load and Heart Rate in Physical Education? Healthcare. 2022;10:3: 428.
 
45.
Lee JWY, Li C, Yung PSH, et al. The reliability and validity of a video-based method for assessing hamstring strength in football players. J Exerc Sci Fit. 2017;15:18–21.
 
46.
Akubat I, Barrett S, Sagarra ML, et al. The Validity of External: Internal Training Load Ratios in Rested and Fatigued Soccer Players. Sports. 2018;6:44.
 
eISSN:1898-2263
ISSN:1232-1966
Journals System - logo
Scroll to top