Next Article in Journal
A WeChat-Based Self-Management Intervention for Community Middle-Aged and Elderly Adults with Hypertension in Guangzhou, China: A Cluster-Randomized Controlled Trial
Next Article in Special Issue
Emotion, Psychological Well-Being and Their Influence on Resilience. A Study with Semi-Professional Athletes
Previous Article in Journal
The Impact of a School-Based Water, Sanitation and Hygiene Intervention on Knowledge, Practices, and Diarrhoea Rates in the Philippines
Previous Article in Special Issue
Prevalence of Relative Age Effect in Russian Soccer: The Role of Chronological Age and Performance
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Performance Differences of Temporal Parameters and Point Outcome Between Elite Men’s and Women’s Badminton Players According to Match-Related Contexts

by
Miguel-Ángel Gomez
1,*,
Fernando Rivas
1,2,
Jonathan D. Connor
3 and
Anthony S. Leicht
3
1
Department of Social Sciences, Physical Activity, Sport and Leisure, Polytechnic University of Madrid, 28031 Madrid, Spain
2
Spanish Badminton Federation, 28040 Madrid, Spain
3
Sport and Exercise Science, James Cook University, Townsville 4814, Australia
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2019, 16(21), 4057; https://doi.org/10.3390/ijerph16214057
Submission received: 26 September 2019 / Revised: 19 October 2019 / Accepted: 21 October 2019 / Published: 23 October 2019
(This article belongs to the Special Issue Health, Exercise and Sports Performance)

Abstract

:
Background: the aim of the present study was to identify the temporal and notational performance differences between elite men’s and women’s badminton players according to match type and set. Methods: the sample was composed of 60 men’s and 60 women’s matches classified by match type or duration: short (lower quartile), long (upper quartile) and regular matches (interquartile range). Temporal and notational variables were analysed for each match and compared between sexes accounting for match duration. Results: greater intensity for most variables (i.e., rally time, rest time, density, and strokes per match/rally) was exhibited in men’s matches compared with women’s matches (i.e., higher frequency between strokes). In addition, the greater intensity for men compared to women was more pertinent during long matches (13 significant variables) and less evident during short matches (six significant variables). Point outcome displayed similar trends for each sex during matches with more winners for men’s players when serving and more unforced errors for women’s players. Lastly, based on each match type, fewer sex differences were noted during sets 2 and 3, as the match progressed. Conclusion: men’s players performed at a greater intensity than women’s players for different match and set contexts, with this sex difference enhanced when controlling for match type and set. The development of sex- and match-specific scenarios will assist coaches and trainers in the design of specific training drills to enhance the athletic performance of elite badminton players.

1. Introduction

Badminton is an intermittent and dynamic racket sport (i.e., combining speed, high intensity actions, anticipation and rest intervals), where both competing players have to act and react during the rallies (i.e., interaction of technique, tactics and decision making) to gain temporal and positional advantages over their opponents in order to win the point [1,2,3,4,5]. Nowadays, the current badminton regulations (i.e., scoring system) have resulted in changes for players’ performances with longer matches incorporating more aggressive playing styles, different tactical patterns and reduced time between strokes during longer rallies [3,6]. Abian-Vicen et al. [1] have suggested that badminton is evolving with an increase in the intensity of rallies, sets and matches. The authors argued that the scoring system has altered the players’ performance profiles with constant adaptations to a high-intensity and demanding game (i.e., more rallies played, more strokes per rally, more variability of rally time and rest time during rallies). Similar to other racket sports [7,8], modelling the performance of elite badminton players is needed to improve players’ profiles and represent the real competition contexts (stable and unstable scenarios).
As a result of these evolving performance trends, most studies of badminton [9,10,11] have focused on identifying temporal and notational characteristics of men’s and women’s players during elite competitions. Abian-Vicen et al. [12] analysed 20 singles matches (only those played with two sets) from the Beijing Olympic Games (2008) (n = 10 matches for each sex), with total match duration, rally time, rest time, number or rallies, strokes per rally and shot frequency greater for men’s compared to women’s players. On the contrary, women’s players performed at a higher work density and played longer match times than men’s players. The authors did not find temporal variable differences between set 1 and 2. In addition, shorter rally times ranged between 3 and 6 s and were more frequent for women’s players, while longer rally times (>16 s) were more frequent for men’s players [12]. Subsequently, Gawin, et al. [10] investigated the performance characteristics of each badminton discipline (singles and doubles for each sex, and mixed doubles) during 50 matches played by the World top 10 players. These authors confirmed the previous findings of Abian-Vicen et al. [1,12] where men’s players performed at a higher intensity, while women’s players performed at a greater workload and longer playing time, compared to the opposite sex. More recently, Valldecabres, de-Benito, Casal, and Pablos [13] studied the differences between men’s and women’s singles matches during the 2015 World Badminton Championship. Their main findings indicated that men’s players experienced greater total match duration, real time played, effective time of play (%), rally time, strokes per rally, rest time, rest time at point interval (rest time at 11th point), and strokes per match than women’s players [13]. However, women exhibited a greater work density, frequency of strokes, and rest time between sets than men’s players [13]. More recently, Torres-Luque, Fernandez-Garcia, Blanca-Torres, Kondric, and Cabello-Manrique [14] studied the differences between sets in all the disciplines of badminton (singles, doubles and mixed doubles) for both sexes. Their results were in accordance with the previous studies cited above. However, a great disparity exists for the match duration of elite badminton studies with these ranging from 40 to 50 min for men and 17 to 28 min for women [1,8,13,14]. Establishing a distinctive approach that accounts for match duration and sets when examining the temporal parameters of men’s and women’s badminton matches would provide more realistic performance profiles for men’s and women’s players during long (three sets) and short (two sets) matches [14]. Previous studies in badminton [10,11,12,13,14] have not accounted for match type and set characteristics when examining sex differences in performances. Prior studies in other racket sports such as tennis [15,16,17], table tennis [18,19,20], squash [21,22] or paddle [23,24] have considered these crucial factors and emphasised the importance of analysing players´ performances according to match-related contexts. Therefore, the aim of the present study was to investigate the effect of sex on temporal parameters and notational variables (e.g., range of strokes and point outcome) in elite badminton accounting for match type and set. Our hypothesis was that men’s players would perform with greater intensity than women’s players for different match and set contexts. Clarification of sex differences during specific match scenarios (i.e., match type and sets) would assist coaches in the development of sex- and scenario-specific training and match strategies for success in elite badminton [13,14].

2. Materials and Methods

2.1. Sample

The sample was obtained from 60 men’s and 60 women’s matches (video recorded matches from the World Badminton Federation) played during the 2016 World Badminton Super Series. In order to control for the variability of match performances based on time in elite badminton [11], total match time was identified with the median, and upper and lower quartiles employed to establish three distinct types of matches: regular matches (within the interquartile range, n = 20 for each sex), short matches (below lower quartile, n = 10 matches for each sex) and long matches (above upper quartile, n = 10 matches for each sex). All data were obtained from a public site in accordance with the European Data Protection Law, and the current study was conducted with the approval of the Polytechnic University of Madrid Ethics Committee.

2.2. Procedure

The matches were examined by four experienced badminton coaches (10 years of experience as elite badminton coaches) using the video analysis program Dartfish (Friburgo, Switzerland), with match temporal parameters and point outcome being the key variables. Reliability (inter- and intra-observer) for match observations were assessed as good and very good (Kappa ≥ 0.81; Pearson’s correlation coefficient: r > 0.86; intraclass correlation coefficient (ICC) ≥ 0.85, and the typical error of measurement (TEM) ≤ 0.46) using 12 randomly selected matches [25,26].
The independent variable was sex, while the dependent variables for each match were considered according to the scientific available research [1,2,3,4,5,6,7,8,9,10,11,12,13,14,27,28]: match/set duration, rally time, real playing time, rest time, real rest time, density, number of strokes per match/set, number of strokes per rally, frequency of strokes, number of rallies, effective playing time (%) and effective rest time (%), number of strokes per rally and rally outcome. In addition, point outcome (winning the rally as the player serving or receiving; and the type of action performed = winning stroke, forced error or unforced error) and range of strokes per rally (considering 2 strokes per range where each player performs one stroke each: A: 1–2; B: 3–4; C: 5–6; D: 7–8; E: 9–10; F: 11–12; G: 13–14; H: 15–16; I: 17–18; J: 19–20; and K: >20) were also considered as notational analysis variables.

2.3. Statistical Analysis

Firstly, the Shapiro–Wilks test was used to check data normality assumptions for all temporal parameters (p < 0.05) followed by the use of the Student’s t-test to analyse sex differences for variables and each match context. Cohen’s d effect size (ES) was calculated and interpreted via the following ranges: 0.20 = small effect, 0.50 = medium effect, and 0.80 = large effect [29]. Secondly, relationships between sex, and range of strokes and point outcome notational variables were determined using the Pearson’s Chi-square test (Crosstabs Command) with adjusted residuals (ARs) > 1.96 classified as significant. Additionally, the Cramer’s V test was conducted to estimate ES with interpretation based on the following values: 0.10 = small effect, 0.30 = medium effect, and 0.50 = large effect [30]. Statistical analyses were undertaken using the statistical software IBM SPSS for Windows version 25 (IBM. Corp. Armonk, NY, USA) and significance level was set to 0.05.

3. Results

The descriptive and univariate differences between men’s and women’s players for all temporal parameters are shown in Table 1. Significant sex differences (p < 0.05) were identified with women’s players exhibiting a greater frequency of strokes (medium ES) and less rally time, rest time, density, strokes per rally, and strokes per match (small–medium ES) compared to men’s players. Significant relationships were identified between the range of strokes and sex (Table 1, small ES) with higher frequencies of short ranges (A and B) for women’s players and higher frequencies of long ranges (H, I and K) for men’s players.
According to each match type, significant differences (p < 0.05) between sexes were noted for short matches, with men’s players exhibiting greater rest time and effective rest time (%) (large ES) and lower density and frequency of strokes (large ES) compared to women’s players (Table 2). Significant relationships were identified between the range of strokes and sex (small ES = 0.15), with men’s players performing more long rallies (range K) compared to women’s players (Table 2). For regular matches, men’s players experienced a greater number of strokes per match (large ES), and greater match duration, rally time, real playing time, density and strokes per rally (medium ES) compared to women’s players (Table 2). Significant relationships were identified between the range of strokes (small ES) and sex with more short (range A) and long rallies (range K) performed by women’s and men’s players, respectively (Table 2). For long matches, men’s players experienced significantly greater rally time (large ES), density (large ES), strokes per rally (small ES), strokes per match (large ES) and effective playing time (large ES), compared to women’s players (Table 2). In contrast, women’s players experienced a significantly greater frequency of strokes (large ES) and number of rallies (small ES, Table 2). Significant relationships were identified between sexes (small ES) with more short (range A) and long rallies (range K) performed by women’s and men’s players, respectively (Table 2).
Results for short (Table 3), regular (Table 4) and long (Table 5) matches with consideration of set have been provided. During short matches, significant differences between sexes were noted for set 1 with men’s players experiencing greater real rest time, strokes per set, number of rallies and effective playing time (all large ES) compared to women’s players (Table 3). In contrast, women’s players experienced greater real playing time, frequency of strokes and effective rest time (all large ES) compared to men’s players (Table 3). During set 2, men’s players experienced greater real rest time) and strokes per set (all large ES) compared to women’s players (Table 3). No significant relationships between the range of strokes and sex were noted during either set (Table 3).
During regular matches, significant differences between sexes were noted with men’s players experiencing greater real playing time (large ES) and strokes per match (large ES) during all sets (Table 4). Men’s players also experienced greater real rest time (large ES) during sets 2 and 3 and greater set duration (large ES) during set 3 (Table 4). Significant relationships between the range of strokes and sex were identified for sets 1 and 2 (all small ES) with more short (range A) and long (range K) rallies performed by women’s and men’s players, respectively (Table 4).
During long matches, significant differences between sexes were noted with men’s players experiencing greater real playing time, real rest time and strokes per match (all large ES) during sets 1 and 2 compared to women’s players (Table 5). Men’s players also experienced greater effective play time (large ES) during set 1 compared to women’s players who experienced greater effective and real rest time (large ES) during sets 1 and 3, respectively (Table 5). Significant relationships between the range of strokes and sex were identified during sets 1 and 2 (small ES) with more long rallies (range K) performed by men’s players compared to women’s players, while women’s players performed more short rallies (range A) during set 1 and 3 compared to men’s players (Table 5).
Results of sex differences for point outcome are presented in Table 6. Significant relationships were identified for: (i) all matches (small ES), with more points won via winners (19.1% vs. 15.1%) for men’s players when serving, with more points won via forced errors (15.5% vs. 13.8%); for women’s players when serving, with more points won via unforced errors (21.6% vs. 18.1%) for women’s players when receiving; (ii) short matches, with more points won via unforced errors (19.7% vs. 14.4%) for women’s players when serving; (iii) regular matches (small ES), with more points won via winners (19.0% vs. 15.0%) for men’s players when serving and more points won via unforced errors (22.2% vs. 17.4%) for women’s players when receiving; and (iii) long matches (small ES), with more points won via winners (18.9% vs. 13.7%) for men’s players when serving and with more points won via forced errors (16.6% vs. 13.3%) for women’s players when serving
Results of set differences for point outcome are presented in Table 7. For regular matches, significant relationships were identified during: (i) set 1 (small ES), with more points won via winners (19.6% vs. 13.5%) for men’s players when serving while more points were won via forced errors (17.2% vs. 12.6%) and unforced errors (22.4% vs. 18.0%) for women’s players when serving and receiving, respectively; and (ii) sets 2 and 3 (small ES), with more points won via unforced errors (21.3% vs. 17.3%; and 26.1% vs. 15.3%, respectively) for women’s players when receiving (Table 7). Lastly, for long matches, significant relationships between sexes were noted during set 1 (small ES), with more points won via winners (22.9% vs. 16.2%) for women’s players when receiving (Table 7).

4. Discussion

The aim of the study was to investigate the sex differences on temporal parameters and notational variables (range of strokes and point outcome) depending on match type and set in elite badminton matches. Similar to prior studies, men’s players performed at higher intensities than women’s players for most of the temporal parameters analysed during all matches (e.g., rally time, rest time or number of strokes) [1,3,9,10]. However, the analysis based on match type and set allowed the identification of different trends and performance profiles related to each sex in those contexts (e.g., short, regular or long matches). In addition, the notational variables (i.e., point outcome and range of strokes) showed different performance profiles for men’s and women’s players in each match and set, highlighting the importance of considering performance variability related to context factors [14]. The current study has added to the knowledge base for racket sports, with coaches encouraged to consider sex differences and their associated controlling match-related contexts [7,8] during the development of training tasks.
Irrespective of match length, a number of temporal parameters were greater for males (i.e., rally time, rest time, density, strokes per rally, strokes per match/set), albeit lower frequency between strokes compared to females (see Table 8). These findings could be related to men´s physical capacities and strength that allow them to perform with greater intensity and explosiveness during rallies compared to women´s players [12]. Males also had a consistently greater range of strokes (e.g., H: 15–16, I: 17–18, and K: >20), while females demonstrated increased short-range strokes (e.g., A: 1–2, B: 2–3). In fact, men´s players were able to maintain the physical intensity with technical effectiveness during the rallies due to their experiences with quick and high-demand rallies that required anticipation and explosive movements [14]. Finally, men had a greater amount of serving winners, while women had greater serving forced errors and receiving unforced errors. These results support those of Avian et al. [12] who reported that men´s players played with higher stroke frequency and explosive actions (e.g., Smash) surprising the opponents and finishing the point with a winner. These results indicate the importance of rest time and recovery between points that may impact on forced and unforced errors (with greater effect for women´s players during long and regular matches) [10,12,14]. Additionally, these findings were consistent with previous literature in badminton [1,3,9,10], whereby men’s matches had a tendency to be longer in duration due to an increased number of certain temporal parameters (e.g., rally time, rest time, density, strokes per rally, strokes per match/set).
A number of significant differences were evident between both sexes, and the match type and sequence of sets. During shorter matches, there was a tendency for an increase in real playing time and real rest time across both sets for men, in comparison to women’s matches. There was also a greater propensity of strokes per match/set, number of rallies, and effective playing time (%), albeit only during the first set of men’s short matches. These trends were previously identified for badminton matches reflecting the increase of physical intensity during longer matches/sets of authentic competitions [1,3,12,14]. Additionally, there was an overall increase in the number of strokes per set, rallies and effective playing time (%), while women had a greater frequency of strokes and effective rest time. During regular length matches, men displayed greater real playing time, strokes per match/set, while women had greater, receiving unforced errors. During the early sequence of sets (e.g., sets 1 and 2), men demonstrated a greater range of strokes (K: >20) and served more winners, while during the latter sets, there was an increase in rally time and rest time. This result likely explains the reduced number of received unforced errors, as this reduction would likely lead to longer playing time. According to Chiminazzo et al. [31], higher temporal demands of long rallies required an increase of total rest time for athletes. Thus, elite badminton players may be more aware of spending more rest time between points and slowing down the playing style or rhythm of the last set (i.e., effective recovery and better preparation for the next point) [32]. Finally, during long matches, rally time and real playing time were significantly greater for men’s competition. Men also had a greater number of strokes per rally, strokes per match/set, and effective playing time (%), while women reported greater density, frequency of strokes, and effective rest time (%). Women also had a shorter range of strokes and serving of forced errors in comparison with men’s matches, who had a greater range of stokes and serving winners. These results support the suggestion that badminton player´s performances evolve from a predominant quantitative (e.g., longer matches and higher intensity during set 3) to a qualitative (e.g., an increase of unforced errors in set 3 and long matches) focus [14]. In particular, the temporal requirements were most relevant during long matches, but as the match progressed, the frequency of strokes increased with the execution effectiveness compromised by fatigue [14]. Together, these findings highlight the differing temporal parameters, range of strokes, and point outcomes between men’s and women’s competition with important consideration of the duration of matches and the sequence of sets. Therefore, consideration of these current trends within matches should be undertaken by coaches and trainers to improve training plans and competition management accounting for match type and set.
The current study enabled the novel exploration of temporal and notational demands of men’s and women’s, elite badminton players while considering performance variability of match-related contexts (match type and set). However, some limitations of the current study should be noted and considered for future studies. The temporal and notational variables examined in the current study were based on prior work [1,2,3,4,5,6,7,8,9,10,11,12,13,14]. However, others including technical- (e.g., type of serve or technical skill used to end the rally), tactical- (e.g., strokes zones distribution for both sexes), or contextual-related (i.e., competition stage and quality of opposition) variables could be examined for a greater understanding of elite athletic performance. The current study included matches from the same tournament, with an examination of performance evolution over multiple tournaments (e.g., Olympic Games since Beijing 2008 to Tokyo 2020) likely providing a comprehensive reflection of match performance trends for each sex. Indeed, further research might consider a multivariate approach to define all possible real match-scenarios for men’s and women’s competition to support staff (coaches, trainers, etc) in the development of athletes with specialised preparation.

5. Practical Applications

The current findings have significant practical implications for coaches and players for their preparation of various match scenarios [14,19]. A tailored approach using real match demands for men’s and women’s players would offer a better foundation for the development of integrated conditioning plans [31,32]. Specifically, men’s and women’s players perform differently during short, regular or long matches, with the current reference temporal parameters encouraged for use in the design of training drills (i.e., rally and rest time, density and strokes per rally), controlling for total playing time (real playing time and effective playing time) and each match type and set. In addition, the use of a key variable such as the range of strokes (a minimum number of strokes to play short rallies in women’s players and a greater number of strokes during long rallies in men’s players) may improve the requirements for each drill and minimise unforced errors under fatigue conditions. Subsequently, we would suggest that training focus equally on total time duration of regular matches (50% of training time), and the needs and requirements of short and long matches (50% of training time). For example, the specific short/long match training could include specific tasks and/or worst case scenarios such as quick rallies (one to two strokes for women; one to four for men), long rallies (longer than 18 strokes for men; longer than 20 strokes for women), sequences of short and high-intensity rallies that accumulate fatigue (rallies with eight strokes and 6 seconds of time duration for men’s players; 10 strokes and 8 seconds for women´s players), and simulation of critical match instants affected by fatigue such as the last rallies of a close match during set 3 (rally duration of 11–12 seconds and with density of lower than 0.40) or the last point of each set and interval where decision making is potentially compromised (e.g., players use winners to end the rally quickly).

6. Conclusions

In conclusion, the current study of badminton performance has confirmed that men’s players perform at a greater intensity than women’s players for different match and set contexts. Specifically, greater intensity for temporal parameters was identified in men’s matches (i.e., rally time, rest time, density, and strokes per match/rally) compared with women’s matches (i.e., higher frequency between strokes). In addition, the sex differences varied according to match type, with greater intensity in men’s matches more relevant during long matches (e.g., significant differences in nine temporal parameters), and less evident during short matches (e.g., significant differences in five temporal parameters). In contrast, the point outcome displayed similar trends for each sex during matches with more winners for men’s players when serving and more unforced errors for women’s players. Lastly, based on each match type, fewer sex differences were noted during sets 2 and 3, as the match progressed. Further, the sex differences for elite badminton players were enhanced when controlling for match type and set highlighting the importance of these factors during performance analyses in badminton. Clarification of sex differences during specific badminton match scenarios will assist coaches and trainers to design specific training drills that simulate the current temporal and notational profiles of real match types.

Author Contributions

Conceptualisation, M.-Á.G. and F.R.; methodology, M.-Á.G., F.R. and A.S.L.; software, M.-Á.G.; validation, M.-Á.G. and F.R.; formal analysis, M.-Á.G., A.S.L. and J.D.C.; investigation, M.-Á.G., F.R., A.S.L. and J.D.C; resources, M.-Á.G.; data curation, M.-Á.G. and A.S.L.; writing—original draft preparation, M.-Á.G., A.S.L. and J.D.C.; writing—review and editing, M.-Á.G., A.S.L. and J.D.C.; visualisation, M.-Á.G., A.S.L. and J.D.C.; supervision, M.-Á.G.; A.S.L.; project administration, M.-Á.G.; funding acquisition, M.-Á.G.

Funding

The Ministry of Economy and Competitiveness of Spain supported the present study with the project “Estudio de los complejos de juego y los perfiles de rendimiento en bádminton de élite COMPLEXBAD” (DEP2015- 67231-R). Additionally, the Ministry of Education, Culture and Sport of Spain supported the corresponding author, under the mobility Grant “Salvador de Madariaga” (PRX18/00098) in cooperation with James Cook University (Townsville, Australia).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Abián, P.; Castanedo, A.; Feng, X.Q.; Sampedro, J.; Abian-Vicen, J. Notational comparison of men’s singles badminton matches between Olympic Games in Beijing and London. Int. J. Perform. Anal. Sport 2014, 14, 42–53. [Google Scholar] [CrossRef]
  2. Chow, J.Y.; Seifert, L.; Hérault, R.; Chia, S.J.Y.; Lee, M.C.Y. A dynamical system perspective to understanding badminton singles game play. Hum. Mov. Sci. 2014, 33, 70–84. [Google Scholar] [CrossRef] [PubMed]
  3. Laffaye, G.; Phomsoupha, M.; Dor, F. Changes in the Game Characteristics of a Badminton Match: A Longitudinal Study through the Olympic Game Finals Analysis in Men’s Singles. J. Sports Sci. Med. 2015, 14, 584–590. [Google Scholar] [PubMed]
  4. Phomsoupha, M.; Laffaye, G. The science of badminton, game characteristics, anthropometry, physiology, visual fitness and biomechanics. Sport Med. 2015, 45, 473–495. [Google Scholar] [CrossRef]
  5. Barreira, J.; Chiminazzo, J.G.C.; Fernandes, P.T. Analysis of point difference established by winners and losers in games of badminton. Int. J. Perform. Anal. Sport 2016, 16, 687–694. [Google Scholar] [CrossRef]
  6. Seth, B. Determination factors of badminton game performance. Int. J. Phys. Ed. Sport Health 2016, 3, 20–22. [Google Scholar]
  7. Lees, A. Science and the major racket sports: A review. J. Sports Sci. 2003, 21, 707–732. [Google Scholar] [CrossRef]
  8. Hughes, M.; Hughes, M.T.; Behan, H. The evolution of computerised notational analysis through the example of racket sports. Int. J. Sport Sci. Eng. 2007, 1, 3–28. [Google Scholar]
  9. Cabello, D.; Padial, P.; Lees, A.; Rivas, F. Temporal and Physiological Characteristics of Elite Women’s and Men’s Singles Badminton. Int. J. Appl. Sport Sci. 2004, 16, 1–12. [Google Scholar]
  10. Gawin, W.; Beyer, C.; Seidler, M. A competition analysis of the single and double disciplines in world-class badminton. Int. J. Perform. Anal. Sport 2015, 15, 997–1006. [Google Scholar] [CrossRef]
  11. Liddle, D.; O’Donoghue, P. Notational Analysis of rallies in European circuit badminton. In Science and Racket Sports II; Lees, A., Maynard, I., Hughes, M., Reilly, T., Eds.; E and FN Spon: London, UK, 1998; pp. 275–281. [Google Scholar]
  12. Abian-Vicen, J.; Castanedo, A.; Abian, P.; Sampedro, J. Temporal and notational comparison of badminton matches between men’s singles and women’s singles. Int. J. Perform. Anal. Sport 2013, 13, 310–320. [Google Scholar] [CrossRef]
  13. Valldecabres, R.; De Benito, A.M.; Casal, C.A.; Pablos, C. 2015 Badminton World Championship: Singles final men’s vs women’s behaviours. J. Hum. Sport Exerc. 2017, 12, S775–S788. [Google Scholar]
  14. Torres-Luque, G.; Fernández-García, Á.I.; Blanca-Torres, J.C.; Kondric, M.; Cabello-Manrique, D. Statistical Differences in Set Analysis in Badminton at the RIO 2016 Olympic Games. Front. Psychol. 2019, 10, 731. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Kolman, N.S.; Kramer, T.; Elferink-Gemser, M.T.; Huijgen, B.C.; Visscher, C. Technical and tactical skills related to performance levels in tennis: A systematic review. J. Sport Sci. 2019, 37, 108–121. [Google Scholar] [CrossRef] [PubMed]
  16. Martin, C.; Bideau, B.; Touzard, P.; Kulpa, R. Identification of serve pacing strategies during five-set tennis matches. Int. J. Sport Sci. Coach. 2019, 14, 32–42. [Google Scholar] [CrossRef]
  17. Torres-Luque, G.; Fernández-García, Á.I.; Cabello-Manrique, D.; Giménez-Egido, J.M.; Ortega-Toro, E. Design and Validation of an Observational Instrument for the Technical-Tactical Actions in Singles Tennis. Front. Psychol. 2018, 9, 2418. [Google Scholar] [CrossRef]
  18. Fuchs, M.; Liu, R.; Lanzoni, I.M.; Munivrana, G.; Straub, G.; Tamaki, S.; Yoshida, K.; Zhang, H.; Lames, M. Table tennis match analysis: A review. J. Sports Sci. 2018, 36, 1–10. [Google Scholar] [CrossRef]
  19. Wang, J. Comparison of table tennis serve and return characteristics in the London and the Rio Olympics. Int. J. Perform. Anal. Sport 2019, 19, 683–697. [Google Scholar] [CrossRef]
  20. Furjan-Mandić, G.; Munivrana, G.; Kondrič, M. Determining the Structure and Evaluating the Role of Technical-Tactical Elements in Basic Table Tennis Playing Systems. Int. J. Sports Sci. Coach. 2015, 10, 111–132. [Google Scholar]
  21. Ramón-Llin, J.; Guzmán, J.F.; Llana, S.; Martínez-Gallego, R.; James, N.; Vučković, G. The effect of the return of serve on the server pair’s movement parameters and rally outcome in padel using cluster analysis. Front. Psychol. 2019, 10, 1194. [Google Scholar] [CrossRef]
  22. Courel-Ibáñez, J.; Martinez, B.J.S.A.; Marín, D.M. Exploring game dynamics in padel: Implications for assessment and training. J. Strength Cond. Res. 2019, 33, 1971–1977. [Google Scholar] [CrossRef] [PubMed]
  23. Torres-Luque, G.; Ramirez, A.; Cabello-Manrique, D.; Nikolaidis, T.P.; Alvero-Cruz, J.R. Match analysis of elite players during paddle tennis competition. Int. J. Perform. Anal. Sport 2015, 15, 1135–1144. [Google Scholar] [CrossRef]
  24. Courel-Ibáñez, J.; Martínez, B.J.S.A.; Cañas, J. Game performance and length of rally in professional paddle players. J. Hum. Kinet. 2017, 55, 161–169. [Google Scholar] [CrossRef] [PubMed]
  25. Altman, D.G. Mathematics for Kappa. Practical Statistics for Medical Research; Chapman & Hall: London, UK, 1991; pp. 406–407. [Google Scholar]
  26. Hopkins, W.G. Measures of Reliability in Sports Medicine and Science. Sports Med. 2000, 30, 1–15. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Evans, S. Winners and errors. The Badminton Association of England Limited. Coaches Bull. Courtside 1998, 108, 8–9. [Google Scholar]
  28. Yadav, S.; Tyagi, N.; Tripathi, R.; Kaushik, P. Analysis of unforced errors and mental toughness of winners and losers in badminton. Sci. J. Sport Exer. 2007, 3, 11–16. [Google Scholar]
  29. Cohen, J. Statistical Power Analysis for the Behavioral Sciences; Abingdon: London, UK, 1988. [Google Scholar]
  30. Field, A. Discovering Statistics Using IBM SPSS Statistics, 4th ed.; Sage: London, UK, 2013. [Google Scholar]
  31. Chiminazzo, J.G.C.; Barreira, J.; Luz, L.S.M.; Saraiva, W.C.; Cayres, J.T. Technical and timing characteristics of badminton men’s single: Comparison between groups and play-offs stages in 2016 Rio Olympic Games. Int. J. Perform. Anal. Sport 2018, 18, 245–254. [Google Scholar] [CrossRef]
  32. Abdullahi, Y.; Coetzee, B. Notational singles match analysis of male badminton players who participated in the African Badminton Championships. Int. J. Perform. Anal. Sport 2017, 17, 1–16. [Google Scholar] [CrossRef]
Table 1. Differences in temporal parameters and range of strokes between men’s and women’s badminton players.
Table 1. Differences in temporal parameters and range of strokes between men’s and women’s badminton players.
VariablesAll Matchesp-ValueES
MenWomen
Temporal ParametersMSDMSD
Match duration49.1418.0446.9519.570.680.12
Rally time9.918.039.056.55<0.01 *0.13
Real playing time13.605.1812.194.510.120.29
Rest time22.9412.7222.0411.910.01 *0.07
Real rest time29.5711.6028.0412.620.500.13
Density0.450.290.430.260.01 *0.07
Strokes per rally10.638.288.736.58<0.001 *0.25
Strokes per match880.7318.3714.6266.70.01 *0.57
Frequency of strokes0.900.131.060.30<0.001 *0.69
Number of sets2.320.472.260.440.540.13
Number of rallies82.8920.1780.6419.330.640.11
Effective playing time (%)31.683.6931.114.490.470.14
Effective rest time (%)68.323.6968.894.490.470.14
Range of strokes%n%nχ2AR
A (1–2)5.725310.9544 9.2 †
B (3–4)17.678719.2960 2.1 †
C (5–6)15.770316.6826 1.1
D (7–8)13.359414.0700 1.1
E (9–10)9.844010.1506 0.5
F (11–12)8.23667.8387174.860.8
G (13–14)5.82595.5274 0.6
H (15–16)5.32363.9196 3.1 †
I (17–18)4.41953.2157 3.1 †
J (19–20)3.01342.6128 1.3
K (21+)11.45086.3312 8.8 †
Total number of ranges44754990
p value<0.001 *
ES0.14
* p < 0.05; † adjusted residual (AR) ≥ |2.0|; ES = effects size.
Table 2. Differences in temporal parameters and range of strokes between men’s and women’s badminton players according to match type.
Table 2. Differences in temporal parameters and range of strokes between men’s and women’s badminton players according to match type.
VariablesShort MatchesRegular MatchesLong Matches
MenWomenpESMenWomenpESMenWomenpES
Temporal ParametersMSDMSDMSDMSDMSDMSD
Match duration29.013.2126.953.630.190.6045.396.8541.897.160.04 *0.5082.075.0583.5410.500.690.18
Rally time8.062.448.150.730.710.059.591.528.671.300.01 *0.6512.061.2310.541.860.070.96
Real playing time508.2130.0524.956.70.910.17753.3140.3665.46135.40.01 *0.641367.3143.31206.5228.20.04 *0.84
Rest time16.701.6414.102.270.01 *1.3122.352.3921.352.530.050.4128.552.0828.124.440.960.12
Real rest time998.4130.8856.3173.60.060.921655.1230.61541.0258.70.080.473062.9192.33054.6550.70.780.02
Density0.480.120.600.120.04 *1.000.440.060.410.060.04 *0.500.420.050.370.030.01 *1.21
Strokes per rally8.276.896.714.390.060.2710.337.748.596.470.01 *0.2512.629.5510.137.520.01 *0.29
Strokes per match528.5128.6432.868.20.060.93822.2141.5662.6139.20.01 *1.371431.7136.81160.0196.90.01 *1.60
Frequency of strokes0.920.041.080.090.01 *2.300.900.030.990.070.491.670.930.031.010.060.01 *1.69
Number of rallies63.906.1964.505.500.650.1078.4714.6875.3812.660.060.23113.43.69114.45.940.03 *0.20
Effective playing time (%)33.575.4238.504.610.080.9831.202.8530.072.800.420.4030.952.4328.361.760.02 *1.22
Effective rest time (%)66.435.4261.504.610.02 *0.9868.802.8569.932.800.490.4069.052.4371.641.760.671.22
Range of strokes%n%nχ2AR%n%nχ2AR%n%nχ2AR
A (1–2)9.46011.977 1.05.113811.3349 5.5 †4.9559.4118 2.8 †
B (3–4)23.214824.5158 0.318.148819.5602 0.913.315115.9200 1.1
C (5–6)18.912122.3144 0.916.043216.8520 0.513.215012.9162 0.2
D (7–8)13.98916.4106 0.813.837313.4415 0.311.613214.2179 1.2
E (9–10)9.9638.756 0.510.026910.2316 0.29.510810.7134 0.6
F (11–12)6.6425.73727.70.48.42267.7238117.50.68.6988.911256.00.1
G (13–14)4.1264.026 0.05.91605.4166 0.66.4736.582 0.1
H (15–16)4.1262.214 1.45.11383.9121 1.56.3724.861 1.1
I (17–18)3.8241.49 1.94.31163.3103 1.34.9553.645 1.0
J (19–20)2.3151.711 0.63.0812.576 0.83.4383.341 0.1
K (21+)3.9251.17 2.3 †10.42815.9181 4.2 †17.82029.9124 3.6 †
Total number of ranges639645 2.7023.087 1.1341.288
p<0.001 * <0.001 * <0.001 *
ES0.15 0.14 0.15
* p < 0.05; † AR = |2.0|.
Table 3. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during short matches.
Table 3. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during short matches.
VariablesSet 1Set 2
MenWomenpESMenWomenpES
Temporal ParametersMSDMSDMSDMSD
Set duration13.241.7912.551.150.310.4614.872.6612.634.440.190.61
Rally time7.856.098.394.630.830.108.057.637.914.450.960.02
Real playing time244.875.68258.544.500.01 *2.67263.366.11266.424.240.210.58
Rest time15.746.3014.054.800.510.3017.559.7014.258.740.430.36
Real rest time459.606.01404.584.46<0.01 *10.4538.829.24451.746.09<0.01 *11.1
Density0.510.320.630.320.410.380.490.320.610.310.410.38
Strokes per rally8.136.266.814.430.590.248.417.516.614.360.520.29
Strokes per set253.6055.81209.9030.730.04 *0.97274.9089.49209.9030.730.04 *0.97
Frequency of strokes0.910.141.180.350.03 *1.010.900.141.140.340.060.92
Number of rallies34.794.9230.802.250.03 *1.0432.704.7633.703.400.590.24
Effective playing time (%)65.214.9239.103.55<0.01 *6.0832.346.6437.916.180.070.87
Effective rest time (%)34.796.0960.903.55<0.01 *6.0867.666.6462.096.180.070.87
Range of strokes%n%nχ2AR%n%nχ2AR
A (1–2)9.93112.338 0.68.92911.639 0.8
B (3–4)21.86823.472 0.324.58025.586 0.2
C (5–6)18.65822.469 0.719.36322.375 0.6
D (7–8)14.44516.651 0.513.54416.355 0.7
E (9–10)11.2358.125 0.98.6289.231 0.2
F (11–12)7.1224.51414.170.96.1206.82323.660.3
G (13–14)3.8124.915 0.44.3143.311 0.5
H (15–16)3.8123.210 0.34.3141.24 1.7
I (17–18)2.992.37 0.34.6150.62 2.3
J (19–20)2.681.65 0.62.171.86 0.2
K (21+)3.8120.62 0.94.0131.55 1.4
Total number of ranges312308 327337
p0.17 0.01
ES0.15 0.19
* p < 0.05.
Table 4. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during regular matches.
Table 4. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during regular matches.
VariablesSet 1Set 2Set 3
MenWomenpESMenWomenpESMenWomenpES
Temporal ParametersMSDMSDMSDMSDMSDMSD
Set duration18.843.0918.692.080.850.0618.913.2118.733.550.860.0520.272.4417.181.76<0.01 *1.45
Rally time9.567.128.696.220.680.139.397.718.606.360.730.119.487.458.376.510.620.16
Real playing time338.46.80314.16.12<0.01 *3.75332.97.43301.25.91<0.01 *4.72348.47.35288.06.04<0.01 *8.98
Rest time20.919.7420.377.440.840.0623.1313.0222.1511.680.800.0822.3914.3520.138.410.550.19
Real rest time697.98.98695.16.880.280.35774.211.60731.69.59<0.01 *4.00777.913.94652.88.01<0.01 *11.0
Density0.470.290.430.260.650.150.430.290.400.230.720.120.420.230.430.310.910.04
Strokes per rally10.397.568.586.360.420.2610.308.068.576.370.460.2410.307.618.636.680.470.23
Strokes per match367.873.9310.149.30.01 *0.92365.463.12300.369.040.01 *0.98378.552.3297.085.78<0.01 *1.14
Frequency of strokes0.900.121.050.310.050.640.890.131.030.290.060.620.890.120.960.250.270.36
Number of rallies35.383.2236.132.730.430.2635.473.9135.033.870.720.1136.754.4634.433.950.090.55
Effective playing time (%)32.713.1731.112.560.350.5630.364.0529.183.450.330.3130.951.7530.224.880.530.20
Effective rest time (%)67.293.1768.892.560.350.5669.644.0570.823.450.330.3169.051.7569.784.880.530.20
Range of strokes%n%nχ2AR%n%nχ2AR%n%nχ2AR
A (1–2)4.35212.2176 4.6 †5.8709.9139 2.5 †5.41614.134 2.4
B (3–4)19.022818.8271 0.117.821520.7290 1.115.34517.041 0.4
C (5–6)15.318416.9244 0.716.519916.8235 0.116.74917.041 0.1
D (7–8)13.015613.6196 0.314.717713.3186 0.713.64013.733 0.0
E (9–10)9.61159.8142 0.110.012010.9153 0.511.6348.721 0.8
F (11–12)9.31127.711172.051.07.3887.911046.350.38.8267.11716.090.5
G (13–14)6.4774.971 1.15.2635.678 0.36.8207.117 0.1
H (15–16)6.0724.260 1.44.1503.651 0.45.4164.110 0.0
I (17–18)3.9473.044 0.84.6553.853 0.74.8142.56 0.5
J (19–20)3.0362.739 0.33.0362.130 0.93.192.97 1.0
K (21+)10.31246.391 2.4 †11.01325.476 3.4 †8.5255.814 0.9
Total number of ranges12031445 12051401 294241
p<0.001 <0.001 0.10
ES0.17 0.13 0.17
* p < 0.05; † AR = |2.0|.
Table 5. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during long matches.
Table 5. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during long matches.
VariablesSet 1Set 2Set 3
MenWomenpESMenWomenpESMenWomenpES
Temporal ParametersMSDMSDMSDMSDMSDMSD
Set duration25.963.1123.373.570.340.7725.254.7024.624.060.750.1427.133.6330.196.810.230.56
Rally time12.859.9410.207.170.240.3111.469.2910.237.210.740.1511.859.0011.188.550.870.08
Real playing time490.99.83381.16.81<0.01 *2.11433.38.85381.26.85<0.01 *6.58443.38.88444.117.710.830.09
Rest time26.9812.4725.4612.900.530.1227.7114.2427.3512.170.950.0330.9216.1231.5418.980.940.04
Real rest time976.512.14900.212.08<0.01 *3.17991.913.17964.610.87<0.01 *2.261094.515.601189.815.79<0.01 *6.07
Density0.480.320.410.220.570.320.420.270.380.200.710.170.400.260.360.210.710.17
Strokes per rally13.4710.069.687.080.340.4311.959.489.847.200.580.2512.459.1210.868.290.690.18
Strokes per match514.467.94361.864.75<0.01 *2.23451.796.98366.770.230.04 *1.00465.673.20431.5131.50.480.32
Frequency of strokes0.910.121.100.290.860.850.930.121.070.270.150.670.900.111.040.260.130.70
Number of rallies38.202.2537.363.200.510.3037.803.0837.273.070.700.1737.402.6739.734.840.200.59
Effective playing time (%)33.452.1829.732.18<0.01 *1.7130.523.5928.422.450.150.6828.862.5526.931.760.060.88
Effective rest time (%)66.552.1870.272.18<0.01 *1.7169.483.5971.582.450.150.6871.142.5573.071.760.060.88
Range of strokes%n%nχ2AR%n%nχ2AR%n%nχ2AR
A (1–2)3.11210.041 2.6 †6.9268.334 0.54.5179.843 2.0
B (3–4)14.45516.568 0.512.74817.672 1.212.84813.760 0.2
C (5–6)10.23913.455 0.916.16112.451 1.013.45012.856 0.1
D (7–8)12.64813.455 0.210.33916.166 1.512.04513.358 0.3
E (9–10)9.93811.246 0.48.2319.539 0.410.43911.249 0.2
F (11–12)7.1278.03344.440.311.64410.04122.750.57.2278.73815.100.5
G (13–14)6.3248.334 0.74.8186.326 0.68.3315.022 1.2
H (15–16)7.3285.422 0.85.8224.418 0.85.9224.821 0.5
I (17–18)5.2202.711 1.34.8183.414 0.64.5174.620 0.0
J (19–20)3.7143.414 0.12.9113.414 0.33.5133.013 0.3
K (21+)20.2777.832 3.3 †15.9608.535 2.1 †17.46513.057 1.0
Total number of ranges382411 378410 374437
p<0.001 0.01 0.13
ES0.24 0.17 0.14
* p < 0.05; † AR = |2.0|.
Table 6. Differences in point outcome between men’s and women’s badminton players according to match type.
Table 6. Differences in point outcome between men’s and women’s badminton players according to match type.
BehaviourPoint OutcomeMenWomenχ2AR
All Matchesn%n%
ServingWinner85519.175415.1 5.2 †
Forced error61713.877415.5 2.4 †
Unforced error74716.785417.144.260.5
ReceivingWinner86019.293418.7 0.6
Forced error58613.159712.0 1.7
Unforced error81018.1107721.6 4.2 †
Total number of points44754990
P<0.001 *
ES0.07
Short matches%n%nχ2AR
ServingWinner12719.912018.6 0.6
Serving
Receiving
Forced error8313.08312.9 0.1
Unforced error9214.412719.77.622.5 †
Winner12419.410616.4 1.4
ReceivingForced error8713.67912.2 0.7
Unforced error12619.713020.2 0.2
Total number of points639645
p0.178
ES0.07
Regular matches%n%nχ2AR
ServingWinner51419.046215.0 4.1 †
Serving
Receiving
Forced error38314.248215.6 1.5
Unforced error47417.553517.335.640.2
Winner50418.756318.2 0.4
Receiving Forced error35713.236011.7 1.8
Unforced error47017.468522.2 4.6 †
Total number of points27023087
p<0.001 *
ES0.08
Long matches%n%nχ2AR
ServingWinner21418.917213.7 3.5 †
Serving
Receiving
Forced error15113.320916.6 2.3 †
Unforced error18116.019215.315.740.5
Winner23220.526521.1 0.4
Receiving Forced error14212.515812.6 0.0
Unforced error21418.926220.8 1.2
Total number of points11341258
p0.008 *
ES0.08
* p < 0.05; † AR = |2.0|.
Table 7. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during long matches.
Table 7. Differences in temporal parameters and range of strokes between men’s and women’s badminton players during long matches.
BehaviourPoint OutcomeSet 1Set 2Set 3
MenWomenχ2ARMenWomenχ2ARMenWomenχ2AR
Short Matchesn%n%n%n%n%n%
ServingWinner6821.85919.2 0.85918.06118.1 0.0
Forced error4113.13812.3 0.34212.84513.4 0.2
Unforced error4614.75919.23.371.54614.16820.210.612.1
ReceivingWinner4815.45317.2 0.67623.25315.7 2.4
Forced error4113.14113.3 0.14614.13811.3 1.1
Unforced error6821.85818.8 0.95817.77221.4 1.2
Total number of points312308 327337
p0.638 0.061
ES0.07 0.13
Regular matchesn%n%χ2ARn%n%χ2ARn%n%χ2AR
ServingWinner23619.619513.5 4.2 †22418.622716.2 1.65418.44016.6 0.5
Forced error15212.624917.2 3.3 †18715.520514.6 0.64415.02811.6 1.1
Unforced error22218.524717.131.550.919616.325318.111.271.25619.03514.511.221.4
ReceivingWinner22718.926618.4 0.322418.625117.9 0.45318.04619.1 0.3
Forced error14912.416511.4 0.816613.816611.8 1.54214.32912.0 0.8
Unforced error21718.032322.4 2.7†20817.329921.3 2.6†4515.36326.1 3.1 †
Total number of points12031445 12051401 294241
p<0.001 * 0.046 * 0.049 *
ES0.11 0.07 0.15
Long matchesn%n%χ2ARn%n%χ2ARn%n%χ2AR
ServingWinner7218.86114.8 1.57018.55513.4 2.07219.35612.8 2.5
Forced error4812.66916.8 1.75514.66515.9 0.54812.87517.2 1.7
Unforced error6316.56215.110.770.56416.96716.310.810.25414.46314.49.700.0
ReceivingWinner6216.29422.9 2.4 †9124.18019.5 1.67921.19120.8 0.1
Forced error5714.95112.4 1.0338.75312.9 1.95213.95412.4 0.7
Unforced error8020.97418.0 1.06517.29022.0 1.76918.49822.4 1.4
Total number of points382411 378410 374437
p0.049 * 0.06 0.08
ES0.12 0.12 0.11
* p < 0.05; † AR = |2.0|.
Table 8. Main differences between sexes of temporal and notational variables according to match type and set.
Table 8. Main differences between sexes of temporal and notational variables according to match type and set.
VariablesAll MatchesShort MatchesRegular MatchesLong Matches
AllSet 1Set 2AllSet 1Set 2Set 3AllSet 1Set 2Set 3
Temporal parameters
Set duration ↑M
Rally time↑M ↑M ↑M
Real playing time ↑M↑M↑M↑M↑M↑M↑M↑M↑M
Rest time↑M↑M
Real rest time ↑M↑M ↑M↑M ↑M↑M↑W
Density↑M↑W ↑M ↑W
Strokes per rally↑M ↑M ↑M
Strokes per match/set↑M ↑M ↑M↑M↑M↑M↑M ↑M
Frequency between strokes↑W↑W↑W ↑M ↑W
Number of rallies ↑M ↑W
Effective playing time (%) ↑M ↑M↑M
Effective rest time (%) ↑ M↑W ↑W↑W
Range of strokes
A (1–2)↑W ↑W↑W ↑W↑W
B (2–3)↑W
H (15–16)↑M
I (17–18)↑M
K (>20)↑M↑M ↑M↑M↑M ↑M↑M
Point outcome
Serving winners↑M ↑M↑M ↑M
Serving forced errors↑W ↑W
Serving unforced errors ↑W ↑W
Receiving winners ↑M
Receiving unforced errors↑W ↑W↑W↑W↑W

Share and Cite

MDPI and ACS Style

Gomez, M.-Á.; Rivas, F.; Connor, J.D.; Leicht, A.S. Performance Differences of Temporal Parameters and Point Outcome Between Elite Men’s and Women’s Badminton Players According to Match-Related Contexts. Int. J. Environ. Res. Public Health 2019, 16, 4057. https://doi.org/10.3390/ijerph16214057

AMA Style

Gomez M-Á, Rivas F, Connor JD, Leicht AS. Performance Differences of Temporal Parameters and Point Outcome Between Elite Men’s and Women’s Badminton Players According to Match-Related Contexts. International Journal of Environmental Research and Public Health. 2019; 16(21):4057. https://doi.org/10.3390/ijerph16214057

Chicago/Turabian Style

Gomez, Miguel-Ángel, Fernando Rivas, Jonathan D. Connor, and Anthony S. Leicht. 2019. "Performance Differences of Temporal Parameters and Point Outcome Between Elite Men’s and Women’s Badminton Players According to Match-Related Contexts" International Journal of Environmental Research and Public Health 16, no. 21: 4057. https://doi.org/10.3390/ijerph16214057

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop