Player Walkovers in Professional Men’s Tennis Tournaments from 1973 to 2019

doi:10.21203/rs.3.rs-4848389/v1

Download PDF

Research Article

Player Walkovers in Professional Men’s Tennis Tournaments from 1973 to 2019

https://doi.org/10.21203/rs.3.rs-4848389/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Purpose

In tennis, there exist different types of situations in which players are unable to finish a match or a tournament. Walkovers (W/O) refer to when a player wins a match due to the absence of his/her opponent. This investigation aimed to describe W/O in Association of Tennis Professional (ATP) tournaments between 1973 and 2019, analysing epidemiological patterns and associated factors.

Methods

A retrospective cohort study was conducted, analysing 168137 matches. Factors that might influence W/O were studied by epidemiological measures, including both absolute and relative measures of risk incidence proportion (IP) per 1000 played matches and cumulative incidence ratio (CIR) are provided as association measures.

Results

The IP was 4.2 (95%CI: 3.9–4.5). Master tournaments showed the higher IP (5.5; 95%CI: 4.6–6.6). Carpet courts were the ones with a higher IP (6.3; 95%CI: 5.2–7.6). The matches with 3 sets had a 2.5% greater risk comparing with those with 5. The primary causes of W/O were attributed to injuries (28.7%), illnesses (7.8%), and personal reasons (2.5%), although the majority of reasons remained unknown (61.0%).

Conclusion

This study provides a comprehensive understanding of W/O in professional tennis, highlighting epidemiological patterns. These findings have practical implications for athletes, coaches, and organizers, guiding preventive strategies and future research.

tennis

walkover

health

epidemiology

ATP

Tennis is one of the most popular sports in the world in which the match duration is not defined by the game-rules as it has no time limit [1]. Male professional tennis matches involve high-intensity intermittent efforts, including forceful strokes, fast accelerations and decelerations and changes of directions played across different indoor and outdoor surfaces [2, 3]. Thus, matches can last for several hours, causing on the players a high level of physical and mental exhaustion that can end with injuries and/or retirement from the match [4]. Moreover, professional tennis players face a continuous increase in competition density, resulting in increased physical, mental, technical and tactical demands and consequently injury rates [5]. In a professional tennis competition, it can be found different situations that can limit the player’s participation (Table S1 in the Supplementary Material). Those situations may be stated by the player him/herself or an official and they may have consequences for the athlete.

In tennis, a Walkover (W/O) occurs when a player automatically advances to the next round without playing the match [6]. The match shall be deemed to begin after the first service of the first set, so the W/O must be determined before that point [7]. There can also exist W/O caused by administrative errors or personal circumstances [6]. It should be stated that a player referring an illness or injury must sustain a mandatory medical examination by an Association of Tennis Professionals (ATP) doctor. The non-compliance of this rule may lead to economical fine that may vary according to the competition [8]. It is worth to clarify that W/O are not the same as Retirements (Table S1 in the Supplementary Material), where their main difference relies at the moment when the decision is made. While the W/O is determined before the beginning of a match, the retirement will be determined during its course, despite injuries or illnesses may be the same in both cases [6–8].

Famous W/O had happened throughout tennis history, such as the case when Nick Kyrgios, at 2022 Wimbledon, reached his first Grand Slam final because of Rafael Nadal’s injury [9] or in Rolland Garros (2020), when Tsvetana Pironkova reached the third round due to Serena Williams absence [10]. Concerning tennis competitions, there are logistic consequences that must be solved, regarding court availability, schedule changes, media coverage and ticket refunding. In fact, at the 2014 Miami Masters (by then called ´Sony Open´) some unusual episode occurred, where both semifinals could not be played due to W/O. Kei Nishikori did not present on-court to play against Novak Djokovic due to an injury on his groin. Likewise, Thomas Berdych could not present himself against Rafael Nadal. The tournament’s organization allowed the public who got a ticket for the affected semifinals, to get a free ticket for the 2015 semi-finals [9].

In scientific literature, we can find several observational studies stating an increase of non-completed games among professional tennis players in the last years [11–13], the non-completed games were mainly because of injuries having different repercussions. Nevertheless, in the best of our knowledge, there are no studies who describes and analyses the causes of W/O in ATP matches. Therefore, the objective of this investigation is to describe the ATP W/O between 1973 and 2019, determining the epidemiology and observing the possible related factors.

Study design and sample

An observational, retrospective cohort epidemiological study was performed. All ATP tour matches between 1973 and 2019 were studied (n = 168137 matches). The ATP tournaments included are shown in Table S2 in the Supplementary Material. A data base created from the website GitHub (https://github.com/JeffSackmann/tennis_atp) which gathers the information from the official sites of the ATP tournaments.

Variables

The main variable is “W/O” (Yes/No), when a match is not completed because of a player leaving the competition before the beginning of the match. The variables related with the match are shown in Table S3 in the Supplemental material. In addition, the difference in age and ranking between players in each match was also evaluated at the player level.

Statistical analysis

In the descriptive analysis, absolute (n) and relative (%) frequencies were computed for categorical variables, while measures of central tendency and dispersion were calculated for the continuous ones. A bivariate analysis was performed to describe the characteristics of the match and the players when a default occurred. In the specific case of W/O, which occur before matches, observations do not have the sum of game data available for matches. Therefore, we cannot always ensure the calculation of incidence as a rate with respect to the games played. Instead, it would be more feasible to calculate the cumulative incidence or incidence proportion (IP) for the defaults according to the formula i = e/n, where e is the number of W/O (events) during the study period and n is the respective total number of exposed matches (expressed in units of 1000 matches played). The number of W/O, the exposure as number of matches, the IP and its 95% confidence interval (95%CI) were provided for each category of the relevant variables. The incidence and 95% confidence intervals were estimated using a Poisson distribution.

In addition, following the recommendations of STROBE statement for observational studies [14] and the CONSORT statement for randomized controlled trials [15], relative and absolute measures of association between covariates and the presence of W/O were given. They were expressed as cumulative incidence ratio (CIR), and risk differences (RD) with their respective 95% CI. CIR was estimated as the ratio of incidence proportion between the two specified studied groups (i.e., carpet and clay surfaces). Furthermore, with the aim to identify how many more W/O were sustained in one group as compared with another one, the absolute measure of RD was calculated by subtracting rates from 2 exposures group.

All analyses were performed using version 4.1.3 of the R statistical software. The R package compareGroups [16] was used to describe characteristics according to the presence of default. The epi.2by2 function of the R package epiR [17], setting method as cohort time, was used to calculate the incidence rates. The CIR were calculated using the function pois.exact from the epitools package. Most of the graphics were obtained using ggplot2 package [18]. The reproducible code used in this study is available on a publicly accessible GitHub repository (https://github.com/marticasals/WO_ATP), allowing for the transparency and replicability of the statistical analysis.

Exploratory analysis of ATP matches during the period 1973–2019

A total number of 168137 ATP matches were analysed. A 97.36% (n = 163701) of the matches were completed (Table 1). The median of games per match were 22 (Q1:18-Q3:29). The majority of the players were right-handed, both those who classified for the next round and the one that did not. The median of age difference was 3.55 years (Q1:1.66-Q3:6.09) and the rank difference was 51 ranking posts (Q1:23-Q3:104).

Insert Table 1 near here

Descriptive characteristics of W/O

Seven-hundred and eight (0.42%) W/O were recorded from 1973 and 2019. The proportion of W/O was higher in the Masters 1000 matches (0.55%), followed by 250 or 500 tournaments (0.45%) (Table 2). The IP was 0.0042 (95%CI: 0.0039–0.0045) W/O per scheduled match. For 1000 scheduled matches, 4.2 would not be played due to a W/O.

The Fig. 1 shows the temporal evolution of W/O in ATP tournaments, showing a maximum IP in 1973, decreasing on the following years and increasing again from 1990 to 2019.

Insert Table 2 near here

Insert Fig. 1 near here

Main causes of the W/O were related to injuries (203; 28.67%), to illnesses (55; 7.77%) and to personal reasons (18; 2.50%). In the remaining 432 cases (61.01%), the reasons were unknown. Regarding these injuries, the most body areas affected were the lower limbs (47.78%), trunk (31.03%) and upper limbs (19.70%) (Fig. 2).

Insert Fig. 2 near here

Epidemiology measures of W/O

The Masters tournaments showed the higher IP (5.53; 95%CI: 4.62–6.57). Considering playing surfaces, carpet courts were the ones with a higher IP of W/O (6.29; 95%CI: 5.17–7.57) (Table 3). The best-of-3-sets matches had a 2.50‰ greater risk of W/O comparing with those with 5 sets. The matches of the final rounds had a 4.28‰ greater risk comparing with qualifying round matches (Table 3).

Insert Table 3 near here

The objective of this study was to describe the W/O of all ATP tournaments between 1973 and 2019. Despite previous epidemiological studies about non-completed ATP matches due to medical reasons have also included W/O in their analysis, this is the first study that analyse specifically the W/O and the factors that may cause or influence them.

The W/O IP was 4.2 per 1000 matches. Although there are no previous studies addressing this specific aspect, it is noteworthy to consider that the relatively low incidence of W/O in professional competitions might be influenced by various factors. Unlike in amateur or lower-level competitions, where a player's W/O may have minimal consequences, W/O in professional tennis tournaments can significantly impact a player's performance, both economically and in terms of ranking points. These potential consequences could contribute to players making greater efforts to compete despite injuries or other challenges, thereby reducing the incidence of W/O observed in our study. Future research could explore these aspects further to provide a more comprehensive understanding of the dynamics surrounding W/O in professional tennis.

Previous studies analysed together W/O and retirements, under the term “medical retirement”. For example, Neri-Fuchs et al. [19] reported an IP of 3.800 (95%CI: 3.799–3.801) per 100 exposures in ATP and WTA matches and Jayanthi et al. [20] reported an incidence rate of 15.6 per 1000 matches in the youth tournaments in the United States Tennis Association (USTA). Concerning retirements, Breznik et al. [11] reported a frequency of 2.57% of retirements in ATP tournaments and Hartwell et al. [21] an incidence rate of 2.59 per 1000 matches (95%CI: 1.68–3.5) in the 2013 USTA Pro Circuit. As important note to clarify, retirements and W/O are two different situations on a tennis match, and despite usually being caused by similar reasons (i.e., injury or illness), they have different consequences. In the present study, retirements happened in 2.12% of the total matches, while W/O happened in 0.42%. Those differences can be explained by the consequences related to each category; in W/O, the player that retires before the beginning of the match gets the economical and the ranking compensations related to the development of the tournament so far, before the scheduled game. By the other hand, after a retirement, the player not only gets the economical and ranking classification until the moment of the game, but also gets the economical and ranking classification of that match [8]. As a practical example, if the Greek player Stefano Tsitsipas had retired before the 2023 ATP Finals match against Holger Rune, he would have received 162.750 dollars. Instead, by the only fact of just presenting himself on court and playing the first game gave him the right of an economic compensation of 244.125 dollars (a difference of 81.375 dollars) [22]. Furthermore, it is notable that W/O are relatively rare in the first round of tournaments, as players who fail to appear for their initial match are typically replaced by lucky losers (LL) – players who lost in the final round of the qualifying stage and are available to compete on the day of the first round of the main draw. Consequently, the points and prize money allocated to players in the first round are instead awarded to those in the second round, while players who W/O in the first round are replaced by other competitors and do not receive any points or prize money. Injuries related with W/O were mainly reported in the lower limbs (47.7%), followed by trunk (31.03%) and upper limbs (19.7%). These findings are consistent with previous investigations in tennis players, were the most injured areas were the lower limbs (IP: 1.59; 95%CI: 0.87–2.30), upper limbs (IP: 0.84; 95%CI: 0.32–1.35) and trunk (IP: 0.75; 95%CI: 0.26–1.24) [21].

In the present study, the risk of a W/O was higher in 3-set matches comparing with 5-set matches. If we consider that best-of-5-set matches are played at Grand Slams tournaments in which a higher amount of economical rewards and ranking points are earned, could explain the willingness of the players to participate in these kinds of matches, despite not being in optimal physical conditions. Regarding playing surfaces, carpet courts had a greater proportion of W/O, with an IP of 6.29 (95%CI: 5.17–7.57) per 1000 matches, followed by hard courts 4.48 (95%CI: 4.00-4.99). Additionally, investigations focused on retirements have highlighted that injuries are more prevalent on slower surfaces such as clay courts. This observation may be attributed to the longer effective playing time on slow surfaces (14.5% vs. 12.9%) and the extended duration of points (5.6 vs. 7.1 s), with clay courts typically exhibiting longer rally times compared to hard courts [23]. Despite these associations (between injury rates and surface types) it is important to note that W/O are determined before the match begins, thus potentially limiting the influence of surface type on physical demands during the game. Some studies have explored the relationship between injury occurrence and playing surfaces in tennis. For instance, research indicates that male tennis players have a significantly higher risk of injury compared to their female counterparts, with a reported fourfold increase in injury likelihood (95% CI: 1.57–18.65) [21].

Another factor related with W/O is the tournament round, the final rounds got a 2.32 (95%CI: 1.75–3.07) chance of having a W/O, comparing with classification matches. That fact could be related with the match congestion, as reported with Jayanthi et al. [20], stating that the medical related retirements had a incidence rate of 6.3 per 1000 match exposures on the first four matches of a tournament and 16.7 after the fourth match.

Finally, reported W/O are increasing over last years, concurring with other studies like Néri et al [19], were the retirements increased after 2000 or Okhlom et al. [13], who reported an increase of injury proportion among tennis player from 50–65% between 2003 and 2012. Tennis has evolved during the years from a technical-tactical game to a completely tough sport with high-intensity periods of performance in which players must be prepared to withstand constant force exertions. Hence, any possible factor that could impact negatively on the player’s physical capacities or not feeling at optimal conditions, he/she might take the decision to not present to play. Such is the case of Naomi Osaka who did not present in the round of 64 at Roland Garros (2021) due to mental health problems [24]. Also, in 2009 an international consensus to define and register injuries and diseases in tennis athletes was published, being another possible reason for the change of tendency in retirements and W/O due to medical reasons [25, 26].

Limitations

The present study is the first to analyse W/O in professional tennis. Therefore, the results cannot be directly compared with existing literature. During the years of analysis, there have been changes in ATP rules, potentially influencing the frequency and nature of W/O. Regarding the registration of W/O in ATP tournaments, there are a lack of data before 2001, causing potential difficulties on the global analysis.

This is the first investigation ever carried out describing Walkovers situations in professional tennis from the years 1973 to 2019 and analysing epidemiological patterns and associated factors. Non-completed matches are increasing in last years. Despite having similar causes, W/O must be studied separately from Retirements mainly because of economical and athletic consequences that may cause players to take different options depending on the case. An extensive analysis over 40 year of ATP games showed that the body location of injuries that caused W/O were similar to retirements. Determinants such as the number of sets matches (best-of-3-sets) or the court surfaces (carpet) and tournaments level (Masters) showed a low influence over the W/O incidence. The congestion of matches (round at play) may be a cause of physical impairment in tennis players, causing W/O. Further studies about the decision making in tennis players taking a W/O must be performed. The information about W/O may be interesting for players, coaches and tournament organizers, in order to avoid the potential causes and minimize the medical, economical and logistical effects of retirements before matches.

Ethics statement

No ethical approval was needed for carrying out this research as all the information used and reported for analysis is freely available online.

Competing interests and funding

The authors report no competing interests to declare.

This research was funded by the Ministerio de Ciencia e Innovación (Spain) [PID2019- 352 104830RB-I00] and the Departament de Recerca i Universitats de la Generalitat de Catalunya (Spain) [2021 SGR 01421] (GRBIO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author´s contribution

All authors contributed equally to the manuscript and read and approved the final version of the manuscript.

Christmass MA, Richmond SE, Cable NT, et al. Exercise intensity and metabolic response in singles tennis. J Sports Sci 1998; 16: 739–747.
Fernandez-Fernandez J, Sanz-Rivas D, Mendez-Villanueva A. A Review of the Activity Profile and Physiological Demands of Tennis Match Play. Strength Cond J 2009; 31: 15.
Pluim BM, Jansen MGT, Williamson S, et al. Physical Demands of Tennis Across the Different Court Surfaces, Performance Levels and Sexes: A Systematic Review with Meta-analysis. Sports Med 2023; 53: 807–836.
Dines JS, Bedi A, Williams PN, et al. Tennis Injuries: Epidemiology, Pathophysiology, and Treatment. JAAOS - J Am Acad Orthop Surg 2015; 23: 181.
Fu MC, Ellenbecker TS, Renstrom PA, et al. Epidemiology of injuries in tennis players. Curr Rev Musculoskelet Med 2018; 11: 1–5.
Gerdes S. FRIEND AT COURT. THE HANDBOOK of TENNIS RULES and REGULATIONS. United States Tennis Association, https://www.usta.com/content/dam/usta/coach-organize/content-fragments/resource-library/assets/pdfs/2023-Friend-at-Court.pdf (2023).
Lawn Tennis Association. LTA COMPETITION REGULATIONS. 2021.
ATP Official Rulebook | ATP Tour | Tennis. ATP Tour, https://www.atptour.com/en/corporate/rulebook (accessed 15 October 2023).
Mercadal J. ¿Qué es un walkover en tenis? Relevo, 2023, https://www.relevo.com/tenis/walkover-tenis-20230328135339-nt.html (2023, accessed 25 October 2023).
PERÚ EP de SESAE. Serena Williams se retira de Roland Garros por una lesión, https://andina.pe/agencia/noticia-serena-williams-se-retira-roland-garros-una-lesion-815846.aspx (2020, accessed 19 November 2023).
Breznik K, Batagelj V. Retired Matches Among Male Professional Tennis Players. J Sports Sci Med 2012; 11: 270–278.
Maquirriain J, Baglione R. Epidemiology of tennis injuries: An eight-year review of Davis Cup retirements. Eur J Sport Sci 2016; 16: 266–270.
Okholm Kryger K, Dor F, Guillaume M, et al. Medical reasons behind player departures from male and female professional tennis competitions. Am J Sports Med 2015; 43: 34–40.
Vandenbroucke JP, von Elm E, Altman DG, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration. Int J Surg 2014; 12: 1500–1524.
Moher D, Hopewell S, Schulz KF, et al. CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials. BMJ 2010; 340: c869.
Subirana I, Sanz H, Vila J. Building Bivariate Tables: The compareGroups Package for R. J Stat Softw 2014; 57: 1–16.
Stevenson M, Sergeant E, Heuer C, et al. epiR: Tools for the Analysis of Epidemiological Data, https://cran.r-project.org/web/packages/epiR/index.html (2024, accessed 7 April 2024).
Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer. Epub ahead of print 2009. DOI: 10.1007/978-0-387-98141-3.
Néri-Fuchs J-B, Sedeaud A, Marc A, et al. Medical withdrawals in elite tennis in reference to playing standards, court surfaces and genders. J Sci Med Sport 2023; 26: 296–300.
Jayanthi NA, O’Boyle J, Durazo-Arvizu RA. Risk Factors for Medical Withdrawals in United States Tennis Association Junior National Tennis Tournaments: A Descriptive Epidemiologic Study. Sports Health 2009; 1: 231–235.
Hartwell MJ, Fong SM, Colvin AC. Withdrawals and Retirements in Professional Tennis Players: An Analysis of 2013 United States Tennis Association Pro Circuit Tournaments. Sports Health 2017; 9: 154–161.
Un paseo a cambio de 81.375 dólares: la retirada entre pitos de Tsitsipas destapa un problema para la ATP. Relevo, https://www.relevo.com/tenis/atp-finals/6000-euros-minuto-detras-retirada-20231114151721-nt.html (2023, accessed 9 January 2024).
Skorodumova А, Baranov I. The differences in energy system demands of competitive male tennis play between fast and slow courts. ITF Coach Sport Sci Rev 2019; 27: 11–14.
La tenista Naomi Osaka se retira de Roland Garros en medio de la controversia con los medios sobre su salud mental. BBC News Mundo, https://www.bbc.com/mundo/noticias-57310957 (accessed 14 January 2024).
Pluim BM. The evolution and impact of science in tennis: eight advances for performance and health. Br J Sports Med 2014; 48 Suppl 1: i3-5.
Pluim BM, Fuller CW, Batt ME, et al. Consensus statement on epidemiological studies of medical conditions in tennis, April 2009. Clin J Sport Med Off J Can Acad Sport Med 2009; 19: 445–450.

Table 1. Frequency of W/O of each match according to, tournament level, surface, sets, round and match outcome.

Variable	Frequency	Percentage
Tournament level
Grand Slams	28294	16.83%
Masters	23313	13.87%
250 or 500	116088	69.04%
Tour Finals	442	0.26%
Surface
Clay	59396	35.33%
Grass	19127	11.38%
Hard	72123	42.9%
Carpet	17491	10.4%
Sets
5	24572	14.61%
3	143565	85.39%
Round
Qualifying	19993	11.89%
Preliminary	123058	73.19%
Final	25086	14.92%
Match outcome
Completed	163701	97.36%
Default	158	0.09%
Retirement	3560	2.12%
Unknown	10	0.01%
W/O	708	0.42%

Table 2. Characteristics of matches and professional players in W/O.

Variable	W/O
	Yes N=708	No N=167429
Tournament level
Grand Slams	60 (0.21%)	28234 (99.8%)
Masters	129 (0.55%)	23184 (99.4%)
250 or 500	518 (0.45%)	115570 (99.6%)
Tour Finals	1 (0.23%)	441 (99.8%)
Surface
Clay	200 (0.34%)	59196 (99.7%)
Grass	75 (0.39%)	19052 (99.6%)
Hard	323 (0.45%)	71800 (99.6%)
Carpet	110 (0.63%)	17381 (99.4%)
Sets
5	51 (0.21%)	24521 (99.8%)
3	657 (0.46%)	142908 (99.5%)
Round
Qualifying	65 (0.33%)	19928 (99.7%)
Preliminary	454 (0.37%)	122604 (99.6%)
Final	189 (0.75%)	24897 (99.2%)


Age difference	3.86(Q1:1.85-Q3:6.11)	3.55 (Q1:1.66-Q3:6.09)
Ranking difference	38 (Q1:17-Q3:73)	51 (Q1:23-Q3:104)

Table 3. Incidence proportion (IP); cumulative incidence rate (CIR), risk difference (RD) and confidence interval (95%CI) of professional matches W/O, regarding tournament level, surface, number of sets, and round.

Variable	WalkOver	Matches	IP (95%CI)	CIR (95%CI)	RD (95%CI)
Tournament level
Grand Slam	60	28294	2.12 (1.62- 2.73)	1	0
Master	129	23313	5.53 (4.62- 6.57)	2.61 (1.92- 3.54)	3.41 (2.32- 4.51)
250 o 500	518	116088	4.46 (4.09- 4.86)	2.10 (1.61- 2.75)	2.34 (1.68- 3.00)
Tour Finals	1	442	2.26 (0.06- 12.54)	1.07 (0.15- 7.68)	0.14 (-4.32- 4.60)
Surface
Clay	200	59396	3.37 (2.92- 3.87)	1	0
Grass	75	19127	3.92 (3.09- 4.91)	1.16 (0.89- 1.52)	0.55 (-0.45- 1.55)
Hard	323	72123	4.48 (4.00- 4.99)	1.33 (1.12- 1.59)	1.11 (0.44- 1.79)
Carpet	110	17491	6.29 (5.17- 7.57)	1.87 (1.48- 2.36)	2.92 (1.66- 4.18)
Sets
5	51	24572	2.08 (1.55- 2.73)	1	0
3	657	143565	4.58 (4.23- 4.94)	2.20 (1.66- 2.93)	2.50 (1.83- 3.17)
Round
Qualifying	65	19993	3.25 (2.51- 4.14)	1	0
Preliminary	454	123058	3.69 (3.36- 4.04)	1.13 (0.88- 1.47)	0.44 (-0.42- 1.30)
Final	189	25086	7.53 (6.50- 8.68)	2.32 (1.75- 3.07)	4.28 (2.95- 5.61)

No competing interests reported.

PlayerWalkoversupplementalmaterialtosubmit080424.docx

Download PDF

Editor assigned by journal
02 Aug, 2024
Submission checks completed at journal
02 Aug, 2024
First submitted to journal
02 Aug, 2024

You are reading this latest preprint version

Player Walkovers in Professional Men’s Tennis Tournaments from 1973 to 2019

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Methods

Study design and sample

Variables

Statistical analysis

Results

Exploratory analysis of ATP matches during the period 1973–2019

Insert Table 1 near here

Descriptive characteristics of W/O

Insert Table 2 near here

Insert Fig. 1 near here

Insert Fig. 2 near here

Epidemiology measures of W/O

Insert Table 3 near here

Discussion

Limitations

Conclusions

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

Player Walkovers in Professional Men’s Tennis Tournaments from 1973 to 2019

Status:

Version 1

Abstract

Purpose

Methods

Results

Conclusion

Figures

Introduction

Methods

Study design and sample

Variables

Statistical analysis

Results

Exploratory analysis of ATP matches during the period 1973–2019

****Insert Table 1 near here****

Descriptive characteristics of W/O

****Insert Table 2 near here****

****Insert Fig. 1 near here****

****Insert Fig. 2 near here****

Epidemiology measures of W/O

****Insert Table 3 near here****

Discussion

Limitations

Conclusions

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

Insert Table 1 near here

Insert Table 2 near here

Insert Fig. 1 near here

Insert Fig. 2 near here

Insert Table 3 near here