INTRODUCTION

The game opening is a crucial feature of tennis (Born, 1996). Not only does every point start with a serve and in most cases with a return, these two strokes also have a strong impact on the outcome of a match (Gillet et al., 2009; Ma et al., 2013). Previous research has shown that the mean rally length in tennis is between three to six strokes, depending on the surface (Born, 2017; Carboch et al., 2018; Fernandez-Fernandez et al., 2008; Weber et al., 2010; Weber & Born, 2012), the 3^rd and 4^th stroke of a rally can be added to the so-called extended game opening that consists of the first four strokes of a rally (Born, 2017; Weber & Born, 2012). Also, 50-70% of all points played in professional tennis, no matter if it is men´s or women´s tennis and which surface is played, are finished after an extended game opening (Born, 2017; Carboch et al., 2018; Weber et al., 2010; Weber & Born, 2012). While the serve is probably the most examined stroke or match situation in tennis, respectively (Elliot et al., 2013; Gillet et al., 2009; Grambow et al., 2020; Grambow et al., 2021; Klaasen & Magnus, 2014; Mecheri et al., 2016; Meffert et al., 2018; O’Donoghue & Brown, 2008; Vaverka et al., 2018; Weber & Born, 2012), there is far less research on the return and almost none on the 3^rd and 4^th stroke although experts claim that the importance of these strokes for a successful tennis player is undeniable (Born, 1996; Born, 2017; Brabenec, 2000; Crespo & Miley, 1998; Giffenig, 2013; Gillet et al., 2009; Klaus et al., 2017; Meffert et al., 2018; Schönborn, 2006 & 2012; Weber et al., 2010; Weber & Born, 2012).

According to the tactical principals of tennis, one of the factors for a successful stroke execution is the placement of the stroke (Crespo & Miley, 1998; Ferrauti et al., 2014) which can be used to (1) move the opponent sideways out of the court, (2) push the opponent back away from the baseline or (3) put the opponent under time pressure (Ferrauti et al., 2014; Tiley, 2002; Schönborn, 2012). The placement into certain zones of the court is useful to execute these goals, whereas a misplaced stroke (e.g., central and short) can lead to an offensive situation for the opponent and put the player itself under pressure. For a systematic analysis of the stroke placement several court divisions have been established until today (Born, 2017; Giffenig, 2013; Gillet et al., 2009; Molina, 1995; Nowak & Panfil, 2012; Schönborn, 2008 & 2012; Tiley, 2002).

While most research on the return focuses primarily on performance indicators other than placement like winning percentages or winning outcome (Cui et al., 2018; Hizan et al., 2011; Ma et al., 2013; Merghes et al., 2014), contact point or ball trajectories (Reid et al., 2016) or efficiency (Filipcic et al., 2015), only a few references can be found for the placement of the return; additionally, all of them refer to men’s tennis: Gillet et al. (2009) state that 75.5% of all returns in men’s tennis are aimed to the central zone of the court and that aiming there leads to a higher winning percentage than aiming to outer zones. According to de Witt (2019) 67% to 92% of the returns on the ATP Tour are played through the middle of the court depending on the serve direction. Nowak and Panfil (2012) present similar findings while Hedelund and Rasmussen (1997) provide coaching tips by advising to aim the return to the middle and/or crosscourt.

Previous research from men’s professional tennis for the 3^rd and 4^th stroke shows that approximately 80% are placed longer than the service line and 30% into the zones close to the baseline. The so-called forbidden zone (FZ) which is located in the center of the court and is related to strokes that are easy to return for the opponent is played into 30% of the time, making it 70% of all 3^rd and 4^th strokes placed outside the FZ. 60-70% of all 3^rd and 4^th strokes are placed into the zones close to the sidelines. Most of these strokes – approximately 30% of all strokes – are placed into the zones close to the sidelines directly behind the service line, referred to as C-Zones by Born (2017; Schönborn, 2008). The difference between the two strokes can be described as the 3rd stroke being more precise than the 4^th, meaning being placed more frequent into the latter described zones, the zones on the sideline, the zones close to the baseline as well as outside the FZ. Other research on the 3^rd stroke focused on the position of the player and the error- and winner-rate (Klaus et al., 2017). Brabenec (2000) states that players should try to dominate the point with a fast and well-placed 3^rd stroke but does not state any specific placement or target zones. state that strokes to win points are directed to the outer zones of the court.

In contrast, there is a clear research gap regarding the mentioned strokes in women’s tennis. Thus, to the best of the authors’ knowledge, the present study is the first which examines the placement of the three strokes after the serve in women’s professional tennis. In particular, this study tries to answer the following questions:

(1) Into which zones and zone groups of the court do professional women’s tennis players place their (a) return (b) 3^rd stroke and (c) 4^th stroke?

(2) Can differences be observed between the placement of the three strokes?

(3) Can possible differences in the stroke placement be related to the level of play?

The main goal of the present study is to generate a first overview of the stroke placement in women’s professional tennis. This could offer useful numbers for coaches and players to derive practical recommendations as well as being a starting point for following research.

MATERIALS AND METHODS

Participants: The research material consists of data from 19 professional women’s tennis matches in total: 7 at the WTA Premier Mandatory¹ Tournament Mutua Madrid Open 2019, 5 at the WTA Premier 5² Tournament Internazionali BNL d’Italia 2019 as well as 7 matches from $15,000 and $25,000 ITF³ Tournaments from 2018, 2019 and 2020. The 14 players examined at the WTA tournaments had a mean ranking at the end of the year 2019 of position 15.2 ± 14.4 with a mean age of 25.8 ± 3.1 years. The 14 players examined at the ITF tournaments had a mean ranking at the time of the tournaments of position 586.6 ± 291.3 with a mean age of 21.3 ± 5.1 years. These matches were chosen to get an overview of professional women’s tennis and to show possible similarities and differences between different playing levels. Inferring from these numbers hereinafter the WTA players are referred to as the better players within the sample. In total this study contains examination of 2562 returns (1647 of the WTA players, 915 of the ITF players), 2065 3^rd strokes (1317 WTA, 748 ITF) and 1606 4th strokes (1021 WTA, 585 ITF).

Design & Procedures: Matches examined in this study were recorded digitally and watched on a laptop using the VLC Media Player. Matches were allocated among three well trained observers on pre-defined criteria (specific zones, see figure 1) according to standard procedures as follows: Every return, 3^rd and 4^th strokes were observed regarding the outcome (i.e., in, out or net) and the placement (e.g., into zone 1c). Microsoft Excel was used to collect the observed data.

For the observation of the placement a modified court division method using 12 different zones based on Born (2017) was used (figure 1). This court division has the purpose of dividing the court as close-meshed as possible to guarantee a differentiated analysis of the stroke placement and, at the same time, keep the court division simple enough to make it applicable for coaches and players (Born, 2017). For the purpose of this study the original division into 14 zones was modified by setting aside the zones 5a and 5b, located directly at the net, because data shows that less than 2% of all strokes are placed into these zones (Born, 2017). Instead, the zones 3a, 3b, 4a and 4b, originally located between service line and the zones 5a and 5b, were enlarged up to the net. All in all, the area between the service line and the net is divided lengthways into 4 equally sized zones (3a, 3b, 4a, 4b) while the area between the service line and the baseline is divided lengthways the same way and additionally across in two parts which results in 8 equally sized zones (1a-d, 2a-d). Also based on Born (2017) certain zones are combined into zone groups to get a better overview: Zones 1c and 2c form the zone group C-Zones; zones 1a, 1b, 2a, 2b form Baseline; zones 1a-d, 2a-d form Longer than serviceline; zones 1d, 2d, 3b, 4b form Forbidden Zone (FZ); zones 1a-c, 2a-c, 3a, 4a form Outside FZ; zones 1b, 1d, 2b, 2d, 3b, 4b form Middle Zones and zones 1a, 1c, 2a, 2c, 3a, 4a form Outer Zones. The collected data was edited in Microsoft Excel for Mac. Since only video footage of professional players, resulting in publicly open-access data, was used, no approval of the ethics committee was necessary.

Analysis: The collected data were first sorted in Microsoft Excel for Mac to get an overview. The statistical analyses were carried out using IBM SPSS Statistics 27 (SPSS Inc., Chicago, Illinois, USA). First the Chi square test was computed to test for equal distribution. Second the Chi square test of independence was used to test for a relationship between stroke (i.e., return, 3^rd, 4^th) and placement frequency (i.e., different zones).

Correlations between the three strokes as well as between the level of play (i.e., WTA, ITF) were computed using Spearman`s rank correlation. The level of significance was set to p < .05 and if applicable to p < .01 and p < .001.

RESULTS

Main findings show that female pro tennis players hit their returns most frequently into the zones 2d (18.9%), 1d (14.0%), 2b (11.6%) and 1b (10.3%), 66.7% into the middle zones, 82.4% longer than the service line and 33.6% into the zones at the baseline. Further, their 3rd strokes were hit into the zones 2c (16.7%), 2d (12.2%), 1c and 2a (both 12.0%) most frequently, 28.7% into the C-Zones, 84.8% longer than the service line and 35.8% into the zones at the baseline and 72.6% outside the FZ. Their 4^th strokes were targeted most frequently into 2c (15.0%), 2d (12.6%), 2a (11.4%), 1d (9.9%) and 1c (9.7%), 24.7% go into the C-Zones, 83.4% longer than the service line, 36.3% into the zones at the baseline as well as 68.5% outside the FZ.

Details on descriptive findings for the return are presented in table 1, for the 3^rd stroke in table 2 and for the 4^th stroke in table 3.

Chi square test revealed an unequal distribution between the number of strokes to the different zones (p < .001) which means that the ball placement was different in every zone of the court (see table 1). Chi square test of independence showed significant relationships between the respective stroke (return, 3^rd, 4^th) and the placement frequency into the different zones (x² (df) = 22, p < .001, Cramer-V .162).

Table 1. Return WTA & ITF Players.

Table 2. 3rd Stroke WTA & ITF Players.

Table 3. 4th Stroke WTA & ITF Players.

The results of the Spearman`s rank correlations are displayed in figure 2. They showed significant correlations between the placement of the 3^rd and 4^th stroke (p < .001) as well as between the return and the 4^th stroke (p < .05). There was no significant correlation between the return and the 3^rd stroke. Also, significant correlations were shown between the WTA and ITF players regarding all three strokes (return p < .01; 3^rd stroke p < .001; 4^th stroke p < .01).

DISCUSSION

This study aimed to examine the placement of the return, 3^rd and 4^th stroke in professional women’s tennis in general and also possible differences related to the level of play.

The difference between strokes (i.e., return, 3^rd, 4^th) revealed different placement frequencies into the respective 12 zones of the court. However, significant correlations between the return and 4th stroke as well as between the 3^rd and 4^th stroke indicate a similar distribution of these strokes into the respective 12 zone. However, the return and the 3^rd stroke data were not inspected since there was no significant correlation between these two strokes. Also, the significant correlation between WTA and ITF players regarding all three strokes indicate that the two groups place the respective strokes with the same distribution into the 12 zones.

Return: The four most frequently targeted zones of the return (2d, 1d, 2b, 1b) are all located behind the service line in the middle part of the court and accumulate 54.9% of all returns and even 66.7% when adding the shorter middle zones 3b and 4b. Also, the returns tend to go more to the backhand side – of a right-handed opponent – with zone 2d being the most frequented zone and all zones on this side of the court being more frequented than their counterparts on the forehand side of a right-handed player. This is in line with previous research findings regarding the return, which suggest players to aim more often to the backhand side to avoid the presumably better forehand of the opponent (de Witt, 2019; Gillet et al., 2009; Hedelund & Rasmussen, 1997; Nowak & Panfil, 2012).

Alongside a correlation between WTA and ITF players regarding their return placement, some differences seem noteworthy: WTA players place their returns longer and more frequent to the middle zones compared to ITF players; however, this striking feature failed statistical significance. Still, the middle zones and especially those closer to the baseline are recommendable targets for the return derived from this data.

3^rd Stroke: The placement of the 3rd stroke is mostly in line with the data from men’s professional tennis (Born, 2017; Nowak & Panfil, 2012; Schönborn, 2008) but also shows some differences. ATP players surpass the women regarding the C-Zones, the Outside FZ and Outer Zones while women are playing close to the baseline more often. Based on this, ATP players seem to play more angles and move the opponent more to the sides of the court while women tend to play the 3rd stroke deeper but less often to the sidelines. A possible explanation could be the overall more aggressive and offensive return of female players in comparison to male players which makes it more challenging to play an offensive 3^rd stroke.

However, following the numbers for the C-Zones, Outer-Zones and Outside FZ (see table 2) the data from this study meets the intention of the serving player to move the opponent and indicates an overall offensive character of most of the 3^rd strokes (Born, 2017; Brabenec, 2000; Crespo & Miley, 1998; Nowak & Panfil, 2012). This is also the main difference to the return placement which is by far more frequent to the middle zones, possibly explaining missing correlations between these two strokes.

Although there is a significant correlation between WTA and ITF players regarding the 3^rd stroke, every zone group related to an offensive tactic (C-Zones, Baseline, Longer than service line, Outside FZ, Outer Zones) is targeted more often by ITF players while both player groups hit the same percentage of 3^rd strokes in. With this, it seems reasonable that a lower return quality on the ITF level (less long and less into the middle zones) may lead to an offensive situation for the 3^rd stroke more often. Thus, the recommendation derived from this data is to try and place the 3^rd stroke at least longer than the service line or even either into the baseline zones or into the C-Zones.

4^th Stroke: All in all, the placement of the 4^th stroke is comparable to the placement of the 3^rd stroke as the returning player seems to have the same placement intentions when hitting the 4^th stroke as the serving player when hitting the 3^rd stroke.

Although correlating, the WTA and ITF players’ 4^th stroke placement differs marginally. Quite surprisingly at first sight, ITF players hit, similar to the findings regarding the 3^rd stroke, more often into the offensive zone groups than WTA players (see table 3). A second look triggers an attempt to explain this by a still overall lower quality of the 3^rd stroke of ITF players in comparison to the WTA players in spite of the placement. This suggests – and underlines the obvious – that stroke placement is just one factor that defines the quality of a stroke and its effect on an opponent. Other factors being stroke velocity, stroke timing and spin.

All in all, the recommendation derived from this data for the placement of the 4^th stroke is the same as for the placement of the 3^rd stroke whilst always depending on the situation the player is in.

Although previous research reported differences between men’s and women’s tennis regarding the game opening with respect to i.e., winning percentages (Carboch, 2017; Hizan et al., 2011), the present findings on stroke placement support previous research on men’s tennis.