{"id":60158,"date":"2023-06-30T18:10:12","date_gmt":"2023-06-30T18:10:12","guid":{"rendered":"https:\/\/revista-apunts.com\/influencia-del-nivel-del-oponente-en-la-creacion-de-oportunidades-de-gol-en-futbol-femenino\/"},"modified":"2023-10-03T09:35:07","modified_gmt":"2023-10-03T09:35:07","slug":"influence-of-quality-of-opposition-in-the-creation-of-goal-scoring-opportunities-in-female-football","status":"publish","type":"post","link":"https:\/\/revista-apunts.com\/en\/influence-of-quality-of-opposition-in-the-creation-of-goal-scoring-opportunities-in-female-football\/","title":{"rendered":"Influence of quality of opposition in the creation of goal scoring opportunities in female football"},"content":{"rendered":"\n

Abstract<\/strong><\/h2>\n\n\n\n

The aim of this study was twofold: i) firstly, to determine the influence of the criterion opponent quality on the offensive tactical behaviour of teams participating in the FIFA Women\u2019s World Cup France 2019 and, ii) on the other hand, to determine whether there were differences in criteria related to the start and development of ball possessions and their influence on the creation of scoring opportunities based on opponent quality. Using observational methodology, 2,045 ball possessions from 14 matches of the final phase of this championship were analysed. First, a bivariate analysis was carried out on the basis of opponent quality, and then three predictive decision tree models were run for the weak, normal and strong categories of the opponent quality criterion. Statistically significant differences were found based on opponent quality for the criteria match result, depth start area, defensive positioning, spatial context of the interaction, possession time in opponent\u2019s half, total time of possession, possession area and possession outcome. On the other hand, a similar pattern was found to exist in obtaining goal scoring opportunities regardless of opponent quality, which was characterised by maintaining possession in the opponent\u2019s half, starting possession in areas close to the opponent\u2019s goal and an initial attacking intention to advance towards the opponent\u2019s goal quickly. <\/p>\n\n\n

Keywords:<\/strong> decision tree<\/span>, FIFA Women\u2019s World Cup<\/span>, observational methodology<\/span>, women\u2019s football<\/span><\/p> <\/div> \n\n\n\n

Introduction <\/strong><\/h2>\n\n\n\n

Women\u2019s football is a phenomenon that has recently started to grow in a significant manner. Among the women\u2019s leagues that still exist, the earliest was founded in 1968 in Italy. This represents a difference of 80 years compared to men\u2019s football (Lago et al., 2022<\/a>). During these decades, women\u2019s football has had to face, among other difficulties, the ban imposed on playing matches on English Football Association (FA) club grounds (Jenkel, 2021<\/a>). Today, however, football has benefited from a remarkable increase in social and media interest, but despite this, there are still obvious disparities between men\u2019s and women\u2019s football (Lago et al., 2022<\/a>).<\/p>\n\n\n\n

One such gap is in the area of research. Only 20% of studies published on the sport are carried out on women\u2019s football (Kirkendall & Krustup, 2020<\/a>). This highlights the large gender knowledge gap in sport and its scientific development (Lago et al., 2022<\/a>; Nassis et al., 2022<\/a>). These factors may account for some of the differences in team performance across the sexes (<\/a>Casal et al., 2021<\/a>Garnica-Caparr\u00f3s y Memmert, 2021<\/a>; Pappalardo et al., 2021<\/a>).\u00a0<\/p>\n\n\n\n

Performance in football should be understood from a polyhedral perspective (Preciado et al., 2021<\/a>) in which possession-related performance indicators play an important role (Wang et al., 2022<\/a>). In recent years, some studies on women\u2019s football have been published in this area (Iv\u00e1n-Baraga\u00f1o et al., 2021<\/a>, 2022<\/a>; Maneiro et al., 2021<\/a>; Mitrotasios et al., 2022<\/a>). Despite this, expertise on these indicators in men\u2019s football (Wang et al., 2022<\/a>) has been the only reliable and objective source of information for several decades for women\u2019s football professionals. In this sense, this work agrees with Lago et al. (2022)<\/a> in stating that performance in football should not be approached from a unisex perspective (applying knowledge from men\u2019s football to women\u2019s football), and consideration should be given to the need to increase scientific work on women\u2019s football (Nassis et al., 2022<\/a>) in order to equip professionals with specific knowledge.<\/p>\n\n\n\n

In relation to team performance in competition, there are some contextual criteria that have been proven to influence the offensive and defensive behaviour of football teams. Among these criteria, opponent quality has been rigorously studied in men\u2019s football (Almeida et al., 2014<\/a>; Castellano et al., 2013<\/a>; Fern\u00e1ndez-Herm\u00f3genes et al., 2021<\/a>; Garc\u00eda-Rubio et al., 2015<\/a>; Lago, 2009<\/a>; S\u00e1nchez et al., 2019<\/a>) and to a lesser extent in women\u2019s football (Lee & Mills, 2021<\/a>). One of the first studies that analysed the influence of opponent quality criteria on offensive play in men\u2019s football revealed a reduction in possession time of 0.2% for each unit of difference in the final classification of the 2005-2006 Spanish League (Lago, 2009<\/a>). In turn, Castellano et al. (2013)<\/a> observed how offensive and defensive positioning changed depending on the quality of the opponent: teams showed greater depth and width in the offensive phase against weak teams and, surprisingly, teams facing strong teams showed greater depth and width in the defensive phase (Castellano et al., 2013<\/a>). Almeida et al. (2014)<\/a> demonstrated that the top-ranked teams in the 2011\/2012 UEFA Champions League were able to recover the ball in more forward areas of the pitch, an indicator related to offensive success in women\u2019s football (Iv\u00e1n-Baraga\u00f1o et al., 2021<\/a>). In the same competition, a longitudinal study carried out during the 2009 to 2013 seasons revealed a significant positive association between opponent quality (i. e. difference in UEFA ranking) and goal difference in the match (Garc\u00eda-Rubio et al., 2015<\/a>). On the other hand, research on the influence of opponent quality on match performance in women\u2019s football is scarce. In this regard, the only study published to date is that of Lee & Mills (2021)<\/a>. This study sought to determine the influence of the criteria opponent quality and time score on the execution of corners in the Women\u2019s World Cup France 2019, revealing statistically significant differences based on opponent quality for the criteria passing the ball, type of pass, number of attackers and attacking organisation, among others (Lee & Mills, 2021<\/a>). In contrast, opponent quality was not found to be a criterion that significantly influenced the outcome of the set-pieces analysed.\u00a0<\/p>\n\n\n\n

For all of the above reasons, and due to the need to increase the degree of understanding about the offensive process in women\u2019s football, as well as to determine which criteria can influence this process, this study was carried out. The objectives of this study were: i) to determine the influence of the criterion opponent quality on the offensive tactical behaviour of teams participating in the FIFA Women\u2019s World Cup France 2019 and ii) to determine whether there were differences in criteria related to the start and development of ball possessions and their influence on the creation of scoring opportunities based on opponent quality.<\/p>\n\n\n\n

Materials and method<\/strong><\/h2>\n\n\n\n

Design<\/strong><\/h3>\n\n\n\n

To carry out this study, the observational methodology (Anguera, 1979<\/a>) was used. This methodology is ideal for the analysis of collective behaviour in natural events such as football matches (Anguera et al., 2011<\/a>).<\/p>\n\n\n\n

It was a nomothetic design \u2014several study units\u2014, isolated (intra-session follow-up) \u2014a single championship analysed\u2014, and multidimensional \u2014several levels of response reflected in the observation instrument (Anguera et al., 2011<\/a>).<\/p>\n\n\n\n

Participants <\/strong><\/h3>\n\n\n\n

All incidents of ball possession (n<\/em>\u00a0=\u00a02,045) with a duration of four seconds or more during the FIFA Women\u2019s World Cup France 2019 finals matches were analysed. Ball possession starts from the moment the observed team gains control of the ball, through a ball interception or a restart of play, until possession is transferred to the opposing team, or there is a break in the game (Almeida et al., 2014<\/a>).<\/p>\n\n\n\n

Two matches were excluded from the analysis because of the large difference in quality level of the teams involved: (i) Germany 3-0 Nigeria (Round of 16: No 2 and 38 FIFA ranking, respectively) and (ii) England 3-0 Cameroon (Round of 16: No 3 and 46 FIFA ranking, respectively).<\/p>\n\n\n\n

The analysed games were ranked based on opponent quality using the latest FIFA rankings pre-tournament [https:\/\/www.fifa.com\/fifa-world-ranking\/women?dateId=ranking_20190329<\/a>]. This ranking is calculated on the basis of the sum of points obtained in the matches played by each team taking into account: (i) the result of the matches played, (ii) the location of the match, (iii) the importance of the match, and (iv) the difference between the FIFA ranking positions at that time [https:\/\/www.fifa.com\/fifa-world-ranking\/procedure-women<\/a>]. The criterion opponent quality was calculated based on the difference between the FIFA ranking positions of the competing teams for each of the ball possessions (i. e. in the final between the USA (No 1 FIFA ranking) and the Netherlands (No 8 FIFA ranking) the USA\u2019s ball possessions were recorded as -7 and vice versa). The actions were classified based on an analysis of k<\/em> means into three groups according to the value of the criterion opponent quality: i) weak (n<\/em> = 700): [-12, -4], ii) similar (n<\/em> = 765); [-3, +3] and iii) strong (n<\/em> = 580): [+4, +12]. <\/p>\n\n\n\n

Observation and recording instrument  <\/strong><\/h3>\n\n\n\n

The observation instrument was adapted from Iv\u00e1n-Baraga\u00f1o et al. (2022)<\/a> and is presented in Table 1. It was a combination of field format and exhaustive and mutually exclusive category systems, which was necessary due to the high complexity of the situation under study (Anguera et al., 2018).<\/p>\n\n\n\n

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Table 1<\/strong><\/p>\n\n\n\n

Observation instrument.<\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

The recording instrument used was free Lince Plus<\/em> software [https:\/\/observesport.github.io\/lince-plus<\/a>] (Soto et al., 2019).<\/p>\n\n\n\n

Procedure<\/strong><\/h3>\n\n\n\n

This study was approved by the Ethics Committee of the University of A Coru\u00f1a (approval code): EIUDC-2019-0024). All matches were recorded from public television, stored on an external hard drive and analysed post-event (Casal et al., 2019<\/a>).<\/p>\n\n\n\n

Three observers were trained in the observation, recording and coding of the offensive actions analysed (Losada & Manolov, 2015<\/a>). All three observers were authors of this work, held the UEFA PRO football coaching qualification and two of them hold PhDs in Sport Science and have more than 30 years of experience in observational methodology between them. The third observer was a pre-doctoral researcher in their research group.<\/p>\n\n\n\n

The data quality control was achieved by calculating the Cohen\u2019s (1960)<\/a> inter-observer kappa coefficient, calculated from the average between the three pairs of observers, who independently recorded 258 ball possessions in two randomly selected entire matches (Arana et al., 2016<\/a>). The average value of this coefficient was .869 (range = .746 – .979), considered excellent (Landis & Koch, 1977<\/a>).\u00a0<\/p>\n\n\n\n

Statistical Analysis<\/strong><\/h3>\n\n\n\n

To achieve the first objective, a bivariate analysis was carried out using contingency tables of the criteria included in the instrument and observation and the criterion opponent quality. The degree of association was analysed using the contingency coefficient. The effect size was classified as mild (ES\u00a0=\u00a0.10), moderate (ES\u00a0=\u00a0.30) or large (ES\u00a0\u2265\u00a0.50) (Gravetter & Wallnau, 2007<\/a>). For the four quantitative categories, which evidences the fact that observational methodology is mixed methods in itself (Anguera et al., 2018<\/a>), normality and homoscedasticity among the three groups were tested and rejected using the KS test and Lev\u00e9ne test, respectively, with a significance level p<\/em>\u00a0<\u00a0.05. The Kruskall-Wallis test was applied to these criteria. The post-hoc<\/em> differences were calculated using the Bonferroni correction.\u00a0<\/p>\n\n\n\n

Secondly, in order to test whether there were differences in scoring opportunities based on opponent quality, three multivariate predictive analyses were performed using the decision tree technique (for the weak<\/em>, similar<\/em> and strong<\/em> categories of the opponent quality<\/em> criterion). This technique, recently applied within the field of sport (Gim\u00e9nez et al., 2020<\/a>; Iv\u00e1n-Baraga\u00f1o et al., 2021<\/a>; Maneiro et al., 2019<\/a>) enabled an optimal interpretation of the results obtained. For the construction of these models, a recoding of the criterion result of the<\/em> action<\/em> was used as the dependent variable (Success<\/em> = goal, shot and delivery into the penalty area; No success<\/em> = remaining possessions). The remaining criteria were entered as independent or predictors in all three models. The tree growth method was CHAID. The model was validated using the cross-validation method, the minimum number of observations at the nodes was 80 (parent nodes) and 40 (terminal nodes) and the maximum depth of the tree was set at 4 levels. Misclassification costs were assumed to be equal for the two categories of the dependent variable. The proposed models demonstrated a high predictive ability, with a risk estimate value of .277, .208 and .217 for the weak<\/em>, similar<\/em> and strong<\/em> categories, respectively. Statistical analyses were performed with SPSS 25.0 software (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25, IBM Corp., Armonk, NY, USA).<\/p>\n\n\n\n

Results<\/strong><\/h2>\n\n\n\n

The results obtained from the bivariate analysis are presented in Table 2. Statistically significant differences were found based on opponent quality for the criteria match result, depth start area, defensive positioning, spatial context of the interaction, possession time in opponent\u2019s half, total time of possession, possession area and possession outcome.<\/p>\n\n\n\n

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Table 2<\/strong><\/p>\n\n\n\n

Bivariate analysis based on the criterion opponent quality<\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em><\/em>.<\/p>\n\n\n\n

See Table<\/a><\/p>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n

The results obtained from the predictive decision tree analysis for the possessions made in the weak<\/em> category are shown in Figure 1. The final model had a reliability of 76.1% (48.2% sensitivity; 89.0% specificity). The criteria that were significant for scoring opportunities were possession area (\u03c72<\/sup> = 142.07; p<\/em> < .001), possession time in opponent\u2019s half (\u03c72<\/sup> = 57.252; p<\/em> < .001), initial offensive intention (\u03c72<\/sup> = 17.012; p<\/em> < .001), possession time (\u03c72<\/sup> = 10.316; p<\/em> < .05), depth start area (\u03c72<\/sup> = 9.870; p<\/em> < .05), time of possession in own half (\u03c72<\/sup> = 8.506; p<\/em> < .05). Furthermore, the criteria interaction which produced a higher probability of scoring opportunities was observed at node 11 (n<\/em> = 97; 71.1\u2006% Success \u2013 28.9 No success), involving the interaction of the criteria possession area (attacking half), initial offensive intention (advance), and depth start area (pre-defensive, pre-offensive, offensive). <\/p>\n\n\n\n

\"\"\/<\/figure>\n\n\n\n

For possessions made when facing an opponent of similar quality (Figure 2) the criteria entered by the decision tree algorithm were possession area (\u03c72<\/sup> = 156.142; p<\/em> < .001), time of possession in own half (\u03c72<\/sup> = 15.817; p<\/em> < .001), possession time in opponent\u2019s half (\u03c72<\/sup> = 36.89; p<\/em> < .001), and initial offensive intention (\u03c72<\/sup> = 8.844;p<\/em> < .005). The model had a reliability of 81.31% (43.2% sensitivity; 91.5% specificity). For this type of action, the highest probability of attaining a scoring opportunity was observed in node 8 (n<\/em> = 121; 57.9\u2006% Success), involving the interaction of the criteria possession area (attacking half), time of possession in own half (\u2264 0 seconds), and initial offensive intention (advance).<\/p>\n\n\n\n

\"\"\/<\/figure>\n\n\n\n

Finally, the results obtained from this technique for the strong<\/em> category of the opponent quality criterion (Figure 3) revealed the influence of the criteria possession area(\u03c72<\/sup> = 125.623; p<\/em> < .001), possession time in opponent\u2019s half (\u03c72<\/sup> = 36.045; p<\/em> < .001), initial defensive intention (\u03c72<\/sup> = 12.475; p < .001), and initial offensive intention (\u03c72<\/sup> = 8.102; p<\/em> < .005). For this type of action, the highest probability of scoring opportunities was observed in node 8, involving the interaction of the criteria possession area (mid-offensive), initial defensive intention (defend) and initial offensive intention (advance). When these criteria and categories interacted with each other, the probability of gaining opportunities was 59% (n<\/em> = 69) compared to a 41% probability of no success (n<\/em> = 48). The proposed model had a specificity of 89.2% and a sensitivity of 50.7% (80.2% reliability).<\/p>\n\n\n\n

\"\"\/<\/figure>\n\n\n\n

Discussion<\/strong><\/h2>\n\n\n\n

This study was carried out with a twofold objective. Firstly, the aim was to determine how the criterion opponent quality<\/em> influenced the tactical behaviour of teams participating in the final phase of the FIFA Women\u2019s World Cup France 2019 and, on the other hand, to determine whether there were differences in criteria related to the start and development of ball possessions and their influence on the creation of scoring opportunities based on opponent quality.<\/p>\n\n\n\n

The results obtained from the bivariate analysis revealed differences in 10 of the 17 criteria analysed in this study. In this line, differences have been found in the match result criteria. This is a logical finding, which confirms the accuracy of the FIFA ranking prepared prior to the championship under analysis in predicting the performance of teams in international championships. In addition, differences have been observed in the criterion depth start area<\/em>. Possessions made against an opponent of strong quality began in the defensive zone more frequently, in line with the findings of Almeida et al. (2014)<\/a>. The criterion spatial context of the interaction<\/em> also revealed differences based on opponent quality. Possessions made against an opponent of similar quality began mainly through MM interaction contexts (middle zone vs. middle zone). This finding may be justified by a higher concentration of female players in the central areas of the effective playing space, as observed in men\u2019s football (Castellano et al., 2013<\/a>). In relation to the spatial context of interaction, it is significant that when possessions were made facing an opponent of weak quality, there was an increase in defensive contexts of interaction, such as BF (back zone versus forward zone). This finding may indicate that better teams are able to advance and overcome opposing lines of pressure more easily (Almeida et al., 2014<\/a>), reaching contexts of offensively valuable interaction more frequently during their ball possessions.<\/p>\n\n\n\n

In relation to the duration of the ball possessions analysed, differences were observed for the criteria possession time in opponent\u2019s half<\/em>, total time of possession<\/em> and number of passes<\/em>. This demonstrates that opponent quality was a criterion that influenced the duration of ball possessions, in the same way as in men\u2019s football (Lago, 2009<\/a>). Possessions made against an opponent of weak quality had a longer duration overall and in the opponent\u2019s half. This is an important finding due to the importance of maintaining possession in the opponent\u2019s half (Casal et al., 2017<\/a>; Casal et al., 2019<\/a>) and highlights the greater ability of better teams to execute combinative actions in tight spaces and close to the opponent\u2019s goal. In addition, keeping the opposing team away from their own goal (Camerino et al., 2012<\/a>) makes it impossible for the opposing team to create goal-scoring opportunities, due to the added difficulty of creating such opportunities from back areas of the pitch in women\u2019s football (Iv\u00e1n-Baraga\u00f1o et al., 2021<\/a>; Scanlan et al., 2020<\/a>). In this sense, this work agrees with Almeida et al. (2014)<\/a> in stating that the best teams are more effective at pressing after losses in forward areas of the pitch, as the simple act of maintaining possession in these areas may enable them to press more aggressively and efficiently once they have lost possession of the ball.<\/p>\n\n\n\n

The results obtained in relation to the criterion result of the action<\/em> based on the criterion opponent quality<\/em> revealed statistically significant differences. The probability of scoring opportunities (i. e. goal, shot or delivery into the penalty area) against a weak opponent was 10 and 8 percentage points higher compared to possessions made against similar and strong opposition, respectively. <\/p>\n\n\n\n

Furthermore, from the multivariate results obtained from the decision tree technique, it is possible to observe common factors in the way goal scoring opportunities are attained regardless of the opponent quality. From these results, it can be confirmed that possession area was the most influential criterion in obtaining this type of action, just as in other studies carried out in men\u2019s football (Casal et al., 2017<\/a>, 2019<\/a>) and women\u2019s football (Iv\u00e1n-Baraga\u00f1o et al., 2021<\/a>, 2022<\/a>; Maneiro et al., 2021<\/a>). Similarly, initial offensive intention significantly influenced the likelihood of scoring opportunities in the championship analysed. Specifically, ball possessions that started with an initial offensive intention to advance significantly increased the probability of success, consistent with existing literature (Mitrotasios et al., 2022<\/a>; Maneiro et al., 2019<\/a>). In this sense, this work agrees with Sarmento et al. (2014)<\/a> in stating that, once ball possession is regained, a quick pass or drive to areas far away from the opposing team must take place, quickly disabling several players from the opposing team and taking advantage of this situation of defensive disorganisation.<\/p>\n\n\n\n

Finally, a differentiating element was observed between the three multivariate models considered: the influence of the initial defensive intention criterion in obtaining scoring opportunities in possessions made against an opponent of strong quality. This factor, which may be important when considering pressure after a turnover, highlights the need for the best teams to quickly press the player who regains possession (Vogelbein et al., 2014<\/a>) in order to reduce the time and space for action, thereby reducing the likelihood of scoring opportunities in that play action.\u00a0<\/p>\n\n\n\n

Conclusions<\/strong><\/h2>\n\n\n\n

Based on the results of this study, it has been demonstrated that opponent quality was a criterion that significantly affected tactical criteria such as the starting area of ball possessions, the opponent\u2019s defensive positioning or the spatial context of interaction. In addition, higher total possession times and possession times in the opponent\u2019s half were found when ball possessions were made against teams of a weaker quality, a factor that has been proven to influence the success of ball possessions in elite football. Furthermore, the fact that only matches from the final phase of the FIFA Women\u2019s World Cup France 2019 were analysed (the 14 teams analysed were among the top 16 in the FIFA 2019 ranking) is an important factor, as it reveals that opponent quality not only influences the behaviour and outcome of ball possessions between teams of very unequal levels, but also influences these actions among the elite of world women\u2019s football. In contrast, from the results obtained from the three decision tree models, it has been possible to verify a trend present in elite women\u2019s football, regardless of the quality of the opponent: the greatest probability of obtaining successful ball possessions is produced by the interaction of criteria associated with ball recoveries in forward areas, with the intention of advancing towards the opponent\u2019s goal and the development of ball possessions in the opponent\u2019s half. These results can help these teams to design match strategies aimed at reproducing these tactical behaviours.<\/p>\n\n\n\n

Acknowledgements<\/strong><\/h2>\n\n\n\n

The authors are grateful for the support of the Integration between observational and external sensor data project: Creation of LINCE PLUS software and development of the mobile application for the optimisation of sport and health-enhancing physical activity<\/em> [EXP_74847] (2023). Ministry of Culture and Sport, Higher Council for Sport and the European Union.<\/p>\n","protected":false},"excerpt":{"rendered":"

Abstract The aim of this study was twofold: i) firstly, to determine the influence of the criterion opponent quality on the offensive tactical behaviour of teams participating in the FIFA Women\u2019s World Cup France 2019 and, ii) on the other hand, to determine whether there were differences in criteria related to the start and development […]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":1,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","inline_featured_image":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":""},"categories":[49,49],"tags":[10662,10661,429,10663],"author_meta":{"display_name":"finderwilber","author_link":"https:\/\/revista-apunts.com\/en\/author\/finderwilber\/"},"featured_img":null,"coauthors":[],"tax_additional":{"categories":{"linked":["Sport Training<\/a>","Sport Training<\/a>"],"unlinked":["Sport Training<\/span>","Sport Training<\/span>"]},"tags":{"linked":["decision tree<\/a>","FIFA Women\u2019s World Cup<\/a>","observational methodology<\/a>","women\u2019s football<\/a>"],"unlinked":["decision tree<\/span>","FIFA Women\u2019s World Cup<\/span>","observational methodology<\/span>","women\u2019s football<\/span>"]}},"comment_count":"0","relative_dates":{"created":"Posted 3 years ago","modified":"Updated 3 years ago"},"absolute_dates":{"created":"Posted on 30 June 2023","modified":"Updated on 3 October 2023"},"absolute_dates_time":{"created":"Posted on 30 June 2023 18:10","modified":"Updated on 3 October 2023 09:35"},"featured_img_caption":"","series_order":"","_links":{"self":[{"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/posts\/60158\/"}],"collection":[{"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/posts\/"}],"about":[{"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/types\/post\/"}],"author":[{"embeddable":true,"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/users\/2\/"}],"replies":[{"embeddable":true,"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/comments\/?post=60158"}],"version-history":[{"count":8,"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/posts\/60158\/revisions\/"}],"predecessor-version":[{"id":61700,"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/posts\/60158\/revisions\/61700\/"}],"wp:attachment":[{"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/media\/?parent=60158"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/categories\/?post=60158"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/revista-apunts.com\/en\/wp-json\/wp\/v2\/tags\/?post=60158"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}