Introduction

In handball, longitudinal studies indicate changes in the effectiveness of throwing from wing positions and the effectiveness of defensive play1, as well as differences in team performance between World Cups2 and European Championships3,4. Analyses of the game at the European Championships also include individual women’s teams5. Previous work includes results indicating higher game efficiency and specific tactical solutions in teams achieving high sporting performance6,7. Studies have also shown differences in the place of completion and effectiveness of activities between men and women during championship games in indoor8 and beach9 handball.

The literature indicates that one area of research in team games is the analysis of differences between win and lose matches. Differences in performance analysis according to the outcome of the match (win or lose) of rugby have been demonstrated in longitudinal studies in women10 and man11. Single-game results also support the demonstrated differences in women’s12 and man’s13. The same differences are found in women’s soccer14 and men’s basketball15. The differences shown indicate a greater number and effectiveness of technical and tactical measures in the matches won.

Analysis of handball games at the highest level shows differences in the number and efficiency of teams’ actions between winning and losing games at the Olympic Games16 and in EHF Champions League matches17. The same differences between winning and losing teams were shown in domestic league games18. In addition to professional games, similar differences between win and loser are also found in amateur matches between men and women19, which is consistent with the results obtained in professional games. Analysis of the last 10 min of women’s matches also shows differences in the number and effectiveness of selected actions depending on the outcome20. Similar results are also found in men’s matches20. The main trend in the research presented is the higher number and effectiveness of offensive actions (number of throws, number of goals, throwing efficiency, number of assists) with respect to place and tactical situation, and defensive actions (steals, number of goalkeeper defenses, effectiveness of goalkeeper interventions) in matches won.

In addition to studying differences in performance analysis (win-lose), research in team games also focuses on building statistical models concentrated on predicting the outcome of matches12,15,21,22,23,24. Previous studies in handball focusing on the prediction of sports success indicate that the number and effectiveness of team and individual actions determine the match’s outcome at the Women’s Olympic Games25, and the men’s World Cup (2007–2019)1. The authors also point to more predictors of winning in men’s matches than in women’s amateur games19. An analysis of the last 10 min of balanced handball matches showed that the number of technical fouls and the goalkeeper’s efficiency during shots from 9 m were predictors of winning20. Studies focusing on team performance analysis indicate that the number and efficiency of selected team actions are predictors of goal difference (goals scored - goals defeated) in matches (3 seasons) of men’s handball26. Previous studies have also shown a relationship between the technical and tactical actions of teams and their place in the men’s World Cup ranking2. An analysis of three seasons of men’s competition showed that the strongest predictors of increasing the probability of winning were the number and effectiveness of selected types of throws and the effectiveness of goalkeeper interventions, with simultaneous differences in the predictors depending on the season of competition26.

The handball results presented in the introduction indicate a substantive need to analyze performance in handball at the highest sport level (European Championships) and to try to determine whether there are differences between matches won and lost, as well as the need to determine which variables are predictors of goal difference and match result at the highest sport level in women’s handball.

The first aim of the research was to determine whether there are differences in performance analysis in matches won and lost at the 2022 European Women’s Handball Championship. The second aim of the research was to determine which of the teams’ technical and tactical actions are predictors of goal difference (goals scored - goals defeated) and match outcome (win) in the 2022 European Women’s Handball Championship matches.

Materials and methods

Procedures

The data was obtained from the official website of the tournament organizer European Handball Federation (https://ehfeuro.eurohandball.com/women/2022/matches/ accessed June 27, 2024). For each match, the website generates a statistical report containing data on the variables included in this study. The authors manually entered the report data into a spreadsheet, creating a database for each match and each team. The first author evaluated the accuracy of the data entered into the spreadsheet. For the comparative analyses and in the logistic regression analysis, the dichotomous independent variable specified in the study was the outcome of the match (win or lose). In the linear regression analysis, the dependent variable was goal difference. The independent variables are described in subsection Material.

Material

The study material consisted of figures of handball matches played at the 2022 European Women’s Championship tournament. The material was obtained from the official website (https://ehfeuro.eurohandball.com/women/2022/matches/ accessed June 27, 2024) of the organizer of the European Handball Federation [EHF]. The owner of the EHF statistics has given written permission for their use for scientific purposes.

The number of matches at the 2022 Women’s European Championship was 47 (n = 47), of which 44 were included in the analysis. Matches ending in a draw (n = 2) and one match with an incomplete report (n = 1) were excluded from the study. The analyzed matches were played by 16 teams at different levels of the tournament (Preliminary Round, Main Round, Placement Match 5/6, Semifinals, Placement Match 3/4, Final).

In each of the analyzed matches, the number of attacks, number of throws, number of goals, and efficiency expressed in percentage were recorded in the following tactical situations: general attack [AT], positional attack [PosAT], fast breaks [FB], breakthroughs [BT], throws: from 6 m [6 m], left wing [LW], right wing [RW], sum of throws from the wing [W] (LW + RW), from 9 m from the left side of the court [9mL], from 9 m in the center sector of the court [9mC], from 9 m from the right side of the court [9mR], sum of throws from 9 m [9 m] (9mL + 9mC + 9mR), and penalty throws [7 m]. In each match, the number of defenses and the effectiveness of goalkeeper interventions in the following tactical throwing situations were recorded: total number [ALL], in the fast attack [FB], in breakthroughs [BT], from the 6th meter [6 m], wing [W], 9th meter [9 m], and penalty kicks [7 m].

Statistical analysis

The collected study material was subjected to statistical analysis. The normality of distribution was determined by the Kolmogorov-Smirnov [K-S] test. The homogeneity of variance was determined by Levene test. For parametric data, the Student’s t-test for two independent groups was used to examine differences between winning and losing matches, and Cohen’s effect size [ES] d was determined (< 0.2 - no effect, 0.2–0.49 - small effect, 0.5–0.79 - intermediate effect, > 0.8 - strong effect)27. For non-parametric data, the Mann-Whitney U test was used. To determine ES, partial eta-square (η2 (< 0.01 – no effect, 0.01–0.059 – small effect, 0.06–0.139 – intermediate effect, > 0.14 – large effect)27.

Multivariate regression analysis (stepwise-backward method) was used to determine predictors of differences in the number of goals (goals scored - goals lost). The normality of the residuals was determined using the Kolmogorov-Smirnov [K-S] test. The Durbin-Watson test was used to determine the autocorrelation of the residuals. Logistic regression analysis (stepwise - backward method) was performed to demonstrate the strength and direction of the effect of the explanatory variables on the binary variable (win - lose). The equality of observed and predicted values was tested using the Hosmer Lemeshow [H-L] test. Nagelkerk’s pseudo R2 and the Receiver Operator Characteristic (ROC) and the Area Under Curve (AUC) were determined as measures of goodness of fit.

The level of statistical significance was taken as p < .05. All statistical analyses were performed using TIBCO Statistica 13.3, IBM SPSS Statistics 28, and Microsoft Office Excel software for Microsoft 365 version 2308.

Results

The number of attacks and throws

The results obtained for the number of attacks, throws, goals, and their effectiveness in each tactical situation are presented in Table 1.

Table 1 The number of attacks and goals and the effectiveness of attacks and throws from different positions.
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The results obtained for the number of attacks indicate that winning teams carry out fewer PosAT (p = .019) than losing teams, and the ES of these differences is intermediate. There is also evidence of a higher number of FBs carried out by teams winning the game (p = .003) relative to losing teams, however, the ES of these differences is small. There are no significant differences in the other variables analyzed.

The number of goals

Analysis of the number of goals thrown in specific tactical situations indicated a higher overall number of goals in AT (p = .000) and PosAT (p = .000) in winning than losing teams, and the ES of these differences is strong. FB was shown winning teams score more goals (p = .010), however the ES is intermetiate. Winning teams also scored more goals from 6 m (p = .037) than losing teams, and the ES of these differences is small.Winning teamst scored more goals from 9mC (p = .029) ant the ES of this differences is small. Other tactical situations showed no significant differences in the number of goals between winning and losing matches.

The effectiveness of attacks and throws

The results indicate higher significant AT (p = .000) and PosAT (p = .000) efficiencies in winning teams, while the ES of these differences is strong. Analysis of throwing efficiency shows significantly higher values in winning teams in throwing situations from RW (p = .003), 9mC (p = .005), 7 m (p = .015), BT (p = .030), 9 m (p = .004) i W (p = .022), and the ES of the differences shown is intermediate. A higher efficiency of throws from 6 m in winning teams was also shown (p = .003), however the ES is small. In other situations, no statistically significant differences were shown.

The number of Goalkeeper’s saves

The results obtained for the number and effectiveness of goalkeepers’s defenses are presented in Table 2.

Table 2 The number and effectiveness of the goalkeeper’s saves.
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The data presented show a significantly higher average number of all defenses [ALL] (p = .000) and in the situation of throwing from the wing position [W] (p = .008) in winning matches. The ES of these differences is intermediate. The other throwing situations showed no statistically significant differences.

The effectiveness of Goalkepper’s saves

Analysis of effectiveness [%] indicates, its higher overall level [ALL] (p = .000) in winning teams, and the ES of these differences is strong. The data in Table 2 indicate significantly higher effectiveness of goalkeeper’s defenses in winning teams, in 6 m (p = .030), W (p = .008), 9 m (p = .017) i 7 m (p = .034) throw-in situations. The ES of the differences shown is intermediate. No statistically significant differences were shown in FB and BT cast situations.

Regression analysis of goal differences

The regression analysis on the goal difference presented in Table 3 indicates the presence of a significant model (p = .000). The predictors are the three independent variables, which explain a total of 74% of the dependent variable. PosAT% (p = .000) and GK% (p = .000) efficiency have the highest contribution to predicting goal differentials, while FB% (p = .000) has the lowest. The distribution of residuals is normal (K - S d = 0.07; p > .2), and there is no autocorrelation (D-W = 2.17). The distribution of observed versus predicted residuals is illustrated in Fig. 1. The regression equation takes the form:

Table 3 Predictors of goal differences – linear regression.
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Fig. 1
figure 1

Distribution of observed and predicted values.

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Goal differencess = .51PosAT [%] + .4GK [%] + .06FB [%] – 39.24.

Logistic regression of match oucome

The results of the logistic regression analysis, presented in Table 4, indicate the presence of a significant model (χ2 = 61.71; df = 3; p = .000; H-L = 5.07; p = .376; AUC = 0.96), which includes three variables that correctly classify 78% of cases (R2 = 0.78). The probability of winning is increased by the variables AT [%] (p = .000) by 55% and GK [%] (p = .006) by 24%. The number of throws from 9 m (p = .040) decreases the probability of winning by 20%.

Table 4 Predictors of match outcome (win) – logistic regression.
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Discussion

The statistical analyses carried out with regard to the first research objective allow us to conclude that there are differences in selected technical and tactical measures between the matches won and lost at the 2022 European Women’s Handball Championship. Referring to the second objective of the study, it was shown that the selected variables included in the analyses are predictors of goal differences and the outcome of the women’s handball match.

Differences between won and lost teams

Discussing the results involving the attacks carried out (number of attacks, goals, and efficiency), it should be pointed out that there are no differences in the number of ATs between the winners and losers, however, differences include the number of goals and throwing efficiency in this tactical situation. This may be influenced by several variables such as a higher level of motor, tactical, and technical preparation, as well as more effective defensive actions, including the effectiveness of the goalkeeper’s defenses. This may also be confirmed by the fact that losing teams carry out more positional attacks scoring fewer goals in them, while winning teams carry out more fast attacks scoring more goals in this element with comparable effectiveness with the losers including the effectiveness of the goalkeeper’s play. Effective defensive play results, in addition to not losing a goal, in the ability to launch a fast attack, and can prove crucial in winning a match28. The results obtained are consistent with the results in balanced, unbalanced and very unbalanced matches29, indicating a substantive need to undertake analysis in the proposed methodology in matches with different goal differences. Demonstrated differences in the effectiveness of throws and goalkeeper’s defenses also occur in women’s handball matches at the amateur level19, in the last 10 min of balanced games20 and men’s Champions League matches17, indicating their utilitarian nature. It is therefore necessary to shape these technical and tactical activities in the training process, as their high level can translate into sports successes. The results obtained can be one of the bases for planning and optimizing the training process at different levels of the women’s handball competition.

Analysis of throws in selected tactical situations showed no significant differences in their number. The results shown indicate a higher number of goals thrown from 6 m by winning teams. The analysis of throwing efficiency shows many differences between winning and losing matches, however, it should also be pointed out that the large standard deviations indicate the lack of homogeneity of the variables. Discussing the obtained differences in throwing efficiency, it should be pointed out that it is higher in the winning teams in the situation of throwing from 6 m, W, 9 m, 7 m. The reason for the obtained results may be both the level of technical training of the players, the level of tactical preparation creating the possibility of throwing in a convenient situation, but also the effectiveness of the goalkeepers, who in the indicated tactical situations also showed higher efficiency in winning matches. The differences shown also correspond with results reported by other authors indicating differences between won and lost matches in balanced and unbalanced matches over 10 years29. In women’s amateur matches, differences were registered only for 7 m, 9 m, and breakthrough, indicating differences that depend on the level of play: top-class vs. amateur. Analyses of the last 10 min of a handball match show that higher efficiency occurs during throws from the 9th meter and in this situation, the goalkeeper’s defenses are higher, which may indicate that a high level of these activities can influence the winning of the match20. Therefore, it seems logical to optimize training so that in these technical and tactical elements the players show the highest possible level, which can translate into sports results. At the same time, the results obtained do not correspond with longitudinal studies, which do not indicate the results obtained at the Olympic Games25. The reasons for the discrepancy may be the years in which the research was conducted, which may be due to the development of handball, a different approach to training, and the tactical solutions used. One reason may be the level of players related to the games (at the Olympic Games proportionally from all continents, at the European Championships only European teams). Similar results regarding throwing efficiency are found in men’s matches at the World Championships over 12 years1, in the EHF Champions League17, in domestic games18, amateur games19 and in the last 10 min of a match20. Although the results obtained are similar, it should be pointed out that in the men’s group, it is possible to see more variables differing in amateur matches and the last 10 min of the game, which may indicate differences between the handball game according to the gender of the players. This is also supported by studies that indicate differences in the place of offensive finishes and efficiency between men and women at the World Cup level8. Such a juxtaposition of results indicates the need to optimize sports training in terms of training volume and content with reference to the gender of players. The differences shown may also indicate the direction of research, which is to compare the actions of players during a match taking into account the score and gender of players at the highest level of the sport.

Discussing the differences in overall throwing efficiency, it is important to point out the differences between winners and losers in the throws from 9 m and W. The analyses conducted allow us to conclude that there are no differences in the throws from LW and higher by about 15% in throws from RW. Similarly, the training of the defense and goalkeepers should also be optimized in order to level out the throwing opportunities from this position, which can also translate into the outcome of the match. A similar approach should be applied to players who throw from 9mC, which, due to the characteristics of sports combat, are exposed to the blocking and cooperation of the defense and goalkeeper, since practice shows that this sector usually features defenders with above-average body height and individual technical training (for defensive play).

Referring to the effectiveness of throws from 7 m, the effectiveness of goalkeepers in this element, which is significantly higher in winning matches, can be identified as the reason for significant differences. Therefore, proper technical and tactical training during throwing (attacking players) and defending (goalkeepers) should be one of the components of the training process, as it can affect the sports results achieved by teams within a single match, as well as entire games. Referring to previous studies, it should be pointed out that at the same time, they coincide with those presented in this article in matches at the World Championships29 and amateur matches19, however, they do not coincide with the results at the Olympic Games25, which can be explained by the difference in competition levels. This state of affairs indicates the need to record the throwing efficiency and defenses of goalkeepers in 7 m throwing situations and to demonstrate the variables that may affect them both at different levels of competition and in longitudinal studies, which may allow us to track changes and trends in this element and adapt training to the latest requirements.

The results obtained for the number of defenses indicate that goalkeepers in winning matches make more effective interventions (per match) and in a throwing situation from wing positions. Adding to this the overall efficiency of defenses (%), it should be indicated that more variables are significantly higher in winning matches. Such a condition may indicate better technical, tactical, and motor preparation of the goalkeepers of the winning teams. However, it should be added that the results obtained are characterized by a significant standard deviation that sometimes exceeds the arithmetic mean, which indicates the lack of homogeneity of the group. As a basis for the results obtained in this way, the number of throws made in specific tactical situations should also be indicated, e.g. defending 1 out of 1 throw gives an effectiveness of 100%, while defending 6 out of 10 throws gives an effectiveness of 60%, however, the contribution to the sports result obtained may be different. Therefore, when evaluating the play of the goalkeeper, in addition to taking into account the positions from which the throw was made, take into account other variables including the number and effectiveness of defenses. The results obtained correspond with other reports in women’s games at the highest level29. It should also be noted that there are differences in the effectiveness of defenses with regard to the position of the throw, however, the higher overall effectiveness in matches won is utilitarian, as it is reported in both women’s indoor handball19,20, beach handball30 and men’s games19,20. In addition, the authors report higher effectiveness of goalkeeper interventions during shots from 9 m in women’s handball matches19,20 and men’s matches19,20. Also in men’s matches, differences are reported between matches won and lost during throws from wing positions19,20, which also corresponds to the results obtained in this study. Different results indicating that there was no difference in the effectiveness of goalkeeper interventions between won and lost matches were shown at the Women’s Olympic Games over 12 years25. Differences in the sports level of players between the European Championships and the Olympic Games (a qualification system proportional to the continents) can be cited as reasons. Another argument that may influence such results may be changes in the game of handball over the years, as indicated by studies showing differences over successive editions of the World Championships in the effectiveness of goalkeeper interventions (decrease in effectiveness in shots from 6 to 7 m, increase in FB)2. This state of affairs indicates the need for research covering successive editions of championship events in order to identify changes and trends in the game and optimize the training process.

Predictors of goal differences and match outcome

The regression results obtained for goal differences indicate three main predictors, which include efficiency. It can also be added that two of them are significantly different in between games won and lost (PosAT [%] and GK [%]), which may affect goal scoring and goal defense and, as a result, may lead to a widening of the goal difference. It should also be pointed out that effective defensive play, including goalkeeper defenses, may translate into a higher number of run FBs28. Even though the effectiveness of FB shots is at a similar level, it should be pointed out that the winning teams make a greater number of such attacks and also score a greater number of goals in this element. In addition, it should also be pointed out that there is no difference in the effectiveness of goalkeeper defenses in FB situations. Discussion of the results obtained is hampered by the small number of studies in this area. It should be pointed out that there are a greater number of predictors of goal difference in men’s matches26, of which GK% is the same as the results obtained in this study. This indicates that GK% is a utilitarian variable affecting goal differentials. It should be added that PosAT efficiency [%] consists of efficiency in specific throwing situations in which there are significant differences between winning and losing matches (6 m, RW, W, 9mC, 9 m), which only completes the results obtained. Discussing the predictor of GK%, it should be pointed out, that the significantly higher efficiency in specific throwing situations in winning matches (6 m, W, 9 m), which is a component of the overall efficiency of the goalkeeper and confirms the results obtained. Previous studies have shown predictors depending on the outcome of the match (balanced, unbalanced, very unbalanced), of which only one is in balanced matches29, which indirectly coincides with the results obtained in this study. The approach used in this study offers the possibility of predicting results, which may prove crucial when exit to the next round of the tournament may be determined by the goal balance, for example, in the group stage of the tournament, which may translate into achieved places in the tournament.

Logistic regression analysis indicates that the effectiveness of the attack (AT [%]) and goalkeeper defense (GK [%]) increase the probability of winning. When discussing these two parameters, it should be pointed out that they are made up of other variables. In the case of AT [%], it consists of the effectiveness of PosAT (which is the resultant of the variables of shots from each position), FB, and BT. The same situation is true for GK [%]. The components of these two variables showed significant differences between the winners and losers at the analyzed championships. Referring to previous research results, it should be pointed out that some variables overlap with those shown in this study, and some are the same indirectly, as they contain predictors that make up the analyzed AT [%] and GK [%]. In studies on women, it should be pointed out that one of the predictors of winning is GK [%] and GK in FB [%], which is a component of GK [%]25. The referenced model also included throwing efficiency, which is a component of AT [%]. In amateur matches, GK [%] and throwing efficiency are predictors of winning, which correlates with the results obtained19. Predictors of winning in the last 10 min of the match were goalkeepers’ efficiency in throws from 9 m, which indirectly correlates with the obtained results20. In addition, it should be pointed out that GK [%] was included in the beach handball win prediction model30. Referring to men’s handball matches, it should be pointed out that the predictors shown in this study directly or indirectly correspond to those in men’s matches at the World Championships1,2,31, in national competitions26, amateur19 and the last 10 min of a match20, and differences in the number of predictors between men and women may be due to many factors such as motor, technical, tactical preparation, and many others. Therefore, it is reasonable to conduct a differential performance analysis at a high level of sports involving the outcome of the match, as indicated by studies showing differences between the play of women’s and men’s teams8.

The number of throws from the 9th meter (9 m), which lowers the probability of winning, was also included in the model shown. It should be pointed out that despite the lack of differences in the number of throws from 9 m, their effectiveness is lower than in other situations included in the study, so the number of throws combined with lower effectiveness may affect the results obtained. In addition, it should be pointed out that after ineffective throws from 9 m (a throw missed, blocked, or saved by the goalkeeper), the opposing team can launch an effective attack (PosAT, FB), which can translate into scoring a goal28, widening the goal difference, and ultimately winning.

Practical aplications

The obtained and described results can become the basis for optimizing the training process in women’s handball to maximize the probability of sports success. The obtained results indicate the need to shape and increase the effectiveness of technical and tactical actions relating to the individual player, as well as whole teams. The selection of team tactics should also lead to actions showing the greatest differences between winning and losing, through which teams can gain a field advantage, which in the end can translate into sporting success within a single game, as well as entire competitions. Similarly, it is necessary to shape and improve the skills of defensive play, both with regard to individual players and team tactics, in order to lower the level of play of opponents in actions characterized by high efficiency and influence on the outcome of the match, as also indicated by previous research18,26. The results also indicate the need to maximize the effectiveness of goalkeeper interventions (motor, technical, tactical training), as this translates directly into the results obtained by teams.

The results obtained can also provide a reference point for coaches and team statisticians, who can compare their own analyses with those presented in this paper. This approach can be the basis for optimizing, modifying and also controlling the training process in handball.

Limitations

The presented results of the study refer to overall team offensive actions and defensive efforts focused only on recording the number and effectiveness of goalkeeper interventions. Despite the determination of the place of the throw from 6 m, it was not recorded which player made it: backcourt (after penetrating the defensive zone to 6 m) pivot (after an assist), winger (after attacking from the position of the playmaker or after running into the position of the pivot). The study did not analyze the tactics of the game (offensive, defensive), which may affect the number of shots made on offense, as well as defensive actions (steals). The study also did not include the individual actions of the players, which can affect the results (one-against-one play, assists). A limitation of the study is also the focus of defensive play only on the number and effectiveness of goalkeeper interventions, and the play of defensive players and their technical and tactical actions were not included. The study included matches throughout the tournament. Previous literature indicates that results may vary depending on the phase of the tournament played. The demonstrated limitations indicate a substantive need for further research in the adopted scheme with the inclusion of more of the variables demonstrated above in order to holistically determine which variables vary depending on the outcome of the match, as well as which ones affect the goal difference and match outcome.

Limitations also arise from the number of games analyzed, which is limited to only one championship tournament. Generalization of the results obtained to other levels of play is therefore difficult. In order to demonstrate the utilitarian variables that differ in matches won and lost, and to determine the predictors of goal differentials, and winning, further research should be conducted at different levels of play, both international and national.

Conclusions

There are differences in performance analysis between winning and losing matches at the 2022 European Women’s Handball Championship. Winning teams perform fewer positional attacks and more fast breaks. Winning teams score a higher number of goals in attack, positional attack, and fast breaks, and have a higher efficiency of attack and positional attack throwing.

In winning matches, teams throw a higher number of goals from the 6th meter, while throwing efficiency is higher in throws from the 6th, 7th, and 9th meters, from wing positions and breakthrough.

Goalkeepers in winning matches make a higher number of defenses (overall) and throw-in situations from wing positions, while overall intervention efficiency is higher with the inclusion of throw-ins from 6, 7, and 9 m and from wing positions.

Predictors of goal differential (increasing it) in matches at the 2022 European Women’s Handball Championship are efficiency: positional attack, fast break attack, and goalkeeper defenses. The effectiveness of the attack and goalkeeper’s defenses increase the probability of winning the match, while the number of shots from 9 m decreases it.

Specialized handball training should be optimized to increase the number and effectiveness of both team (tactics) and individual actions, which differentiate the outcome of the match, affect goal differentials, and are predictors of winning. Special attention should be paid to the players’ throwing and goalkeeper training with a view to maximizing the effectiveness of these activities. At the same time, it is necessary to shape team (tactics, cooperation) and individual (technique) defensive actions in situations that affect winning.

There is a substantive need to continue research aimed at determining the variables that differentiate the outcome of a match at different levels of handball play and are predictors of winning in order to determine them holistically and generalize the results obtained. Subsequent research should focus on determining the differences according to the outcome of the match and analyzing the predictors according to the phase of the championship tournament. Conducting further research in the adopted methodology at subsequent championship events will allow us to record and identify trends and changes in handball and provide a basis for modifying training plans to optimize them.