This study explores the influence of throw-ins on soccer team performance, specifically within the 2018-2019 English Premier League (EPL) season. By analyzing over 16,000 throw-ins, the research investigates the relationship between throw-in success metrics (such as first contact success, possession retention, time in possession, and shot creation) and a team's final league position. Additionally, it examines how the direction and length of throw-ins affect these outcomes. The study finds that higher league positions correlate with better throw-in performance, particularly for backward and lateral throws, which challenge the traditional preference for forward throws.
Description: Table 1 details the distribution of throw-ins across EPL teams, showing totals and averages per match for each team, vital for understanding the dataset's scope.
Relevance: This table provides context for the overall analysis, illustrating the frequency and variance of throw-ins across different teams.
Description: Figure 2 visually represents the correlation between league standings and throw-in performance metrics through scatter plots, offering a clear visual insight into the study's primary findings.
Relevance: The figure effectively communicates the strength and direction of the relationships between league position and throw-in success, crucial for understanding the study's implications.
The study highlights the significant role of throw-ins in soccer performance, suggesting that teams with effective throw-in strategies, particularly using backward or lateral directions, tend to achieve higher league standings. These findings challenge traditional coaching practices that favor forward throw-ins, offering new insights into how strategic throw-ins can impact game dynamics. The study encourages coaches to rethink their approach to throw-ins, potentially leading to improved team performance. Future research should explore these findings in different leagues and contexts to validate the generalizability of these results and further understand the tactical nuances of throw-in strategies.
This research investigates the impact of throw-ins on soccer performance, a relatively understudied set piece compared to free kicks and corners. The study analyzed over 16,000 throw-ins from the 2018-2019 English Premier League season to determine the relationship between throw-in performance (first contact success, possession retention, time in possession, and shot creation) and a team's final league position. Additionally, it examined how throw-in direction (backward, lateral, forward) and length affect these performance metrics. The study found a correlation between higher league positions and better throw-in performance, particularly for backward and lateral throw-ins, which were associated with higher first contact success, possession retention, and shot creation.
The abstract clearly states the research aims, focusing on the understudied area of throw-in impact on soccer performance. This focus provides a clear direction for the study and justifies its relevance.
The abstract effectively summarizes the main findings, including the correlation between throw-in performance and league position, and the impact of throw-in direction on success rates. This allows readers to quickly grasp the study's main contributions.
The abstract highlights the practical implications of the findings for coaching strategies, suggesting that focusing on backward or lateral throw-ins could improve team performance. This makes the research relevant to practitioners and increases its potential impact.
While the abstract mentions a correlation, providing the correlation coefficient would strengthen the claim and give readers a better understanding of the relationship's strength.
Rationale: Quantifying the correlation adds more weight to the findings and allows for a more objective assessment of the relationship.
Implementation: Include the correlation coefficient (e.g., r = 0.75) in the abstract.
Including a brief mention of the statistical methods used (e.g., correlation, ANOVA) would enhance the abstract's credibility and provide context for the findings.
Rationale: Mentioning the statistical methods demonstrates the rigor of the study and helps readers understand how the conclusions were reached.
Implementation: Add a short phrase like "using correlational and ANOVA analyses" to the abstract.
While the abstract acknowledges the limited research in this area, briefly mentioning the study's specific limitations (e.g., single season data, focus on EPL) would increase transparency and provide a more balanced perspective.
Rationale: Acknowledging limitations strengthens the research by demonstrating awareness of potential biases or constraints.
Implementation: Add a brief sentence acknowledging the limitations, such as "These findings, based on a single EPL season, warrant further investigation across different leagues."
This introduction sets the stage for a study on the impact of throw-ins in professional soccer. It emphasizes that while other set pieces like free kicks and corners have been extensively studied, throw-ins remain largely unexamined. The introduction highlights the frequency of throw-ins in a match, suggesting their potential importance in influencing possession and match outcomes. It also points out the existing gap in research regarding the strategic use of throw-ins and how different approaches (e.g., direction, length) might affect a team's success. The study aims to address this gap by investigating the relationship between throw-in performance and overall team success, as well as the influence of throw-in direction and length on key performance indicators like first contact success, possession retention, and shot creation.
The introduction effectively establishes the lack of research on throw-in strategies, creating a strong rationale for the study. By contrasting the existing knowledge on other set pieces with the limited understanding of throw-ins, the authors highlight the importance of their research.
The introduction convincingly argues for the study's relevance by emphasizing the frequency of throw-ins and their potential impact on possession and match outcomes. This connects the research question to important aspects of soccer performance.
The introduction clearly states the study's two main aims: examining the link between throw-in performance and overall soccer performance, and investigating the effect of throw-in direction and length on key performance indicators. This provides a clear focus and direction for the research.
While the introduction mentions the need for empirical evidence to inform coaching tactics, it could further elaborate on the potential benefits of understanding throw-in strategies for coaches. This would strengthen the connection between research and practice.
Rationale: Highlighting the practical implications would increase the study's appeal to coaches and practitioners, potentially leading to greater impact and adoption of findings.
Implementation: Add a sentence or two discussing how the study's findings could inform coaching decisions regarding throw-in training and in-game strategies.
Including a concise summary of the data source and analysis methods would give readers a preview of the study's approach and enhance transparency.
Rationale: A brief methodological overview would help readers understand the study's scope and limitations, allowing them to better evaluate the findings.
Implementation: Add a sentence or two mentioning the data source (EPL 2018-2019 season) and the type of analysis conducted (e.g., correlational analysis, analysis of variance).
The introduction could further explore the potential link between throw-in strategies and broader team tactics. This would provide a more nuanced understanding of how throw-ins fit within the overall game plan.
Rationale: Connecting throw-in strategies to team tactics would highlight the strategic importance of throw-ins and their potential to contribute to a team's overall success.
Implementation: Expand on the quoted text by providing examples of how different throw-in strategies might be integrated into offensive or defensive tactics.
This section details how the researchers investigated the relationship between throw-in strategies and soccer performance. They analyzed data from all 380 English Premier League matches during the 2018-2019 season, focusing on 16,154 throw-ins. The data, sourced from the StatsBomb database, included information about the throw-in location, direction, length, outcome, and subsequent possession. The researchers categorized throw-ins based on length (short, medium, long), direction (backwards, lateral, forwards), and pitch location. They then analyzed how these factors related to first contact success, possession retention, time in possession, and shot creation. To ensure data reliability, a subset of matches was independently coded and compared to the StatsBomb data, showing excellent agreement. Statistical analysis included descriptive statistics, correlations, and three-way ANOVAs to examine the relationships between the variables.
Using data from all 380 EPL matches provides a large and representative sample, increasing the generalizability of the findings.
The study clearly defines the independent variables (length, direction, location) and dependent variables (first contact success, possession retention, etc.), ensuring clarity and reproducibility.
Independently coding a subset of matches and calculating Cohen's kappa demonstrates a strong commitment to data reliability and strengthens the validity of the results.
The rationale for using 7 seconds as the cutoff for successful possession retention is not explicitly stated. Providing a justification would strengthen the methodological rigor.
Rationale: A clear justification for the 7-second threshold would enhance the transparency and interpretability of the results related to possession retention.
Implementation: Explain why 7 seconds was chosen, perhaps referencing previous research or providing a logical explanation based on the dynamics of soccer.
While the method section mentions "shot creation," it doesn't explicitly define what constitutes a shot. Does it include blocked shots, shots off target, or only shots on goal?
Rationale: A precise definition of "shot creation" is crucial for accurate interpretation of the results. Different definitions can lead to different conclusions about the effectiveness of throw-in strategies.
Implementation: Provide a more specific definition of "shot creation," clarifying whether it includes all shot attempts or only those meeting certain criteria (e.g., on target, resulting in a goal).
The method section mentions excluding throw-ins from injury clearances. Providing more detail on what constitutes an "injury clearance" and how these were identified would improve transparency.
Rationale: A more detailed explanation of the exclusion criteria would enhance the reproducibility of the study and allow readers to better understand the sample selection process.
Implementation: Provide a more precise definition of "injury clearance" and explain how these events were identified in the data. For example, specify whether this information was directly available in the StatsBomb data or if it required additional coding or interpretation.
Table 1 presents the total number of throw-ins and the average number of throw-ins per match for each of the 20 teams in the 2018-2019 English Premier League season. This table helps understand the distribution of throw-ins across teams and provides context for the overall sample size used in the study.
Text: "see Table 1"
Context: This resulted in a sample of 16,380 phases of play starting from a throw-in. After excluding throws-ins from injury clearances (i.e. possession freely given back to the opposition following the ball being kicked out of play due to an injury) a total of 16,154 throw-in’s were included in the sample (see Table 1) and resulted on average of 808 throw-in’s per team (range 716–912 throw-ins).
Relevance: This table is relevant because it provides descriptive statistics about the throw-ins included in the study. It shows the distribution of throw-ins across teams and gives an idea of how many throw-ins occur in a typical match. This information is crucial for understanding the scope and context of the analysis.
Figure 1 illustrates the definitions of key variables used in the study, including pitch location (divided into four areas), direction of throw-in (backward, lateral, forward), and length of throw-in (short, medium, long). The figure uses a simplified representation of half a soccer field to visually define these categories. This visual aid is essential for understanding how the researchers categorized and analyzed the throw-in data.
Text: "see Figure 1"
Context: Based on the performance indicators, three independent variables were examined, length (short, medium, long), direction (backwards, lateral, forwards) and pitch location (4 areas, see Figure 1).
Relevance: Figure 1 is crucial for understanding the methodology and analysis. It clearly defines the categories used for the independent variables (pitch location, direction, and length of throw-in), which are central to the research questions. The visual representation makes it easy to grasp the different throw-in scenarios being analyzed.
This section presents the results of the study, starting with descriptive statistics of the throw-ins. It then details the correlations found between a team's final league position and their throw-in performance metrics (first contact success, possession retention, time in possession, and shot creation). The results also show how throw-in direction and length influence these performance outcomes. Key findings include a positive correlation between higher league position and better throw-in performance, and the superior effectiveness of backward and lateral throw-ins compared to forward throws, especially in terms of first contact success and possession retention. The results also highlight how different throw-in strategies affect the likelihood of creating a shot at goal.
Table 3 provides a comprehensive overview of the throw-in data, including frequencies and percentages for different lengths, directions, and pitch locations. This allows readers to quickly grasp the distribution of throw-in characteristics and their associated outcomes.
The use of correlations and three-way ANOVAs allows for a thorough examination of the relationships between throw-in strategies and performance outcomes. The reporting of F-statistics, p-values, and effect sizes strengthens the analysis.
Figures 2, 3, 4, and 5 effectively illustrate the key findings, making the results more accessible and easier to understand. The figures complement the statistical analysis and provide a visual representation of the relationships between variables.
While the correlations between league position and throw-in performance are presented, the practical significance of these correlations could be further emphasized. For example, how much of a difference in league position is associated with a certain improvement in throw-in success?
Rationale: Adding context to the correlation results would make the findings more meaningful and relevant for coaches and practitioners.
Implementation: Provide examples of how differences in throw-in performance translate to differences in league standing or other relevant outcomes.
The results section mentions several interaction effects, but their interpretation could be clearer. What do these interactions mean in terms of how throw-in strategies differ across pitch locations and lengths?
Rationale: A clearer explanation of the interaction effects would enhance the understanding of how different throw-in strategies interact with each other and with pitch location.
Implementation: Provide a more detailed interpretation of the interaction effects, explaining how the relationship between throw-in direction and performance outcomes changes depending on the length and location of the throw-in.
The results section could benefit from a brief discussion of the limitations of the statistical analysis. For example, are there any potential confounding variables that were not accounted for?
Rationale: Acknowledging the limitations of the analysis would strengthen the research by demonstrating awareness of potential biases or limitations in the interpretation of the results.
Implementation: Add a brief paragraph discussing any potential limitations of the statistical analysis, such as the possibility of confounding variables or the assumptions of the statistical tests.
Table 3 presents a descriptive analysis of throw-in strategies in the 2018-2019 English Premier League season, categorized by length, direction, and pitch location. It shows the number and percentage of throws for each category, as well as the success rates for first contact and possession retention (for at least 7 seconds). This table allows for comparison of different throw-in strategies and their effectiveness.
Text: "Table 3. Descriptive analysis of throw-in strategy (n = 16,154), first contact success (n = 13,376) and possession retained (n = 8847) in relation to throw-in length, direction, and pitch location."
Context: Results section
Relevance: This table is highly relevant as it provides a detailed breakdown of the core data analyzed in the study. It directly addresses the research questions about the effectiveness of different throw-in strategies based on length, direction, and pitch location. By presenting both raw numbers and percentages, it offers a comprehensive overview of the observed patterns.
Figure 2 displays the correlations between a team's final league position and four throw-in performance metrics: first contact success, 7-second possession retention, mean time in possession, and shots resulting from throw-ins. Each metric is presented as a separate scatter plot (a-d), with league position (rank) on the x-axis and the performance metric (rank) on the y-axis. The figure aims to visually represent the relationships between league standing and throw-in effectiveness.
Text: "Figure 2. Correlations between final league position and first contact success (a), possession retention for 7s (b), mean time in possession from the throw-in (c), and (d) throw-ins resulting in a shot from the possession achieved after a successful first contact."
Context: Results section
Relevance: This figure is crucial for understanding the relationship between throw-in performance and overall team success. It visually represents the correlations between league position and key throw-in metrics, providing a direct answer to one of the study's primary research questions. The scatter plots allow for a quick assessment of the strength and direction of these relationships.
Figure 3 illustrates the correlations between a team's final league position and the percentage of throw-ins they perform in each direction (backwards, forwards, and lateral). Each subplot shows a scatter plot with the team's final league position (rank) on the x-axis and the percentage of throw-ins in a specific direction on the y-axis. A negative correlation suggests that higher-ranked teams tend to perform more backward throws, while a positive correlation suggests lower-ranked teams favor forward throws.
Text: "Figure 3. Correlations between final league position and percentage of throw-ins performed in the backwards (a), forwards (b) and lateral (c) direction."
Context:
Relevance: This figure is relevant because it visually represents the relationship between throw-in direction strategy and league standing. It helps to understand whether certain throw-in directional preferences are associated with better or worse overall team performance.
Figure 4 presents the first contact success rate for throw-ins, broken down by pitch location, throw-in direction, and throw-in length. It uses a diagram of half a soccer pitch, divided into attacking and defensive halves. Different colored arrows represent the direction and length of the throw-in, and the percentages next to the arrows show the success rate of the first contact. The numbers in parentheses represent the absolute number of successful first contacts. This figure helps visualize how the combination of location, direction, and length influences the success of the first contact.
Text: "Figure 4. First contact success rate (percentage and absolute values) based on pitch location, throw-in direction and throw-in length."
Context:
Relevance: This figure is highly relevant as it visually demonstrates the effectiveness of different throw-in strategies in terms of first contact success. It allows for a direct comparison of success rates across different combinations of location, direction, and length, providing key insights into optimal throw-in strategies.
Figure 5 illustrates the success rate of retaining possession after a throw-in, categorized by pitch location (rest of attacking half, rest of defensive half), throw-in direction (backwards, lateral, forwards), and throw-in length (short, medium, long). The figure uses a simplified representation of half a soccer field, with percentages indicating the possession retention success rate for each combination of factors. Absolute values (number of successful possessions retained) are shown in parentheses, and mean time in possession (for possessions lasting at least 7 seconds) is provided at the bottom of some columns. This figure helps visualize the effectiveness of different throw-in strategies in maintaining possession.
Text: "see Figure 5"
Context: The three-way repeated measure ANOVA showed an interaction for direction * length * location for possession retention F(2.647, 50.292) = 4.02, p < 0.05, gp2 = .175 (see Figure 5).
Relevance: Figure 5 is highly relevant as it directly addresses the research question about the impact of throw-in strategy on possession retention. It visually presents the complex interplay between throw-in location, direction, and length, allowing for a clear comparison of their effectiveness in maintaining possession. This information is crucial for understanding how different throw-in strategies contribute to team performance.
This discussion section interprets the study's findings on how throw-in strategies relate to soccer performance in the 2018-2019 English Premier League. The study found that higher-ranked teams had better throw-in performance (first contact success, possession retention, and shot creation). Backward and lateral throw-ins proved more effective than forward throws, challenging traditional coaching practices. The discussion explores why backward and lateral throw-ins might be advantageous, suggesting they allow more time and space for building attacks, while forward throws often lead to contested situations and turnovers. The findings highlight the importance of strategic throw-ins for gaining and maintaining possession, creating scoring opportunities, and potentially influencing match outcomes. The discussion also acknowledges the need for further research to confirm these findings and explore the tactical implications in more detail.
The discussion effectively summarizes the main findings of the study, highlighting the relationship between throw-in performance and league position, as well as the effectiveness of different throw-in directions. This provides a concise overview of the key takeaways.
The discussion provides plausible explanations for why backward and lateral throw-ins might be more effective than forward throws. The reasoning about reduced pressure and increased time and space for building attacks is consistent with the findings and adds depth to the analysis.
The discussion highlights the practical implications of the findings for coaches, suggesting that they should reconsider traditional throw-in strategies and explore the potential benefits of backward and lateral throws. This makes the research relevant for practitioners and encourages the adoption of evidence-based coaching methods.
While the discussion mentions the tactical implications, it could delve deeper into how specific team formations or playing styles might interact with different throw-in strategies. For example, how might a high-pressing team utilize backward throws differently compared to a team that plays a more defensive style?
Rationale: A more detailed exploration of tactical implications would enhance the practical value of the research and provide more specific guidance for coaches.
Implementation: Provide examples of how different teams could integrate the findings into their tactical approaches, considering various playing styles and game situations.
The discussion acknowledges the limitation of using data from a single season, but it could also address the potential limitations of focusing on a single league (the EPL). Do the findings generalize to other leagues with different playing styles or levels of competition?
Rationale: Addressing the potential limitations of using EPL data would strengthen the research by acknowledging the context-specific nature of the findings and encouraging further research in other leagues.
Implementation: Add a sentence or two discussing the potential limitations of using EPL data and the need for research in other leagues to assess the generalizability of the findings.
While the discussion links throw-in performance to league position, it could further quantify the impact of different throw-in strategies on match outcomes (e.g., wins, losses, draws). For example, how much does a team's likelihood of winning increase if they effectively utilize backward throws?
Rationale: Quantifying the impact on match outcomes would strengthen the argument for the importance of throw-in strategy and provide a more direct measure of its influence on team success.
Implementation: Conduct further analysis to determine the relationship between throw-in strategies and match outcomes, and report these findings in the discussion.
This conclusion summarizes the study's findings on the relationship between throw-in success and soccer team performance. The research suggests a link between how teams perform on throw-ins and their final league standing. Specifically, throwing the ball laterally or backward, rather than forward, is associated with greater success in various aspects of throw-in plays, such as first contact success, possession retention, and shot creation. Higher-ranked teams tend to utilize this backward/lateral strategy more often. The authors suggest that coaches should re-evaluate their throw-in strategies to potentially improve team performance.
The conclusion effectively summarizes the main findings of the study in a clear and concise manner, highlighting the link between throw-in success and league performance, as well as the effectiveness of lateral and backward throws.
The conclusion clearly states the implications of the findings for coaches, encouraging them to re-evaluate their throw-in strategies and consider incorporating lateral and backward throws.
The conclusion reinforces the importance of the study by highlighting the potential impact of the findings on coaching practices and team performance, emphasizing the contribution of the research to a relatively understudied area.
While the conclusion mentions the potential for improved team performance, it would be stronger if it provided some quantification of this impact. For example, could the authors estimate how many additional points a team might gain over a season by optimizing their throw-in strategy?
Rationale: Quantifying the potential impact would make the conclusion more compelling and provide a more concrete incentive for coaches to adopt the recommended strategies.
Implementation: Based on the observed differences in throw-in success rates and their correlation with league position, attempt to estimate the potential impact on points gained or league standing.
The conclusion could be strengthened by explicitly restating the initial research question and summarizing how the findings directly address it. This would create a stronger sense of closure and reinforce the study's contribution.
Rationale: Connecting back to the research question would enhance the clarity and coherence of the conclusion, ensuring that the study's main objective is clearly addressed.
Implementation: Begin the conclusion by briefly restating the research question (e.g., "This study aimed to investigate the relationship between throw-in strategies and team performance...") and then summarize how the findings answer this question.
While the paper includes a separate section for future research, briefly mentioning one or two specific areas for future investigation in the conclusion could stimulate further interest and provide a more direct call to action.
Rationale: Suggesting specific research directions in the conclusion would encourage other researchers to build upon the study's findings and contribute to a deeper understanding of throw-in strategies.
Implementation: Include a brief sentence or two at the end of the conclusion suggesting specific areas for future research, such as investigating the impact of throw-in strategies in different leagues or exploring the tactical interplay between throw-ins and other set pieces.