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What are football insights?
Football insights are the meaningful takeaways from analysing and interpreting various types of football data. These insights go beyond basic statistics by explaining their significance and how they can influence future decisions or actions. In simple terms, an insight turns data into understanding. For example, it helps coaches identify why their team isn’t creating enough chances, allows scouts to spot undervalued players, or helps clubs better understand their fans.
Sources of football data for insights
To generate meaningful football insights, you need access to various types of data. These sources capture different aspects of the game, from what happens on the field to off-field operations:
– Event data: This is the core data from a match, capturing actions like passes (completed, incomplete, type, location), shots (on target, off target, blocked), tackles, interceptions, fouls, offsides, clearances, saves, and goals. This data is collected by analysts or automated tracking systems.
– Positional data (tracking data): Collected through GPS trackers on players or cameras in the stadium, this data tracks the positions of players and the ball, helping to analyse distances covered, speed, team shape, defensive lines, and spatial relationships.
– Physical and physiological data: This includes data from wearable devices (heart rate, sleep patterns, recovery metrics) and training sessions (strength, conditioning). It helps assess player fitness, fatigue, and injury risks.
– Scouting and recruitment data: This includes both qualitative evaluations from scouts (e.g., personality, coachability) and quantitative data (performance, market value, contract details) to assess potential recruits.
– Medical data: Detailed records of player injuries, recovery times, and medical histories, helping manage player health and availability.
– Training data: Data from training sessions, including drills and tactical exercises, captured using similar technologies to those used during matches. It helps track player progress and monitor tactical development.
– Financial and commercial data: This includes data from ticket sales, merchandise, sponsorships, social media engagement, website traffic, and fan demographics. It helps clubs understand their business performance and fan base.
– Publicly available data: Basic data such as league tables, historical match results, fixture lists, and news articles, which can provide context and highlight trends.
From raw data to actionable insights: The process
Turning raw football data into useful insights is a step-by-step process that needs a mix of technical skills, analysis, and deep knowledge of the sport. Here are the key steps involved:
– Data collection and extraction: The first step is gathering data from different sources, such as event data from tracking systems, physiological data from wearables, public match results, or scouting databases. This often involves handling different data formats and systems.
– Data cleaning and pre-processing: Raw data is rarely perfect. In this step, errors, inconsistencies, duplicates, and missing values are present. Data might need to be standardised (e.g., making player names consistent), summarised (e.g., adding up individual actions to get team totals), or transformed into a useful format. This step is important because “garbage in, garbage out” applies to analytics.
– Data integration: Data from different sources (e.g., event data and tracking data) must be linked together to create a full dataset. This enables deeper analysis, giving a complete view of performance and other factors.
– Analysis and modelling: This is where data starts to show patterns and connections. Analysts use various techniques:
– Descriptive statistics: Summarising data, like average possession or total shots.
– Inferential statistics: Drawing conclusions about a team based on sample data, like whether a team’s expected goals (xG) are higher than their actual goals due to poor finishing.
– Machine learning: Creating models to predict things like injury risk, player market value, or match outcomes.
– Tactical analysis: Using tools like heatmaps or passing networks to understand team setup, player movements, and tactics.
– Interpretation and contextualisation: Numbers alone don’t provide insights. This step involves interpreting the data in the context of the game, the opponent, the player’s role, and the team’s strategy. Analysts ask: What does this data really mean for performance? Why is this happening?
– Visualisation: Complex data is often easier to understand with visual tools like charts, graphs, and heatmaps. These make insights clear to coaches, players, and others who may not be experts in statistics.
– Communication and actionable recommendations: Finally, insights need to be clearly communicated to people, with practical suggestions for action. This could mean recommending tactical changes based on findings, like, “Onana struggles under pressure, consider changing the strategy,” or “United set-piece defence is weak, work on that area.”
Key areas where football insights provide value
Football insights, derived from detailed data analysis, improve decision-making in various aspects of the game.
– Player performance and development: Insights measure more than just goals and assists, evaluating factors like passing accuracy, defensive duels, and off-ball movement. This helps coaches create tailored training plans. An example is a winger with great dribbling but poor crossing might receive focused training to improve crossing accuracy.
– Tactical analysis and match preparation: Insights reveal a team’s strengths, weaknesses, and tactical patterns, including opponent weaknesses and team formation effectiveness. An example is discovering that an opponent frequently concedes from crosses informs attacking and defensive strategies.
– Scouting and recruitment: Data-based scouting helps clubs identify undervalued talent, assess a player’s adaptability, and compare potential signings objectively, reducing bias.For instance, a midfielder’s “expected assists” and “defensive actions” may highlight their importance for a tactical style, even if traditional stats overlook them.
– Injury prevention and sports science: Combining physical data with training and injury history helps predict injury risks, allowing better training management.
– Fan engagement and commercial operations: Insights help clubs understand fans’ preferences, improving marketing, ticket sales, and merchandise.
Who uses football insights? (Stakeholders)
Football insights are valuable to many people across the sport. These insights help everyone, from those making decisions on the pitch to those handling business strategy, as well as the fans. Key stakeholders include:
– Coaching staff: Head coaches, assistant coaches, and specialised coaches (like set-piece or attacking coaches) use insights to understand opponent weaknesses, improve their own team’s tactics, prepare for matches, and review past performances.
– Performance analysts: These professionals collect, process, and analyse data. They present insights to coaching staff and players, often using video analysis and statistics to provide clear, actionable findings.
– Players: Individual players use insights to understand their strengths and weaknesses, review specific game situations, and adjust their play based on tactical plans or how their opponents play. This can include personalised video clips with data.
– Scouting and recruitment departments: Sporting directors, scouts, and recruitment analysts rely on insights to identify and evaluate potential transfer targets. They use data to reduce risk and find players that fit the team’s needs and budget.
– Sports science and medical teams: Doctors, physiotherapists, and strength coaches use physiological and performance data to track player health, manage fatigue, predict injury risks, and optimise recovery plans.
– Club management and board members: Executives use performance data, player values, and market trends to make long-term decisions about club strategy, finances, and investments in players or infrastructure.
– Commercial and marketing departments: These teams use fan data to develop targeted campaigns, improve merchandise sales, enhance ticketing strategies, and offer a better fan experience.
– Media and broadcasters: Sports journalists and broadcasters use football insights to enrich their commentary, offer deeper statistical analysis during broadcasts, and create content that helps fans understand the game better.
– Gambling and fantasy sports operators: These companies use insights to set odds, manage risk, and provide real-time updates for fantasy leagues or betting.
– Fans: While fans don’t create insights, many enjoy using them to deepen their understanding and enjoyment of the sport. Media outlets, independent analysts, and club channels provide these insights to fans.
The impact of advanced analytics on football insights
Advanced analytics has transformed football by moving beyond basic stats and subjective views, driven by key factors:
– From descriptive to predictive and prescriptive: Traditional analytics describes past events (e.g., total shots, possession), while advanced analytics predicts future outcomes (e.g., injury risks, expected goals) and offers actionable advice (e.g., tactical changes).
– Deeper understanding of performance: Metrics like Expected Goals (xG), Expected Assists (xA), and Expected Goals on Target (xGoT) evaluate the quality of chances, not just quantity. Tracking data provides insights into player movement, pressing intensity, and team formation, revealing tactical details not visible from event data alone.
– Objective player evaluation: Advanced analytics removes bias by assessing how players perform against different teams and in various roles. Algorithms can highlight players who outperform or underperform relative to their stats, helping to identify hidden talents and assess how players fit into new teams.
– Personalised player development: Combining physical, technical, and tactical data enables customised development plans, allowing coaches to track progress and tailor training to specific needs.
– Enhanced tactical understanding: Advanced models analyse pressing, build-up play, defensive transitions, and set-pieces in more detail, helping coaches refine tactics and study opponents more effectively.
– Integration of diverse data sources: Advanced platforms combine data from tracking systems, GPS wearables, medical data, video analysis, and social media to offer a comprehensive view and multi-layered insights.
– AI and machine learning applications: AI and machine learning uncover hidden patterns and complex relationships, generating insights from large datasets faster and more accurately than manual analysis.
Challenges in generating and applying football insights
While football insights have great potential, there are challenges in creating and using them effectively. Overcoming these obstacles is key for clubs to fully benefit from data:
– Raw football data can be inaccurate, incomplete, or inconsistent, with different data providers defining events differently and errors occurring in human tagging or automated systems, leading to poor data quality and misleading insights.
– Numbers alone don’t always tell the full story. For example, a player’s high passing accuracy might result from making safe passes, or a low expected goals (xG) could reflect a tactical decision to take long-range shots. Without considering the context, insights can become irrelevant or misleading.
– Combining data from various systems, like event data, tracking data, medical records, and financial data, into one format is complex. Different formats, unique identifiers, and real-time syncing issues can cause important connections between data to be missed.
– Some coaches, scouts, and players may resist using data, preferring their experience and intuition (“the eye test“). Without buy-in from key factors, insights are useless, requiring good communication and education to encourage adoption.
– There is a shortage of people with both advanced data skills (such as statistics and programming) and football knowledge, which limits the ability to turn complex analysis into actionable decisions on the pitch.
– Some teams may rely too heavily on data and overlook the importance of instinct, improvisation, and the unpredictable nature of football. Overemphasis on data can lead to inaction, reducing creativity, slowing decisions, and diminishing intuition.
– Many clubs keep their analytical models and insights secret to maintain a competitive edge, which prevents shared learning and innovation. This leads to isolated progress, hindering industry-wide development.
Sportmonks’ football insights
Sportmonks provides a football API that delivers raw data and advanced analytics, enabling developers, analysts, and businesses to generate actionable football insights. Covering over 2,500 leagues, our API offers live scores, detailed statistics (e.g., passes, shots, tackles), and fixtures, collected from global scouts and data partners via our Scout Application Platform (SSAP). The SSAP standardises and validates data, ensuring consistency for reliable analysis.
Key features include the Predictions API, which uses machine learning to forecast match outcomes (e.g., match-winner, total goals) based on historical data, team form, and player contributions, available 21 days pre-match. Expected Goals (xG) metrics, including xG On Target (xGOT), quantify scoring chance quality, supporting post-match and live analysis (advanced plans). These insights power applications like livescore portals, betting platforms, and fantasy games, aiding stakeholders such as media, gambling operators, and fans in understanding performance and trends.
Turn football data into powerful insights
Football insights can shape tactics, enhance player performance, and drive smarter decision-making across the sport. With Sportmonks football API, you get access to detailed match data, advanced metrics like Expected Goals (xG), real-time match predictions, and comprehensive statistics from over 2,500 leagues globally.
Whether you’re building a tactical analysis tool, a fantasy football app, or conducting deep performance analysis, Sportmonks provides consistent, high-quality data to fuel your football insights.
Start your free trial today and leverage the full power of football analytics.
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