The global sports analytics market is on track to reach $3.4 billion by 2028, underscoring the increasing importance of data in the sports sector. Stemming from the in-depth analysis of metrics related to teams and athletes, sports analytics has transformed the industry, influencing professionals across various fields, from traditional sports to fantasy leagues and online sports betting. This trend is evident in how teams have adopted analytics for strategic planning, player development, and injury management in basketball.
Yordan Dimitrov, a BI Developer at B EYE, contributes to this evolving field with his practical experience as a player in the NASL Amateur Basketball League with the LA Bakers. His dual role provides a unique perspective on applying analytics in basketball. Here, Yordan discusses the influence of data analytics at both the amateur and professional levels of the game, offering insights into its current and future impact.
Get to Know Yordan: Tableau Consultant in B EYE
In your experience, how have advanced analytics changed the way basketball teams approach game strategy and player development?
Advanced analytics have a massive impact on developing winning strategies, forecasting and preventing player injuries, and scouting potential players. They enable teams to understand their strongest and weakest areas.
For example, every coach wants to know where his team scores the most and, respectively – the least. That highlights the areas for improvement and where to focus on offense. The same can also apply to defense, where advanced analytics can help understand where the defense is lacking and let the most points be scored.
They can also help track player loads, training, nutrition plans, and weight. Nobody wants an injury, and strictly tracking all these aspects is important when players must constantly travel and play at a high level.
Let’s not forget the scouting aspect – advanced analytics help you understand a lot about the player, using his stats (points, rebounds, assists, FG%, FT%, 3PT %, steals, blocks), before you even go to see him play.
In a well-designed platform, you can then attach your comments to an already created stats overview, which forms a detailed picture of players’ abilities to make plays, involve the team, play defense, and contribute to the game overall.
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Can you discuss the balance between traditional scouting and analytics in identifying promising talent in basketball? How has this balance evolved in recent years?
Technology and traditional scouting are not mutually exclusive. They can complement each other and provide different perspectives and insights. You can use technology to collect, analyze, and visualize data, but you also need human judgment, context, and feedback to interpret and apply it. You can use traditional scouting to observe, evaluate, and communicate with players, but you also need data and technology to support and validate your opinions. I’d say in recent years, advanced analytics have reduced the time required for scouters to prepare for a potential scouting event, and they already have a good picture of what the respective player is good at and what they are lacking.
Balancing technology and traditional scouting in sports analytics is not a solo endeavor. It is a team effort that requires effective communication and collaboration. You need to share your data and insights with your colleagues, coaches, players, and other stakeholders and listen to their input and feedback. You need to explain your methods and findings in a clear, concise, and compelling way, using stories, visuals, and examples.
Injury prevention is crucial in sports. How are analytics being utilized to predict and prevent injuries in basketball, and what improvements would you like to see in this area?
One of the most important technologies used in injury prevention in the NBA is wearable sensors. These small devices can be attached to a player’s body and can track a variety of metrics, including heart rate, movement, and exertion levels. By monitoring these metrics, teams can identify when a player is at risk of injury and take steps to prevent it. For example, if a player’s heart rate or exertion levels are abnormally high, it may indicate that they are at risk of overexertion and are more likely to sustain an injury.
Motion capture is another technology used in injury prevention. This technology employs cameras to track a player’s movements and can determine when a player is at risk of injury based on their movement patterns.
The improvements I would like to see in this area are advanced analytics on the stretch pattern required if a player has an overload in a specific area. Proper targeted stretching and plyometric exercises can help significantly strengthen the area and get it used to a variable load.
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With the growing trend of data-driven decision-making, what are the key metrics or data points that teams and coaches should focus on to gain a competitive edge?
Key metrics for individual players include: Points, Assists, 3-Pointers Made, Rebounds (Offensive/Defensive), Blocks, Steals, FTA (free-throws attempted), FG%.
For teams, important statistics include: Points, Rebounds (Offensive / Defensive), FG%, Opponent Points, Opponent Rebounds, Opponent Field Goal %, Points Differential, Rebounds Differential, Field Goal % Differential.
Technology plays a significant role in sports analytics. Can you share insights into how emerging technologies like AI and machine learning are influencing basketball analytics?
One of the most exciting prospects for AI in basketball is the player performance enhancement. AI systems equipped with advanced sensors and machine learning algorithms can track players’ movements and analyze their performance in real-time.
AI can also be used to simulate game scenarios and predict outcomes. This can help teams experiment with different schemas, offensive / defensive plans, and different lineups.
What’s more, they can also consider variables such as opponents’ tactics and lineup, players fatigue, players shooting efficiency.
How do you see the integration of analytics platforms like Qlik and Tableau transforming the decision-making processes in basketball teams at various levels?
Analytics platforms like Qlik and Tableau are transforming decision-making in basketball by providing deep insights into performance metrics and enabling quick, data-driven decisions. At B EYE, we use these tools to deliver tailored analytics solutions, integrating comprehensive data sources that can optimize strategies and enhance performance. This approach ensures teams make informed decisions, maximizing their potential on and off the court.
For CEOs and executives considering investing in sports analytics, what would be your advice on the key factors to consider for effective implementation and ROI?
As with everything related to analytics, data collection, data source preservation, and integrity need to be considered first. They need to be able to analyze the potential size of data, relationships between data, who will monitor and maintain this data, meaning how much human resources they will need to maintain such an environment, and of course – KPIs. Depending on the complexity of the front-end visualizations and what the ERP data source (Data Warehouse/ Data Lake) would be, they can make the decision about the front-end tool.
Considering the advancements in sports analytics, where do you see the future of basketball analytics heading in the next five years?
I believe more professional organizations will seek utilizing sports analytics to enhance the performance of their teams. I doubt they will invest in building a big data BI (Business Intelligence) team, which means they will probably look to outsource to various consultancy companies. I predict that in the near 5 years, basketball analytics will have spread across Euro League as well, as currently it is predominantly used in the NBA. I see also a more detailed expansion on the functionalities provided with analytics — wearable sensors and motion AI can start improving player movement, shooting form, jumping technique, etc. I think it will also play a big role in the diet planning for separate athletes and help build the most optimal nutrition plan for their required physique, dictated by the position they play in.
How does the approach to analytics differ between amateur and professional basketball leagues, and what can these leagues learn from each other?
Main thing here would probably be scalability and affordability. Having an advanced analytics system implemented requires a lot of resources and a group of backend / frontend developers to implement it.
I reckon most amateur leagues can’t afford to have such a system in place and are not fully aware of how to use it.
How do you see the role of analytics evolving in other sports, similar to basketball?
The more it gets implemented and teams realize the potential and added gains, the more they will seek such solutions. Every sport can benefit from such a system. And the benefit is – one tool can analyze multiple sports. The concept will be similar, but the KPI’s different.
The sports analytics field is evolving at a high pace, and its influence in shaping the future of sports like basketball cannot be overstated. From optimizing player performance to enhancing fan engagement and operational efficiency, the power of data-driven decision-making is reshaping the landscape of sports.
At B EYE, we leverage cutting-edge analytics platforms like Qlik, Power BI, Tableau, and Snowflake Data Cloud to transform sports organizations into data-driven powerhouses. Our custom solutions are designed to meet the unique needs of each organization, ensuring that every strategy is backed by robust, actionable data. If you’re embarking on a sports analytics project and seek to elevate your organization with data-centric solutions, have a chat with our experts. Let’s discuss how our innovative approach can help you achieve superior results and gain a competitive edge in the dynamic world of sports.
