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Sports Analytics: What It Is And Why It Matters


Sports analytics encompasses the technologies and skills used to deliver business insights from operational data.

Through modelling, optimization, predictive analytics and business intelligence, sports clubs and leagues can gain insights to strengthen marketing performance, deepen fan-centric relationships and improve the way they engage customers to maximize their experience.

One of the key benefits of iQ-Sports™ is that it standardized the process for storing source data as well as creating reports and analytic models to make critical information available to business users.

Sports organizations suffer from a lack of fan engagement, marketing campaigns are often too generic, and the data available for campaigns is frequently inconsistent and plain wrong.

A sports marketing solution should be affordable, scalable, adaptable, and capable of targeting quests in all possible ways.

Figure 1. IQ-Sports™ Overview


Advanced analytics from IQ-Sports™ can deliver crucial insights to propel growth and success by:

• Real-time alerts for VIP behaviour offer a competitive advantage
• Creating a fan-centric 365° view
• Delivers a total fan view to better understand customers
• Targets the right marketing campaigns to the most strategic customers
• Improve operating results and marketing performance
• Live, interactive and intuitive dashboards with guaranteed data consistency


• Provide simple and fast data consolidation
• Quickly deployed and scaled to provide quick and easy access to data through a robust platform that evaluates and modifies marketing strategies
• Stored procedures generate a single report to reveal underutilized data and ways to capitalize on the information
• Helps identify patron trends in real-time
• Integrates with other leading software and systems in the Sports and Entertainment industry with its multivendor architecture
• Establishes a centralized data source to help our customers better manage the overall effectiveness of their teams
• Predicts fan behaviour through statistical models in real-time

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