Watching sports should be more than just seeing the action—it should be an immersive, interactive, and enriched experience. Whether it’s tracking player movements, revisiting key match events or analyzing team strategies – data plays a crucial role in transforming passive watching into an engaging experience and studies support this. 

But what makes sports data truly valuable? And what happens when data is incomplete, inconsistent, or structured differently across providers? In this post—the first in our Data in Sports blog series—we explore the problems with third-party data, how we categorize sports data, why structuring it is crucial and how we overcome integration challenges to enhance fan experiences. 

The problem with third-party data 

Third-party data, while essential, often presents hurdles: incomplete or inconsistent data, lack of standardization and events not captured or incorrectly timestamped. Overcoming these limitations demands creativity, effective communication, and sometimes even stepping beyond traditional boundaries. 

Example 1: Volleyball highlights and complex data points 

Automating volleyball highlights appeared simple at first glance. Our idea for one of the things to show in highlights: identify interesting rallies by measuring their duration. A rally lasting more than 30 seconds seemed inherently exciting and worthy of inclusion. 

However, challenges quickly emerged. The third-party data we relied upon had inaccuracies in marking the exact moment a serve occurred, making it difficult to precisely determine rally lengths. Our response was straightforward—we communicated directly with the data provider, clearly explaining our challenge and the impact precise timing had on our product. They adjusted their scouting approach accordingly, improving serve-point accuracy. This proactive collaboration not only enhanced our product but raised overall data quality standards, benefiting both sides and the industry as a whole. 

Example 2: Tennis and the Challenge of Data Synchronization 

In sports streaming, synchronization between data and video is critical—especially in fast-paced games like tennis. Even a slight mismatch can disrupt the experience. 

Imagine watching a high-stakes match. You’re fully engaged, anticipating every serve and rally. But if the match data updates before the video feed, the score changes on screen before you see the point played. The excitement vanishes—you already know the outcome. 

This happens because live data and video streams don’t always travel at the same speed. Transmission delays, network latency, and processing times can cause the video to lag behind the incoming data—even by a few seconds, which is enough to ruin the experience. 

At NativeWaves, we solve this with RealTimeOffset, dynamically adjusting data updates so they stay in sync with video, ensuring a seamless, spoiler-free experience. 

Example 3: Football’s invisible moments 

Football presents its own unique challenges. Many compelling, visually exciting moments aren’t clearly captured or adequately reflected in standard data streams. 

For example, imagine a defender dramatically clearing the ball off the goal line at the last second—preventing a certain goal. Though visually thrilling, standard event data usually ignores these goal-line clearances, treating them as insignificant or simply omitting them entirely. 

Similarly, consider a gripping 2-on-1 counterattack where an attacker sends a precise pass toward a teammate, creating what seems like a certain goal-scoring opportunity. However, a defender intercepts at the critical moment, turning the action into a memorable defensive play. Standard third-party data typically labels this merely as an “intercepted pass,” completely missing the action’s significance. 

These examples highlight an industry-wide challenge: how do we automatically capture and highlight such nuanced yet exciting moments effectively using third-party data alone? Currently, no standard solution exists, leaving plenty of room for innovation and creative thinking. 

These challenges highlight the complexity of working with third-party sports data. Whether it’s synchronizing real-time updates, interpreting incomplete event feeds, or capturing nuanced game moments, structuring data effectively is key. 

To tackle these issues, we categorize sports data into four distinct layers, each serving a different purpose in delivering an enriched fan experience. 

The Four Layers of Sports Data 

When integrating third-party data into a sports experience, it’s not just about retrieving numbers—it’s about structuring them meaningfully. We break down sports data into four core categories: 

1. Basic Data 

This includes foundational match information, such as: 

• Which teams are playing 

• Score updates 

• Match status (live, halftime, full-time) 

• Player formations 

Most sports data providers cover this level of detail, making it relatively easy to integrate. However, even at this level, data structures can vary—for example, one provider might have a dedicated “standings” endpoint, while another distributes team ranking data across multiple sources. 

2. Advanced Data 

This category involves richer, more analytical insights, such as: 

• Player performance metrics (expected goals/xG, pass accuracy, heat maps) 

• Team rankings and in-depth statistics 

• Tactical formations and game momentum 

Not all data providers offer these insights in the same way. For example, one may include expected goals (xG) by default, while another provider may not track this metric at all. This inconsistency means we must find creative ways to standardize and enhance missing data. 

3. Real-Time Layer of Data 

The most dynamic, time-sensitive layer: 

• Current live scores and instantaneous updates 

• Live positional data and player movements 

• Instantaneous statistics (ball speed, player heart rate, racing car speed) 

• Real-time event prediction (penalties, overtaking in racing) 

Live data must be accurate and synchronized precisely with video, as even minor discrepancies can ruin the experience. 

4. Replay & Event Data 

This is the most complex layer, focusing on real-time event markers and highlight-worthy moments, such as: 

• Goals, red cards, and penalty events 

• Significant game-changing plays (e.g., last-minute goal-line clearances) 

• Replay triggers for key moments 

However, not every provider captures events in the same format. One, for instance, provides detailed event markers, including reasons behind VAR decisions (e.g., an offside linked to a disallowed goal). Other providers, may offer a more fragmented event feed, requiring us to backtrack and reconstruct key moments manually. 

The Challenge: Integrating Different Data Sources Seamlessly 

One of the biggest hurdles in creating a seamless sports experience is the fact that no single data provider has everything we need. Integrating multiple providers means dealing with inconsistent structures, missing data points, and varying data accuracy. 

How We Handle This Challenge at NativeWaves 

Dynamic Data Mapping: Since different providers structure their APIs uniquely, we’ve built a flexible mapping system that can integrate multiple providers and even static sources like team colors, flags and emblems or unrelated 3rd party sources like weather conditions. 

Handling Missing Data: If a specific provider lacks a key metric, we either estimate it using other available data or display a placeholder message (e.g., “Data not yet available” for early-season statistics). 

Caching & Backend Optimization: To improve efficiency and reduce costs, we offload data processing to the backend, allowing us to cache results and prevent excessive API calls. Instead of querying all endpoints every second for millions of users, we fetch only what has changed. 

Synchronizing Data with Real-Time Streams: In live sports streaming, data doesn’t always arrive at the same time as the broadcast. A match might have a 5-second transmission delay, while some stats update in real-time and others lag behind. To solve this, we developed a RealTimeOffset system that ensures event markers align accurately with the video stream. 

Looking Ahead: The Future of Sports Data Integration 

At NativeWaves, we believe that sports fans want more insights, deeper engagement, and smoother experiences. This means continuing to refine how we present data, ensuring that even complex, multi-provider integrations feel seamless to the user. 

This is just the first post in our Data in Sports series. Next, we’ll explore the technical challenges of handling data licensing, latency issues, and how we manage absent data—diving deeper into the complexities of sports data infrastructure. 

If you’re passionate about data-driven sports innovation, stay tuned—there’s much more to come.