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GRID: Securing the holy grail of sports data collection

GRID: Securing the holy grail of sports data collection


Sports data and its accompanying analytics market has boomed over the past decade. The tangential sports industry has produced multiple billion-dollar companies in the wake of data and engagement.

In the current era of sport, fans expect to see live scores and statistics uploaded to mobile phones seconds after the action takes place. The consumption of statistics has become ubiquitous. It is an aspect of daily life to provide tinder to fiery discussions over who is the greatest, and wisdom to wagers proving once and for all the one was right about the underdog.

Disclaimer: This piece was written by GRID for The Esports Journal

Photo Credit: GRID

This consumption of player and team statistics brought forth the rise of both sports betting and fantasy sports. Business verticals arose from sports statistics and birthed the need for faster and more accurate data, revealing the data collection holy grail: an instantaneous, error-free scorekeeping system. While this is still the goal of many sports companies, esports and GRID have accomplished this feat through the digital nature of the competitions in which they specialise.

What eventually became modern stat keeping formed decades ago. The 1930s introduced Pinsetter boys who worked the bowling alleys and manually set up pins while keeping score for patrons. Earlier still, 1870 brought Henry Chadwick and the first tradition of manual baseball scorekeeping. The years following slightly modified the process, but it is still in practice today.

In 1947, the “Magic Eye” photo finish device came to the Olympics. Athletes stood around for minutes after an Olympic race waiting for the film to develop to crown a winner. While primitive by current standards, it was the first step towards including technology into the scoring of a sporting event. This inclusion of technology spurred the adoption of pressure plates and finally by laser finish lines that can be accurate to the nearest hundredth of a second.

Traditional sports, up until the past five years, have stayed true to the art of manual data collection. Often a scorekeeper in a press box or at a scorer’s table sits with a digital tablet trying to keep pace with the action at hand. In 2014, Zebra Technologies and the NFL began placing RFID chips in the shoulder pads of players to automate the player tracking process, SportVU came to the NBA, and goal-line technology has been added to FIFA. It’s a massive breakthrough for traditional sports, but still requires a manual scorekeeper to enter in the final result of the action.

The equation for successful data collection is simple and straightforward. Faster statistics lead to better products, better products lead to accurate predictions, and with it, more informed fans. Each decade comes with breakthroughs, and each giant step forward creates additional technological hurdles. That is until you consider esports.  

Chris King, CTO of GRID. Image credit: GRID Esports

GRID Esports is a Berlin-based esports data platform that has already mastered the art of producing true real-time data for consumption by a wide variety of customers, from mobile applications to traditional sportsbooks. “Thousands of data points flow through our system every second for a single esports match.” explained Chris King, CTO of GRID. “The group here has worked in traditional sports for many years. It was the dream to be able to pull these statistics from a sports match, but with human constraints, it just wasn’t possible.”

GRID technology sits on a server level for each of the partners they service. Data is delivered in milliseconds from the press of a button and into the GRID API. This allows GRID to service its customers with data that pairs simultaneously with the action, even if you are sitting at the venue and watching live. When comparing a GRID API feed to an undelayed video, it flows in perfect lockstep.

GRID products built on this data look like the final culmination of what tracking devices for sports will eventually be able to produce. Artificial intelligence and machine learning are employed to apply a flashy prediction graphic. A series of players move around an environment without a hitch. The top-down view gives a visual representation of what is happening in the background: direct, ongoing communication of GRID technology and the partner’s server.

In Counter-Strike: Global Offensive, for example, you can see the loadout and current economy of each player if they pick up a different weapon, and exactly when and where the last frag came from. In Dota 2, you can see the player’s items and spells along with their current XP. All the while, a lightning-fast feed of the game events flows through written out in plain English.

Esports data was not always this clean. In the early days of esports data, information – much like in traditional sports – was collected manually off of a stream for a live broadcast. Some companies and fans use Optical Character Recognition or “OCR” to lay a capture device over a broadcast and try to pull the data. King explains this was common practice for many years, but the issue is that the data becomes unstable over time. Players can change tags, screen resolution can be altered, and labels in the game may be different. All of these factors can lead to the code written for the OCR programs to become obsolete, not to mention all of the data that is present in the game without being available on a live screen.


Read the full version of this article in Edition 7 of The Esports Journal.

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