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ABSTRACT

The sports consumer of today not only has a variety of content choices, they also enjoy the convenience of consumption when they want it, the way they want it.

In this multi-choice environment, competition to deliver live, high quality and engaging content across multiple platform-devices combination is fierce.

This has in turn created the need for a newer, faster production environment that is collaborative, facilitates real time storytelling and is able to deliver to multiple platforms at one go.

This paper highlights innovation done using Cloud technology enabled systems to automate and ease each step of the story telling process that can aid live sports production.

This with the additional flexibility for various teams involved to operate from different physical locations.

The result – an integrated and quick story telling cloud based system that facilitates collaboration between multiple teams and vendors to create content that is contextual, engaging & delivered quickly.

INTRODUCTION

Sports as a content genre can be characterized using certain keywords – live, unscripted drama, conversational, loyal audiences.

No wonder that major sporting events like the FIFA World Cup, Olympics and sporting leagues like NFL, NBA, NHL and MLB are watched by millions of people across the globe.

But the way we consume sports is evolving. Add immersive experience, the need to view more of contextual content and the need for participation – interaction and sharing: one gets to see the emerging future of sports broadcast.

How long does it take to create an engaging story from a live sports event and publish it to Over-the-top (OTT) or social media? How long will viewers wait for this video?

For consumers who are not able to view the live event, getting near real time access to the key moments of a live event is a given.

Thus if the clip is not available on one platform, they will probably view it somewhere else.

This lag between creating stories and publishing them is a key concern during live sports/event production.

And with the number of monetization opportunities associated, content owners do not want to miss even one due to any such “lag”.

The need of the hour was for one solution that effectively manages the interplay between real time metadata, editing and delivery to multiple screens.

POST PRODUCTION - LIVE SPORTS

Post producing content for live sports events typically goes through the following process:

Step 1 – Capture of live feed
Step 2 - Edit sequentially in linear way as the feed grows. Scrub through the timeline and search for point of interest clips
Step 3 – Transcode the edited sequences
Step 4 – Publish to multiple platforms: TV, back to live playout, Over the top (OTT) platforms

Key Challenges

Traditionally, the key challenges encountered with the above process are:

Searching for ‘point of interest’ footage across the entire live feed timeline is manual and cumbersome
The approach to editing is linear. This not only is time consuming but also leads to curtailing creative freedom as time is most lost on scrub and search
Communication gap between remote teams - on-field Producers/reporters & Editors. This leads to multiple iterations and hamper creativity
Distribution – The complex task of transcoding multiple formats and delivering to multiple platforms (Broadcast, Video on demand (VOD), Over the Top (OTT)) and multiple devices (Web, Mobility, STB) overburdens the operational teams’ tasks

THE SOLUTION

Labelled as the “StoryTeller”, this cloud based solution would aim to address each of the ‘areas to solve for’ highlighted above by marrying data and video.

Be it live sport, production of shows from archive material or support for Studio productions, the thought was to build a platform for Sports that would manage content operations through various stages by providing tools and solutions like multi-sports live logger, native integration to Non Linear Editing (NLE) and integrated publish robots.

Sport & Associated Data Model

The true capability of the solution would come to the forefront if it could handle a lot of data – each data point associated with a unique event during the live sports event.

Owing to this Cricket and Football were chosen as the two sports to begin with.

For example, in a cricket match, every ball bowled is an event. Typically on an average, one match has around 600 on field events. Each event can be described using a number of parameters.

The data models for these sports were defined in conjunction with the end user. These data models not only included the on field events but off field ones too.

On and Off field events could be used to create topical stories drive additional viewership.