Analytics, Big Data and BI or: How I Learned To Stop Worrying And Love The Cricket

analytics-big-data-and-bi-blog-cricket-pitch-map

One of the challenges of working for a company like AlignAlytics is explaining exactly what it is that one does all day. Nothing scares off a new potential friend quicker than phrases such as ‘data-driven strategy and insight’, accompanied by some vague hand waving, especially if said hand waving usually sends drinks flying. Typically, after several failed attempts at explaining the concepts of customer segmentation and advanced analytics, the standard fallback response is that we spend our days doing reporting & analysis before moving the conversation on to more interesting topics, such as Justin Bieber turning up really late for gigs or the on/off relationship between those two miserable leads from the Twilight movies.

However, while analytics might appear a foreign concept to many people, the truth of the matter is that it has been part of people’s lives for a long time, even if they didn’t know about it. One particular area of modern life in which analytics is widely used is in sport, specifically in its coverage on television and via digital media. It’s also here that concepts such as big data can be most easily comprehended and explained.

One particular sport close to the heart of this particular author is cricket, a sport built entirely on large numbers of discrete data points. Every single time a ball is bowled, a huge number of different pieces of information are collected – how fast was the delivery? Where did it land? What shot did the batsman play? Which Australian did it dismiss? This is repeated for every ball bowled in every day of (almost) every match around the world. Before you know it we have a genuine example of this mythical big data that everyone has been talking about.

Of course, collecting data for data’s sake can be its own reward – apropos of nothing, nothing impresses a crowd like owning the entire set of classic Doctor Who DVDs – but it’s the interpretation of all this data that is really the key. Hence the proliferation of visual methods on TV and the internet to help commentators or writers provide insight and clarity, such as this example, a pitch map for a specific bowler:

Stuart Broad Pitch Map

Image Supplied by © Hawk-Eye Innovations

Suddenly, and without really thinking about it, we have analytics. And not just that, analytics based on big data. In order to get to those analytics we’ve used specific software to turn our data into something that we can visually comprehend and interpret. And that’s Business Intelligence (BI) software explained at the same time.

Of course, cricket isn’t the only sport to use these concepts. Football (or soccer as it’s occasionally known in the colonies) is a more recent convert to the idea of big data, albeit in a much more ‘closed shop’ way. The likes of Opta and Prozone provide enormous amounts of data around every single football match in the Premier League (and beyond), with every single pass, shot and run recorded in frightening detail. This data is generally not made available to the public, instead being closely guarded behind closed doors by those football clubs that use it (and largely ignored by those that don’t).

Recently however, Manchester City made large amounts of this data available, encouraging members of the public to do their own analysis and trying to create an ‘analytics community’ in which ideas could be shared. Whilst it’s possible to argue about their motives for this – why pay for an analytics team when hardcore fans will do it all for free and then you can steal their ideas? – it’s clear evidence of the growing significance of analytics (and big data) across different areas of everyday life.

To conclude, perhaps the best way to explain what one does all day is to talk about cricket and its approach to big data, analytics and BI. And then, after several hours of explaining the intricacies, such as the difference between the flipper and the topspinner, casually point out that AlignAlytics generally applies these concepts to the marginally less exciting worlds of consumer goods and utilities. We say generally because everyone needs a hobby for their free time, such as tracking Stuart Broad’s Test career over time:

Bowling average vs Batting Average

Author: Ashley Michael

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