The business of sport is unlike any other business. It is one that is governed by emotion more than anything else, and will continue to be so. There is no “logic” behind why someone is a sports fan or why someone stays so loyal to their team. This is an industry where growth and profitability are directly correlated with one predominant thing- fan (human) behaviour.
So how can analytics, a concept that is synonymous with logic, be effectively used here to drive business value?
Well, analytics has been present in the industry for quite some time and it can essentially be broken down to two key segments - On-field and Off-field analytics.
This is something that the industry has been familiar with for some time- it is essentially a data-driven approach to improving performance. Whether it is player fitness, offensive strategy, shot selection, biometrics etc. on-field analytics has been helping clubs better their teams. The media has done a wonderful job on shedding light on this topic and movies like “Moneyball” have become household topics.
Over the last few years, analytics in sport has evolved beyond the field. A seemingly less glamorous element, but no less important, off-field analytics deals with every aspect of the sport business other than on-field performance. A much broader segment, it does take into account on-field variables such as match wins as well however, this is done with a more surgical focus on off-field elements such as sales patterns and ticket pricing to help rights-holders grow their business. Off-field analytics essentially considers every parameter associated with the performance of the business to aid and promote decisions that would lead to higher growth and increased profitability.
As a rights-holder or business leader, visibility into aspects such as merchandise sales and stadium attendance, is critical to business performance and Traditional BI has been used over a long period of time to help such processes. Through our endeavours, we have seen newer aspects of analytics such as, sentiment analysis, being adopted to understand fan sentiment on social media and other platforms prior to taking further marketing decisions. However, due to the rapid evolution of technologies over the last few years, the real value in off-field analytics lies in the application of sophisticated algorithms (Deep Learning & Cognitive algorithms) to quantify fan behaviour and predict future scenarios and events.
We have seen such technologies are already being used in other industries for Business and Engineering applications such as Machine Failure Prediction and Operations Optimisation, and is critical to the future of the sport business. The adoption of these technologies would essentially form a strong bridge between rightsholders and fans, who are essentially a clubs/leagues major source of revenue, and help answer critical questions such as:
What are the actions that I must take to increase attendance at games?
Which of my sales channels are likely to be the most effective next season?
Are there events going on around the world that might affect a fan’s opinion on whether a ticket is justly priced?
How do I quantify the level of loyalty of a fan based on their behaviour and maximise his or her propensity to spend?
What kinds of products should I market to different groups of fans?
Though partly aided by data, ever so often, these questions have been dealt with in a way that is highly dependent on the opinions of individuals within sport bodies rather than data. Their understanding and knowledge of the industry is critical but currently, data technologies have evolved to a point where with the right application, better informed decisions could be taken that would ensure a brighter future for the industry as a whole.