Sports clubs are more and more real business companies with a very specific aim: to produce values. This is the final goal, but the real challenge is how to reach it.

All the items of income are closely linked to the sports results of the team, but there are many leverages that the management can use in order to maximise the revenues. One of them is to bring the highest number of supporters into the stadium or arena.


After years in which the number of visitors was increasingly falling down during matches, in 2007 San Francisco Giants, one of the clubs of the Major League Baseball, decided to introduce one of the most successful practices used in other business sectors like travel or hotels: the dynamic pricing. 

Whats is Dynamic Pricing?

This new way to manage pricing caused a real revolution in those areas where it has been practiced; if you think about airline societies, some sophisticated algorithms allowed many low-cost companies to powerfully enter the global market always scheduling sold-out flights.
Dynamic pricing consists of modifying ticket prices according to some direct and indirect factors. This system permits to maximise revenues both in a match with low and high attendance. In fact, when a match has no appeal for the fans, the ticket average price drops down; instead, when a sold out it’s announced the ticket average price rises up (usually, in this case, secondary ticket platforms sell tickets with a very higher price).
The only issue was caused by seasonal tickets. In fact, the club guaranteed the subscribers that the single ticket would have never had a lower price than the one they paid for. In the supporters’ hierarchy, the seasonal ticket is at the higher position, because it manifests trust and faith in the club and allows it to have financial resources at the beginning of the season.
This MLB franchise was able to implement dynamic pricing for the first time in the worldwide sports, thanks to the support of Qcue, the first company that used these algorithms in this sector. In fact, using dozens of rules (like weather, the opponents, the day of the week) they apply prices that convince the fans to assist the match.
In the first year ticket prices dropped down of an average 15%; in the meanwhile, attendance, in the sector influenced by dynamic pricing, rose up of 20% and revenues increased of 7%. Fantastic results, if you consider that other teams saw a downward trend in the ticket revenues. 
The choice of San Francisco Giants was the best one compared to other franchises that, to fight the crisis, frozen and sometimes lowered the prices with bad outcomes.
In the next years, many clubs followed this choice in all the most common American sports leagues like MLB, MLS, NHL, NBA. At this point, almost all the American franchises use dynamic pricing. In the last two years, it crossed the European borders, where teams like Virtus Entella (a Football team in the Italian Serie B) and Fiat Torino (a Basketball team in the Italian Serie A) are frequently using it with good results. In the Italian sports panorama, where the attendance at the events is always lower, dynamic pricing could be a solution. In fact, it’s thought that in the next 5 years dynamic pricing will be a common practice.
This is a classic example of how big data and data mining are positively influencing company choices, in this case, sports companies, that are even more forced to find new ideas to be sustainable and, why not, to make their fans happy. Supporters are the real engine of all the worldwide sports system and make them loyal is an ambitious challenge. 
The dynamic pricing practice is the paradigm of how business can learn from the digital developments of the sports world. When we talk about sports system, we are not only analyzing values but also technological working models able to become real game changers in a mid-long term period.