Need you to write a 2-3 essay
Bradley Williams
Professor Barr
CIS 201
4/20/17
Speaker Assignment
Analytics are being used to improve business operations through things like fan behavior, how sensitive people are to ticket pricing, how much other people are being influenced, and what a person’s path was to buying the ticket. With regards to ticket pricing, on average for a typical professional game, twenty-five percent of tickets go unsold. If the fans were polled and questioned about the game, 30% said that they would have gone to the game if they had known there were seats available. Many online sites like Hubspot and Ticketmaster are doing competitive pricing. Fifty percent of people are looking up the prices of ticket on their mobile phone. Many people are not just using social media at the game to tell other people that they are there through Instagram and Twitter, they are actually using their phone to look up prices for the next game they plan to attend. This data is very important data for the people who are selling tickets.
The first report on dynamic pricing was done by the San Francisco Giants and they were classifying the price of tickets depending on all of the factors that are thought to be important: When the game is being played, who the team is playing, the seat location, and what part of the season. All of these factors influence how much money people are willing to pay for tickets. With airline tickets, every 15 minutes on Continental United Airlines revenue optimization is being done where the price of the ticket will change. Sometime the price of tickets will go up, sometimes the price will go down. Bayern Munchen a German Soccer Team, is using smart seats that know when you sit down and can start giving you different food options through your phone. If you are late to a game, though their app they can direct you to the closest parking garage where a bus can pick you up and bring you to the game. Also they can stop congestion where everyone leaves at the same time by having star players go to certain parts of the stadium so fans can follow them and leave through a certain exit. After the game is over they offer discounted beer and food so people can stay a little longer, slowing traffic outside of the stadium and ultimately bring in more revenue to the soccer team.
Leading pro teams and leagues use analytics for basketball, baseball, football, and soccer. Analytics are being adopted very quickly, by many teams, in many different sports. The New York Yankees and the Boston Red Socks are the most expensive tickets in the MLB. It would cost you 356 dollars for a Red Socks Ticket. The cheapest tickets in the MLB are the Rays and the Diamondbacks. It is a 3:1 ratio in comparison for what you have to pay. The most expensive ticket come from the NFL and the Cowboys will charge you the most per ticket, while the Bears will charge you the least. Teams like the Cowboys have had a loyal fan base for a long time, because of this they are able to charge more for their tickets and in a way they don’t really need to do anything. Some teams add superstars to make more people come to games to see these certain players perform.
Analytic techniques used in business apply to sports because people have passion to stay with their team. Through techniques such as text analytics, emotion in words, data monitoring, and machine learning people will renew their season tickets and seats because they have passion. No matter how much they complain about food prices, jersey prices, and drink prices they will come back in the future. There are gaps when it comes to the people or demographics of people tweeting about a certain sports program. When there is an MLB game on the people who are tweeting are substantially older than the people tweeting if there were a NFL or NBA game on. Some interesting research problems in sports analytics are things like environmental and psychological factors. Environmental Factors in the NFL for kicking a field goal are the distance, the temperature, field surface, altitude, precipitation, wind, and humidity. Psychological factors are regular vs. postseason, situational pressure, home/away, and whether the kicker was iced of not.
Other parts of the university, like the business school can collaborate with sports programs to provide analytics for teams to think of new products and ways to keep athletes safe and at their best. Also they can use analytics to get more people at the sports games and decide days and times to have the games as well. Stanford did a study with their basketball players making them sleep ten hours a night to see if there was a correlation in their free throw percentage and their sprint time. Their sprint time surprisingly went down but their free throw percentage went up. Some good projects to launch could be a sign in at the sports games here at Bryant, seeing how many people go to watch which team the most. Smart mouth guards could be another project, which are actually coming out in the future. More projects that can improve safety are projects that will matter in the long run.
Other universities such as Wright State University in Dayton have done two projects, one on injury prediction in soccer and one on ticketing analysis. At the university students wanted to figure out what drives the ticket sales and for the second project they take daily measurements, putting a vest on and taking measurements of heart rate for male and female athletes. We can certainly do Money Ball at Bryant. The speaker was able to do an activity with everyone in the room with a smartphone to see if they would be vulnerable to athletic injury in the future. If he can do it with all of the students, coaches should be able to do something with their athletes to make sure they are safe in the future.
