Last Sunday was the largest sporting event in the United States, the pinnacle of the 2017 NFL season, and the odds are high that you watched it. NBC's telecast for the Super Bowl drew 103.4 million viewers, apparently tumbling by 7% to its lowest levels since 2009. Even so, 103.4 million viewers are almost a third of the entire population of the USA, a staggering number in its own right.
The Philadelphia Eagles eked out a hard-fought victory against the New England Patriots, winning by a full eight points, 44-31. That 8 point spread was actually the largest margin in a Super Bowl that the Patriots have played in since 2002, the first time Tom Brady played in one. The 8 point loss was by far the largest loss the Patriots have experienced in the Super Bowl, as they fell by 4 and 3 points respectively to the New York Giants.
The average National Basketball Association franchise is now worth $1.36 billion, a 350 percent increase over the last five years. We took the time to perform an investment analysis on two teams valued below average for the NBA, the Milwaukee Bucks and the Orlando Magic, to look for any beneficial investment opportunities. We considered the asking price for the team, based off of recent valuations, anticipated revenues and expenses, thought of as cash inflows and outflows, as well as an investment horizon of five years.
One business strategy that is finally gaining traction in sports is dynamic pricing. Associated with a poor connotation to users of Uber and Lyft, dynamic pricing, which is also referred to as surge pricing, is a pricing strategy in which businesses set their prices for products or service based on current market demands. This real-time pricing strategy is not a new concept. Travel-related industries such as hotels, rental cars, and airlines have employed this technique for years, as well as more recently in the energy market and sports businesses.
In 2014, Cubs single-game ticket prices at Wrigley Field were set through dynamic pricing, which helped more accurately price tickets for individual games and provides fans with more price options. However, with football season finally back, we decided to look at how a dynamic pricing structure could work for an NFL team. Back in April, the Buffalo Bills announced a new dynamic ticket pricing model for all Bills home games in the 2017 regular season that will adjust ticket prices to better reflect demand throughout the season. With this precedent established, we decided to see how this economic strategy would work for the Houston Texans.
With the Super Bowl between the Patriots and Falcons coming up on Sunday, the internet is flooded with probabilities of which team will win as well as a myriad of other prop bets. Currently, the Patriots are favored by three points and the predicted score is estimated to be around 28-25.
Nate Silver of the FiveThirtyEight blog, using a pretty intense simulator, has the Patriots at 61% of winning the Super Bowl with the Falcons consequently at 39%. His forecast is based on 100,000 simulations of the season with updates after every game. His model uses Elo ratings, a complicated measure of strength based on head-to-head results and quality of opponents, to calculate a team’s chances of winning their next game.
To check these probabilities, we developed a basic simulator incorporating only the final scores from games played by the Patriots and Falcons during the regular season and playoffs so far.