Hi, my name is Jonathan, and I'm a freshman at NYU Stern School of Business. As a lifelong New York Rangers fan, I have seen my team tease me with success in the playoffs before bowing out to better teams. A few years ago, NHL started an advanced statistics page looking at two of the most notable advanced hockey statistics, Corsi and Fenwick. I began to notice that teams with a higher percentage of shots during a game, specifically those over 50%, usually had more playoff success. That, along with the Michael Lewis' Moneyball, introduced me to the power of using statistics and science to achieve success in sports. As a result, and at the recommendation of my regression statistics professor and data-analytics-industry-veteran, Lucius Riccio, I created this blog to explore this relationship. Specifically, how hockey statistics can lend a hand to team development and ultimately, and most importantly, playoff success. Since I am still scratching the surface of this field, please be prepared to learn with me, and I encourage you to highlight any missteps I make in my analysis. I will conduct this analysis in weekly blog posts. For my first analysis, I will examine the recent blockbuster trade between the New York Rangers and Tampa Bay Lightning. For this, I will look at an advanced statistics breakdown for J.T. Miller and Vlad Namestnikov who went to Tamp Bay and New York, respectively.
As you can see in this image, in spite of my initial pessimism due to Vlad's being a year older, Namestnikov is actually a more effective player in some regards. First, their exits statistics reveal some interesting things. Although his per-60-minutes-exits is lower, his possexit% is 30% higher than Miller. This is more significant than the above statistics, as it indicates Vlad, when he does carry the puck out of his zone, is more likely to maintain control during such plays. One explanation for his lower possexits60 and lower entry statistics is his Tampa Bay linemates. Playing frequently with elite offensive talents in Nikita Kucherov, currently first in the NHL in points with 82, and Steven Stamkos, 9th in points with 71. Additionally, Stamkos is 9th in the NHL in assists with 47 and Kucherov is 4th in the NHL in goals with 33. This means that Namestnikov was a third option on a line, behind two players who have dominated the opposition offensively the entire season. Therefore, beyond the defensive zone, he is shooting and handling the puck less. Additionally, Namestnikov's data is from 61 games and 863 minutes fewer than Miller, so as his playing time and responsibilities increase, it is reasonable to expect an increase in his offensive statistics as he has played with and learned from elite talents. Further compared to Miller, Namestnikov had superior defensive statistics and understandably inferior offensive statistics in a role with reduced responsibility as Miller was one of the Rangers' top players. Defensively, as I do not expect his responsibilities to decrease, similar numbers should be expected. Therefore, in spite of his elder age, and from the perspective of a student exploring the power of using science to build successful hockey teams, this was a fantastic trade. It provided the Rangers with a different kind of center, a center who will likely be more effective in an increased role. I hope you enjoyed my analysis, and please provide suggestions as to where I might improve in the comments. 'Till next week, Jonathan.
Comments
Post a Comment