Project Development: Eureka!

I believe I may have had the breakthrough I was looking for with my project. I am very relieved, as this has been extremely stressful throughout this semester, and I finally feel as though I possess an idea that accomplishes everything I wanted to: Uses GIS, encorporates hockey, effectively illustrates an idea, and makes my data set perfectly manageable.

To this point I had considered several different ideas all relating to hockey. I considered doing a project similar to Vince’s illustrating player origin. That had since evolved into an idea which plotted those players as well as their journeys throughout their careers, looking at trade deadlines and player impact on new teams. This was going to be a tremendous amount of data and was something that had been plaguing my nerves.

I also had a personal qualm with that project idea: I had decided to cut off any data from my map before 1980, contending that this data would be far less useful to my project then the data from years after 1980, as player movement during that time was far less. I like to be able to justify, in a sound manner, reasons for why my projects relating to academia are crafted the way they are. I was not sure that I had achieved this with my 1980 cut-off, as even to me that seems somewhat arbitrary. My train of thought was that if I felt this way, and I was the project creator, I should likely try to address that.

Then I got an idea! 

I started thinking about what had happened in the hockey universe lately. Things like, who has been winning and losing? How have drafts affected team performance? Things like that. Then my brain said: Steve, you’re an idiot. Lockout. Duh.

Ofcourse! The lockout!

I have decided that what I will do is map the movement of each player who was in the NHL during the lockout. This will be similar to my original project idea, which saves me some of the work I’ve done, as well as the skills with GIS I’ve been slowly and painfully developping. 

Essentially, my map will consider things like players age and political climate when mapping player movement. Were younger players more likely play in Europe? Did governmental structure change appeal to players as indicated by the map? Did players select leagues by which paid the most money? I’m sure that I will bring this into greater focus as we draw nearer to the conclusion of the semester, but my excitement is buidling. This is primarily the result of having addressed what I felt were the most difficult obstacles standing in my academic path: Proving something and avoiding an arbitrary launching point. 

In other news, I continue to be in contact with hockeydb.com regarding the use of their database as the primary resource tool for my project. As mentioned during my presentation, the primary concern of hockeydb.com is that my site will be competitive with theirs, disturbing their traffic and business. I feel that this new information about the tweak I’ve made in my project will be to their relief, and secure their blessing. That is the next objective.