Alright, let’s dive into my little hockey experiment! Today’s title is “vancouver canucks vs san jose sharks”. Yeah, I know, not the most glamorous matchup, but hey, every game’s got potential, right?
First things first, I grabbed the data. I’m talking about goals, shots, penalties, the whole shebang. Found a decent API online, nothing fancy. Wrote a quick Python script to pull all the historical data I could get my hands on for these two teams. Basically just looped through the API, parsed the JSON, and dumped it into a couple of CSV files.
Next up, data cleaning. Oh boy, was this a mess. Dates in different formats, missing values everywhere. Used Pandas in Python to wrangle it all. Filled in the missing bits with averages and medians where it made sense. Standardized all the date formats. Basically, I just wanted the data to be somewhat usable before I started trying to make sense of it.
Time for some actual analysis. Fired up my trusty Jupyter Notebook. Started with simple stuff. Win/loss records head-to-head. Goals scored per game on average. Power play percentages. Just trying to get a feel for the overall history of these matchups. Nothing ground breaking, but it gives you a starting point.
Then, I tried to get a little fancier. Looked at rolling averages for goals scored over the last 10 games. Tried to see if there were any noticeable trends. Saw some small bumps and dips, but nothing screamed out “this team’s on fire!” or “this team’s totally falling apart!”.
Visualization was key. I whipped up a few charts with Matplotlib and Seaborn. Line plots showing goal scoring trends, bar charts comparing power play success, scatter plots looking for correlations between shots on goal and goals scored. Made things way easier to digest than just staring at rows and columns of numbers.
I even tried to build a really simple predictive model. Just a basic logistic regression. Fed it the historical data, told it to predict the winner of each game. Accuracy was, well, not amazing. Around 55%, which is barely better than a coin flip. But hey, it was worth a shot!
- Win/Loss Ratio: Canucks had a slight edge in the overall head-to-head record.
- Goal Scoring: Canucks tended to score a bit more on average in these games.
- Recent Form: Both teams were pretty inconsistent lately.
Final Verdict? It’s hockey, anything can happen. But based on the historical data and my quick analysis, I’d give a slight edge to the Canucks. Mostly because they seem to score a bit more consistently in these matchups. But honestly, it’s a total toss-up.
Look, it wasn’t a super in-depth analysis. More of a fun little side project. But it was cool to see what I could dig out of the data with some basic Python skills. And who knows, maybe I’ll refine my model and actually start predicting games accurately one day… probably not, but a guy can dream, right?
