Last Friday I published a thread on Twitter decrying the NHL’s proposed Play-in 24-team format for the 2019-20 Stanley Cup playoffs: What’s most insane about the 24-team suggested format is that it inordinately impacts a select few teams. CHI and MTL go from like <1% chance of making the “playoffs” to (let’s back-envelope) 40% while…
Author: Michael Parkatti
The Unlikeliness of Goaltending: A New Methodology to Assess Talent
TL;DR – I helped create a new model to assess goaltending talent based on simulating each goalie’s career-to-date expected goals 10,000 times and seeing how unlikely their actual results were after each career game. You can see the final visualization here. How I got into this mess… This past summer I embarked on a series…
Neal’s 3rd rounder: deconstructing a beautiful condition
Last week I analyzed James Neal’s projected goal totals for 2019-20, concluding that his average goal expectation was around 18.5 goals over an 82 game schedule. An astute observer noted that it was unlikely he would play the entire schedule, making that prediction a bit optimistic. I’ve also been a bit fascinated by the Lucic/Neal…
How many goals will James Neal score in 2019-20?
On Friday, news broke of one of the more anti-climactic 1-for-1 trades of former NHL stars when the Oilers and Flames swapped slumping players Milan Lucic and James Neal. While a near-obvious win for the Oilers with respect to contract terms alone, the trade also offers an alluring second pathway to create additional value in…
When you can tell your goalie isn’t a starter — Part III — Bad Goalies
Over the last couple of days I’ve posted on applying a simple statistical test to NHL goalies to gauge their starter potential and how this test performed on actual ‘good’ goalies. Today I’ll be exploring an unanswered question from yesterday — does this test falsely characterize actually ‘bad’ goalies as being good, thereby leading to…
When you can tell your goalie isn’t a starter — Part II — Good Goalies
Yesterday I wrote about how you can apply a straightforward statistical test using the binomial distribution to accept or reject the notion that a particular goaltender has decent-NHL-starter talent as his career progresses. It turned out that Mikko Koskinen failed this test at game 37 of his career and then from games 56 and beyond…
When you can tell your goalie isn’t a starter, and Mikko Koskinen – Part I
TL;DR Using probability theory, the conclusion that Koskinen was a non-starter-quality NHL goalie could have been reached by game 37 of his career, shortly after he signed a huge deal at game 31. This week I’ve gotten myself obsessed with Mikko Koskinen and the recent start of his 3-year $13.5 Million contract. I’ve long had…
NHL Draft Series Part 5: Support Vector Machines (Linear)
In my previous posts, I’ve been using relatively simple tree-based models to visualize how classification works in sorting teenagers into two piles: “NHLer” and “Non-NHLer”. I went to fairly ridiculous lengths to squeeze as much predictive power out of those admittedly cute trees as I possible could. In today’s post, I’m moving on to some…
NHL Draft Series Part 4: Exploring Dimensional Space
In my series of posts on building predictive models for the NHL Entry Draft, I’ve explored using classification trees both on a full set of 57 variables and on a 2D fun-sized version of those 57 variables. In today’s post I’m going to explore using a) feature selection and b) dimensionality reduction to transform my…
Draft Series Part 3: Classification Trees (2)
In my last post, I introduced the concept of classification trees to predict NHL players in the entry draft. In that post, I made a simple tree that explored a 2-dimensional space to select the best decision shape to predict well using held-out data. In this posting, I’ll be allowing a classification tree to explore…