Michael Southwick
@michaelstatwickVillanova AQF & Sports Analytics President | IG:hockey.ranks | prospect & hockey analytics
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Just made a post outlining the current iteration of the OHL xG model I’ll be using more and more frequently, check it out! instagram.com/p/CpSv9-hODHz/…
Amazing turnout for our first meeting of the semester 💪🏻 See everyone next week!
We’re happy to announce the club’s team of Michael Southwick, Chris Galgano, Amelie Devine, Stephen Cain, and Colin Hofmeister placed 1st at the Phillies’ 2024 Hackathon! We are proud of our team and excited to see what they can do in the future!
The long-work-in-progress PRJr project I showed work on during early 2023, will soon be ready to deploy to the website Results this year favor Dickinson over Parekh by a good deal in terms of elite upside even w Parekh’s higher PPG that will favor him in traditional NHLe models
A should-be functioning version of ranks-stats.com is now available for desktop use! Working on making it adaptive for mobile use as we speak. This is a very early version and I plan to add a ton more, but would appreciate any feedback on early OHL stuff!
Nick Bonino is currently 2nd in the NHL in blocks with 31 (19.35 per60) Frank Vatrano is the next closest forward who has less than half that with 15 (5.37 per60)
Lotta talk around Matthew Poitras’ play for the bruins this preseason. Had an extremely strong 22-23 campaign. Finishing 2nd in Playmaking among all OHL forwards & 5th in PP efficiency
I have been working with Juypter notebooks for the first time recently after years of R / Stata / SAS and the inability to see the datasets your working on in the corner is giving me like separation anxiety how do Python people do this
Here’s a look into some of the numbers from 22-23 for the 3 OHL dmen featured in Bob McKenzie’s 2024 draft rankings
how else am I gonna incite qmjhl teams to hire me if i you don't even let me do data analysis @CHLHockey
very preliminary and very simple tool I put together highlighting where players are generating most of their chances by xG/GP relative to the rest of the league.
Here’s a look at some work for a rink bias adjustment for my OHL xG. Shots tracked for and against at Oshawa’s Tribute Community Centre are consistently recorded about 4.5 ft further from goal than the mean SF & SA distance tracked during Oshawa’s away games
Jagger Firkus remains one of the best performing players in the model after this season. The results here do look pretty bullish, but with no huge jump in production his profile is one that tends to project to a very high level in the NHL
Here’s an example of the process of implementing DY progression into this model. Probably not the best vis here but each model gets significantly more accurate moving from DY to DY+1 which makes sense. Some players w/ big changes like Chabot, others really minimal like Suzuki
The only player besides Bedard in this dataset that shows a clear downward sloping curve from Elite potential is Zach Benson. Cristall has a very solid curve aswell, but despite Cristall’s higher PPG the model does favor Benson by a good margin, similar to most draft rankings
Danielson and Lardis follow similar trends (I swear they don’t all look like this). Danielson differentiates himself from Lardis as one of the highest players in the dataset in terms of projecting to AHLr or better and his high TOPr %
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