u/Practical-Climate926

Hi all!

I wanted to share a new feature of my website Hockey Alchemy, in time for the start of NHL Free Agency tomorrow: Trade Probability Board

How does it work:

I built a trade probability model using Python (Not GenAI), that uses seven different factors including: contract, performance, team situation, age, depth chart, injury history and finally player "buzz". For Buzz, I scrape tweets and articles from different authoritative sources and weigh them based on how correct they have been in the past (Shoutout to Elliott Friedman). It doesn't predict the probability of a trade to a particular team at the moment (next steps), but I do include the rumoured teams in the UI based on what I can scrape.

Open to all feedback and suggestions on how to make it better!

About Hockey Alchemy:

New Website includes: A full GAR/WAR model with component breakdowns (EV offense/defense, PP, PK, shooting), Power rankings, playoff odds, player + team pages and comparison tools, customizable dashboard and personalization for logged-in users, and the best public xG model from what I can find (0.81 AUC).

Link to the trade board: https://www.hockeyalchemy.com/trade-board

Hi all! I wanted to share a new hockey project I've been working.

A few years ago, I started an NHL Draft-focused website (hockeypipeline.com), which is still going. My co-founder and I are currently adding new features as we prepare for the upcoming NHL Draft.

I wanted to try something new and started building Hockey Alchemy — a free NHL advanced-stats site — and I'd rather get torn apart by this sub than anyone else, so here it is lol.

What's on it right now:

- A full GAR/WAR model with component breakdowns (EV offense/defense, PP, PK, shooting)

- An ML expected-goals (xG) model, RAPM, and GSAx for goalies

- Power rankings, playoff odds, player + team comparison tools

- Per-player and per-game pages with the underlying analytics

- Customizable dashboard and personalization for logged-in users

On the model: I've been validating it the way I think these models should be judged — year-over-year repeatability and correlation with actual team results — rather than how closely it matches another public model. On those metrics, it holds up well against the best public NHL models. Happy to go into methodology or share tech stack in the comments.

It's free, no paywall currently, but will probably add a subscription model for some net new features.

Link: https://hockeyalchemy.com

You can also follow me on X/Twitter and DM me if you have any questions/comments/feedback: https://x.com/hockey_pipeline

Not trying to spam — genuinely want the criticism. Thank you and have a good day!