Sorry, not sure if this is the right subreddit, but I found a very old hoodie (probably from 2011 - 2013 given that is when the CT Whale team existed) in a small creek with roots growing through it and lots of holes. I doubt I’ll ever find the owner of it, but it made me very curious about the team and who could have owned it before throwing it away here.

Any other Hammers STH here? Any thoughts of feedback so far on the seats and venue? I just purchased premium seats in 116 and loving the seats and experience so far. Team needs work but we'll get there.

Mods, I appreciate you

I’m watching tonight’s game Hamilton Hammers game against the Rochester Americans, one thing that have found weird is that there at home and wearing there white jerseys because I thought there blue ones were supposed to be there home/primary is there something in the AHL where the home team usually wear the white jersey or some home games they where the white jerseys at home

Hey!

I'm starting a book and my main male character is a hockey player in AHL league. Can anyone give me a realistic time frame for practices. I don't want to look like a dummy. It looks like maybe practice tues, wed, thurs, games FSS. Off monday for travel and rest.

But how many hours is a typical practice?

Scrimmaging vs drills vs strategy ?

Clearly I'm not an athlete.

thanks : )

I played field hockey in high school but I was no good!

I moved away from Belleville 26 years ago and was a Bulls fan of the OHL so I was curious and streamed a bit of a recent Belleville Senators AHL game and noticed that the rink was like 90% empty. Is it always like this? For Bulls games it used to be mostly full.

I’m interested in consensus opinion on hockey development. How do you think an average modern day AHL team would fare against an NHL team from 2003? Would the advancements in training, game speed and systems put the AHL team over the top?

We could theoretically have two games, one with 2003 rules and the other with 2026 rules.

The AHL site only gives save percentage and GAA, and those treat a point shot and a one-timer from the crease as the same shot. I wanted a rough goals-saved-above-expected number off data anyone can already see, so this isn’t a private model or a scraped tracking feed.

The shots come from the public HockeyTech feed behind the AHL game center online, the same source as the shot chart on a game page. For every final 2025-26 regular-season game I pulled the play-by-play. Each shot event has the goalie, whether it went in, an x/y location, and the league’s own quality tag.

Empty-net shots are dropped, because there’s no goalie on the event. Shootout attempts are dropped too. The coordinates are an image scale, not NHL feet, so I estimated the two nets from where goals actually clustered at each end of the rink and measured distance to the nearer one.

Expected goals is then just the season’s scoring rate in that distance bin and quality tag, shrunk toward the league rate so a bin with four shots doesn’t go to 0% or 100%. One fix matters: the raw tag says “Quality goal” on goals and “Quality on net” on saves. If we leave that in, the model already knows the result and the GSAx is wrong. I stripped the outcome and kept only quality vs non-quality.

GSAx is expected goals against minus goals allowed. Positive means the goalie allowed fewer than that location model expected on the shots they faced. GSAx per 100 shots is the rate version, so a 20-start goalie and a call-up aren’t compared only on totals.

This is NOT MoneyPuck. There’s no rush, rebound, screen, or pass quality in the public feed, and the coordinates are coarser than NHL tracking. One season of goalie data is still noisy even with a better model. Read it next to save percentage: a big gap is the interesting part, a one-goal gap is not.

Whether GSAx is better than GSAx/100 depends entirely on what you want to measure: total team impact or individual efficiency. Both are vital advanced metrics in hockey analytics used to evaluate goaltenders by comparing actual goals allowed against expected goals (xG) based on shot quality. GSAx is Heavily biased toward starters who play more games and for GSAx/100 Small sample sizes can heavily skew data (e.g., a backup after 2 games).

Leading scorer?

Cup Champions?