Hello everyone Could you suggest any betting sites in the UK or Europe that offer Asian handicap markets for individual team goals—for example, betting on a specific team to score "over 1" or "over 2" goals, rather than the standard 1.5 or 2.5?

Brighton at 3rd, Man Utd at 9th. Not a typo 🤯 before GW7

Been working on this in my spare time: getsidelinestats.com
It's got predictions, injury impact and player stats for every NFL game, with NHL, NBA, AFL and NRL on the way. It's free, with no sign-up or ads.
It's my first time putting something like this out there, so any feedback is appreciated. What works, what doesn't, what you'd change. Please be nice 🙂
Not betting advice, just a fun stats project.

As some of you know, we have built and been upgrading longshot.football for a while now — it’s a verified database of long-range goals measured frame by frame (distance, speed, flight time, all derived from the actual footage).

Just pushed three new updates to the GoalPOV side of the site:

1. “What if X shot this?”
On any goal in the database, you can now swap the shooter for any other player we have data on. Pick Gerrard’s free kick, choose Scholes as your comparison — it recalculates the flight using Scholes’ fastest recorded shot from our database and shows you the difference in speed, flight time and trajectory side by side. Basically answers the “but what if [player] had taken that?” argument with actual data. No more "player X doesn't have the power to shoot from there"- its fractions of a second you will see.

2. Custom Speed Mode
You can now set any shot to any speed up to 266 km/h (based off the Mandirali debunk) and watch it play out in GoalPOV. Built this specifically for the debunks — if you’ve ever seen someone claim a shot was 200+ km/h and wondered what that would actually look like, now you can see it. Spoiler: it would be physically unreasonable.

3. YouTube Sync Mode
Since every goal on the site comes from YouTube footage, you can now play the GoalPOV alongside the original broadcast at the same time. There’s a scrubber to align them manually since not every clip syncs perfectly, but once you’ve got it lined up you’re watching the real footage and the 3D recreation simultaneously.

Everything is free to explore at longshot.football

Been working on this for a while. It tries to predict when the strike is coming and if it landed.
Eventually creates a fighter profile which tells about the traits of the fighter. Long way to go but this a working first version.

This has bugged me for a while. The box score has three shooting percentages: FG%, 3P% and FT%. Two of them measure one kind of shot. FG% doesn’t. It lumps twos and threes together, even though threes already get their own column.

The box score already solves this for rebounds. You get OREB, DREB and the total REB. Shooting is the odd one out: FG is the total, but only 3P gets broken out. Adding 2PM, 2PA and 2P% would just make shooting work the same way as rebounding, and you’d still keep FG%.

It’s basically a leftover from before the three-point line. When the NBA added it in 1979, they tacked 3P columns onto FG% instead of rethinking it. With how many threes teams take now, FG% says more about shot selection than shooting. A guard who’s great from deep can have a worse FG% than a center who only dunks, and stuff like 50/40/90 punishes the guys who take the most threes.

Before you all crucify me: yes, I know eFG% and TS% exist, and they’re better for overall efficiency. But they mash everything into one number. 2P% shows you the split. And it’s not new data. Basketball-Reference already lists it.

Is there a good reason not to add it next to FG%? What am I missing / what do you all think?

I work on Liat AI, and I wanted to share what we have been building and hear what people here think.

Many clubs, youth academies and smaller leagues stream their matches with no commentary at all. We give those matches AI football commentary. It watches the live match through one camera and commentates as the match is played, with a few seconds of delay, in 20+ languages.

You can pick the commentator's pacing, tone, accent etc. Line-ups are optional, and without them the commentary refers to players by jersey number. It's very cheap and affordable

There is a short demo of it here: https://liat.ai/demo/

I would love to hear what you think, especially from anyone who works with match data or streams matches. What would you want an AI commentator to get right first?

Week 5 of the NFL has dropped and isn't it about time we show special teams the love/hate it deserves?

First, I looked just going into the third period. So blowing leads, or coming back from a deficit in the third.

Then I looked at this controlling for team quality. Not in the worlds most rigorous way, just imagine this scenario:

1. You play 100 games, and in 35 of them you enter the third behind
2. You win 9 of the 35, which is 26%. Is that good or bad?
3. Well, in your other 65 games you took about 78% of the points, and other teams in the league at that level come back from trailing at 15%, which is ~5 games.
4. Therefore, you make come backs a bit more than expected, 4 more times than expected.
5. Over the five and change seasons, anything within about 9 games of expectation is normal variation

I've been looking into whether the NFL's limits on padded practices have made players more vulnerable to soft-tissue injuries.

The timeline is interesting. The big practice restrictions started in 2011, with another change in 2020. Then the pandemic wiped out preseason games entirely.

A 2022 study found much higher hamstring, groin and calf injury rates in 2020 compared with 2018. That seems to support the idea that players need a progressive ramp-up before full-speed competition.

But another study looking at the 2011 CBA found no sustained injury increase. And the NFL says its lower-extremity strain rates have recently declined.

So here's the question: Is the real problem a lack of contact, or a lack of progressively increased football-specific workload?

Would more preseason snaps actually help, or would they just shift injuries into August?

https://2ndcitystandard.com/articles/nfl-soft-tissue-injuries-cba-practice-restrictions

I am a data analyst by trade and was looking for fun/useful applications of my score and setup data. This project takes your setup and scores and predicts likely scores for WA and AGB rounds. It also gives a suggested aiming point for barebow off shelf/rest etc. Uses fairly basic physics via python but it's working. Is this interesting to anybody?

I don’t support one club, I just like a good game. So I built a site that gives every UCL match a pre-match "watchability" score out of 10.

An LLM reads recent coverage of each club, including local papers in Italian, Dutch, Ukrainian, Greek and more, and rates how the team plays: how high they press, how high their line is, how they build up. A few simple rules then combine the two teams. If both press high, the score goes up. If both sit deep, it goes down.

This week my tool says the most fun games will be Inter v Club Brugge and Arsenal v Lille (both 10.0, the scale tops out, I’m working on it). It says skip Aston Villa v Fenerbahçe (3.8).

https://worthwatching.football. It’s free, no sign-up, and each match links the articles behind it. Would love to hear your thoughts!

I would like to know sources of data for non-major sports. I would like to exclude football/soccer, American football, NBA (European basketball is OK), MLB, NHL and other USA-specific sports. I intend more on track and field, cycling (as team strategy), handball and 'european' sports

League power rankings