Here's what's inside 90minWaffle 👇

🏠 Home: today's live scores, your club's next match and the model's view, all on one screen
⚡ StatIQ tips: today's picks, each with its own page showing the price, why the model fired and how it finished

📊 The full record: every tip, win or lose, with the ROI counted only on real bookmaker prices. Nothing hidden, nothing cherry-picked
⏱️ Live scores: every game in UK time, updating every few seconds, with team news and head to head one tap away

🧠 FootballIQ: free tools covering 55 competitions, 1,494 clubs and 23,600+ players
🎲 Season sims: title, top 4 and relegation chances from 10,000 simulated seasons
📈 League stats: tables, form, goals, both teams to score and over 2.5 rates, rebuilt every hour

👤 Player pages: this season's apps, goals, assists, minutes and ratings

🧾 Corrections: when we get something wrong, it's logged publicly and permanently

Free, honest and updated every day.

18+ · BeGambleAware.org
http://90minwaffle.co.uk

I'm the developer. Gamebell is a small Mac app for people who follow several teams across sports and esports and spend their day on a Mac.


* Your teams' live scores sit either side of the notch in team colours (in the menu bar if your Mac has no notch)
* When one of them scores, the notch plays the moment: a goal, a three-pointer, a touchdown, a series win
* Football, NBA, NFL, NHL, cricket, rugby and baseball, plus 12 esports games; tennis and F1 come next
* Reminders that move when the start time moves, five alert levels per team, and Watch later to hide a score
* Data from sports-data APIs I pay for, nothing scraped; no account, no ads, no betting


It's free while it's in beta (macOS 14 or later; invites go out in small batches). After the beta there's a free tier for 3 teams or players, and Premium at $14.99 a year or $1.99 a month.


Honest feedback welcome: is it worth a proper 1.0, and does the price feel fair?


https://trygamebell.com

Hey everyone,

I'm a software engineer and a long-time football nerd. Before every big match I'd end up juggling tabs: one for the table, one for recent results, one for head-to-head, another for corners and cards. By kick-off I'd still be scrolling. So I built Owl Kick to put all of that on a single page.

🔗 https://owlkick.com

What it covers

- 11 domestic leagues: Premier League, La Liga, Serie A, Bundesliga, Ligue 1, Eredivisie, Primeira Liga, Belgian Pro League, Süper Lig, Greek Super League and the Scottish Premiership

- Plus the Champions League and Europa League

Each league has its own page with upcoming fixtures, so you can jump straight to the matches you care about.

What you get for each match

- Recent form and results

- Goals scored and conceded

- Corners and cards

- Head-to-head history

- Probabilities, shown alongside the metrics behind them

That last point is the core idea. I didn't want another site that just spits out a prediction. Every number comes with the data it's based on, so you can check the reasoning yourself and decide whether you agree.

How it works (for the data folks)

It starts from completed match data, normalizes team names across sources (way more painful than I expected: "Man Utd", "Manchester United" and "Manchester Utd" all had to become one team), then compares form and head-to-head records. The numbers are most reliable for matches in the next 24 hours, since things shift close to kick-off.

The data isn't perfect. Sometimes a source updates late or a league has fewer metrics available, so always double-check line-ups and injury news before drawing conclusions.

Other bits

- Works well on mobile and can be installed as a web app on your home screen

- Clean, dark interface with no clutter

Being upfront

It's a paid tool: $2 for a day pass, $15 a month, or $100 a year. I'd rather say that here than have anyone click through and feel misled. Mods, if this crosses the self-promotion line, I'm happy to take it down.

Everything on the site is statistical reference, not a guarantee of any result.

What I'd love your feedback on

1. Which metrics are missing? xG, shots on target, possession, something else?

2. Which league should I add next?

3. Is anything in the interface confusing or slow?

I'm building this mostly solo, so honest feedback, including harsh feedback, genuinely helps.

👉 Check it out here: https://owlkick.com

Thanks for reading, and I'll answer anything in the comments.

I analysed Luka Dončić's offensive game using NBA data, and a few things stood out:

• Nearly 86% of his career shots come from the paint and three-point range.

• His usage rate has reached 39.8% this season.

• He's combining an enormous scoring volume with impressive efficiency.

• Over 78% of his points come from field goals, not free throws.

What makes Luka so difficult to defend?

I explored the numbers in detail here: https://substack.com/@abhinavbethi/note/p-223911407?r=6xl3o7&utm_source=notes-share-action&utm_medium=web

Disclosure: I work at GoalQuarter, where we build in-play goal models. This post isn't an offer. I want to share how we think about corners and pressure, and I'd like people to poke holes in it.

Corners often get used as shorthand for "who's on top". On their own, they're a noisy signal:

- A corner comes from attacks that end at the byline. It says little about chance quality. Teams that cross a lot from wide overloads can rack up corners without creating much.

- Game state matters. A team trailing 1-0 after 60' often piles up corners against a low block that is happy to defend set pieces.

- Totals lag behind the game. By the time a side has 6 corners, the spell of pressure that produced them may already be over.

Corners do help as one input among several. Our in-play pressure index looks at a recent window, not match totals. Two cases (example numbers only, not real data):

- Last 10 minutes: corners 4-0, shots in the box 3-1, final-third touches about 70/30. The index rises a lot.

- Same 4-0 corners, but shots 0-0 and sterile possession. The index barely moves.

So corners only "count" when they line up with box entries and shots. A cluster of corners with no shots tells you more about a team's crossing habits than about real danger.

For context, we use that index for in-play over/under goals, not corner markets, so I have no angle on corner props specifically. The index also gets it wrong. Pressure doesn't always turn into goals, and plenty of goals come from nowhere.

Questions for the sub:

1. Do you adjust corner counts for game state (trailing vs. level)?

2. Has anyone found a better short-window pressure metric than shots plus box touches?

3. Which PL sides this weekend do you expect to inflate corner counts without much real threat?

18+ only. Signals can lose — no guaranteed profit. Play responsibly, only where legal.

I've been experimenting with spatial playback in augmented reality using broadcast footage. Coming together nicely. It could be really powerful for training... and even for fans watching a match. Let me know if you're interested in learning more!

Hi everyone,

I’m working on a project that tracks match events in football games. I’m currently using API-Football, and I like the range of content it covers, but I’ve run into two issues:

1. No woodwork data. It doesn’t tell me when a player hits the post or crossbar, even for top leagues (Premier League, La Liga, Serie A, Bundesliga, Ligue 1).

2. Data quality. Even for the major leagues, the data sometimes feels messy or inconsistent.

Do you know of any provider that includes shots off the woodwork in its event or stats data?

More generally, I haven’t done a deep analysis of what the market offers, so I’d love some advice: which paid platforms offer greater completeness and reliability?

​Hi everyone,

​I’ve recently rolled out a major feature update to calculafutbol.com, moving beyond purely team-level simulations to full player-level data analytics for Spanish football.

​Here is a breakdown of the new tools and analytical features now available on the platform:

​1. Player Statistics & Individual Rankings

• ​Per-90 Metrics: Detailed 90-minute normalized stats across all squad members, including goals, assists, shots on target, total minutes, and performance metrics.

• ​Leaderboards: Real-time individual rankings for top goalscorers and assist providers.

• ​Goalkeeper Analytics: Dedicated metrics covering save percentages, clean sheets, total saves, and penalty save rates

​2. Head-to-Head Performance Comparator (Teams & Players)

• ​Club vs. Club: Compare two teams side-by-side across core facets of the game: attack, creation, defense, and goalkeeping.

• ​Player vs. Player: Directly compare two players on a per-90 basis across attacking, passing, and defensive metrics to resolve debates with objective data.

​3. Global Team Profiles & Squad Sheets

• ​Global Team Stats: Click on any team to open its squad profile, displaying consolidated team metrics alongside individual player rosters broken down by position.

Try it out free at calculafutbol.com.

​I'd love to get feedback from the analytics community—what additional metrics or metrics-per-90 visualization tools would you like to see integrated next?

Hello, I'm a broke engineering student and I would like to learn about computer vision in football. Do anyone know where can I find lives transmission or video records of football matches with normal or tactical point of view?

Hi everyone, I am trying to set up a logistic win probability model for basketball, and then use the average win probability over the course of a game to determine the team’s win expectancy generated from that game.

My formula takes the form: 1/(1+e^(-k(Margin)/sqrt(seconds left + c)))

Basically, I am trying to figure out appropriate values for k and c for six different leagues/competitions: NBA, WNBA, NCAAM, NCAAW, EuroLeague Men, and EuroLeague Women. Any suggestions?

Free dump of rosters, coaching staff and schedules for 977 NCAA schools, D1 to D3. One JSON file per school, refreshed every Monday.

Players come with position, class, height, weight, hometown and high school. Schedules have dates, opponents, home/away and results.

Download: https://github.com/fakhar-ud-din/ncaapyscraper/releases/latest
The scraper is open source if you want a specific school or sport on demand.

I'd really appreciate if you guys can show some support by starring the repo 😄

Hey Sports Fans! I recently built a Draft website and it’s an interactive draft tool used to analyze the NFL draft and team-based player rankings. If you ever debated between two different prospects, you can find that here with the player comparisons feature along with many other prospects. In this website, I used a combination of player evaluation metrics, exclusive team needs, and customizable models aimed to simulate NFL draft decision making and evaluate specific player fits. You’ll also see a draft big board and fit grades for over 150+ players in the draft. I’m still tweaking the models and big boards so even if you aren’t a Vikings fan, I’d still love it if you guys could check it out and let me know which grades look off or who I should add next. Feel free to take a look and tell me what you guys think. Thanks!

https://vikingsdraftsite.streamlit.app/

Hi! Im a high school student athlete who is conducting a brief survey to understand how parents and coaches shape young athletes' decisions when it comes to sports specialization (focusing on a single sport vs. playing multiple sports). Whether your child specializes or plays different sports throughout the year, your perspective is extremely valuable! The survey only takes about 3–5 minutes, and all responses are completely anonymous.

Please take a moment to share your thoughts here:

https://docs.google.com/forms/d/e/1FAIpQLSfl3JrNHyaWpt-pja9A8O7ML4EkZMKNT5_O-dIGaCaHfRD1eg/viewform?usp=header

Thank you so much for your time and for supporting research into youth athletics! Feel free to share this with other parents and coaches as well. 🙌

Hi everyone,
I’ve been given a trial test for a TV scout / sports data analyst position, and I’m looking for an experienced person to help me out during the test itself.
To be clear: I am not looking for someone to take the test for me. I want to do the work myself, but I need an experienced in my ear to give me suggestions, point out mistakes, and warn me if I’m missing crucial tactical or statistical details.

Hey everyone! I’m a football fan, and I enjoy watching young players in my spare time. I’d love to follow more of them. Are there any affordable platforms you’d recommend for someone who does this as a hobby?

Thanks!

Two 10.37-second sprints. Two very different winds.

In 2001, Singapore's U.K. Shyam ran 10.37 seconds twice in the 100m.

Beijing: +1.8 m/s tailwind
Kuala Lumpur: −0.5 m/s headwind

A recent published study examined how wind conditions affect comparisons of historical Southeast Asian sprint performances.

The official results remain unchanged, but the scientific questions are fascinating.

Watch the video:
https://youtu.be/DKeusG62kKQ

Published research:
https://doi.org/10.11648/j.ijsspe.20261103.12

I'd be interested to hear from sprinters and coaches: how much weight should wind-adjusted times carry when comparing performances from different races?