Football Pad
Simulate football matches with your own tactics
What it does
Simulate football matches using real teams, leagues, and player data. Football Pad uses real lineups, tactical attributes, and AI-driven analysis to model match outcomes. Test strategies, compare teams, and explore data-driven predictions before games happen. Built for fans, analysts, and those who want deeper insight into match results.
Does the same job
all alternatives →
- IMI made a football/soccer formation and squad app2024 · apps.apple.com · ▲17
Inspired by watching my sons coach using a carry around whiteboard, plus also starting to coach my wifes over 30s womens amateur team I wrote a mobile app for amateur football/soccer coaches. It allows you to add your players information, manage substitutions during games (who's on the field, whos on the bench) as well as drag around players into formations, draw tactics on the screen and share using the IOS share features to email, messages etc. Build your tactic and share it with the team between games. It's free and its designed to just be an easy thing for coaches to take around…
tactica.14d ago · app.tacticafootball.co.uk · ▲2Football intelligence that shows you why, not just what.
Football PredictorMay 2026 · football.edccc.cn · ▲1AI football predictions with odds and accuracy tracking
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, May 2026
the whole month →
Parallel agents, diff reviewer, and multi-model comparisons
Dev tools · May 2026 · kilo.ai
- NW
Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
Life & fun · May 2026 · github.com
- FM
Dev tools · May 2026 · github.com