Building an AI that watches rugby

https://nickjones.tech/ai-watching-rugby/

by reddavis • 1 year ago

87 45 1 year ago

nickjones.tech

xnx• 1 year ago

Better title: "LLM OCR on Rugby screenshots to read score and clock"

djtango• 1 year ago

I don't quite get how diffing frames allows you to find the scores.

TFA mentions comparing a frame with and without - but how do you generate that frame without? If you can already do it, what's useful about doing that?

barbegal• 1 year ago

I think the text is wrong, it's diffing two frames and the areas that are the same are where the scorebaord is as this doesn't change between frames but everything else does.

nirvael• 1 year ago

I was also confused by this. I think you're right, but in the original text they specifically mention a 'static background' that they remove, so it's not just a simple 'wrong way round' error, it's a fundamental misunderstanding of what's happening. Makes me wonder if the author actually knew what they were doing, or just using an LLM to vibe-code everything.

sebastiennight2• 1 year ago

He's diffing the frames, and then the only pixels that stay the same are the UI, from which he doesn't directly get the UI (see the example, it's illegible) but he can extract the POSITION of the UI on the screen by finding all the non-red pixels.

And then he does a good ol' regular crop on the original image to get the UI excerpt to feed the vision model.

itissid• 1 year ago

Why does yolo not work?

mon_• 1 year ago

Why the focus on scorekeeping? I feel like an AI model is overkill here, when you have text-based sources readily available such as news apps, Twitter feeds, and apps such as Livescore which would be easier and cheaper to scrape. They probably cover more matches that aren't televised too.

I'd be curious to see what useful insights could be gleamed from the match commentary. You have the main commentator giving play-by-play objective reporting and then a 'colour' commentator giving some subjective analysis during breaks in play. I bet there's a lot of interesting ways this could be used.

dmurray2• 1 year ago

The only interesting part of the model's output was

{ "current_play": "ruck", }

So the vision model can correctly identify that there's a ruck going on and that the ball is most likely in the ruck.

Why not build on this? Which team is in possession? Who was the ball carrier at the start of the ruck, and who tackled him? Who joined the ruck, and how quickly did they get there? How quickly did the attacking team get the ball back in hand, or the defending team turn over possession? What would be a good option for the outhalf if he got the ball right now?

All of these except the last would be straightforward enough for a human observer with basic rugby knowledge going through the footage frame by frame, and I bet it would be really valuable to analysts. It seems like computer vision technology is at a stage where this could be automated too.

MuffinFlavored• 1 year ago

ESPN has play by play stuff for free like this on their website for some other sports

not sure if it is done by a human or not

curious how “an AI can do it” yields much difference in terms of result for the casual watcher

thom3• 1 year ago

Multiple companies sell Rugby data of various levels of granularity. I don't know if rugby has all the toys (i.e. full tracking outside of wearables) that soccer or American football have because there's less money sloshing around.

ookdatnog2• 1 year ago

The AI's job as described in this article is two-fold:

- The relatively trivial task of extracting textual data from the screen.

- The task of obfuscating that they're publishing other people's work as their own.

When I clicked the article I assumed they'd try to automatically construct analysis of the game by using AI to analyze frames of the game, but that's not what they are doing. They are extracting some trivial information from the frames, and then they process the audio of the referee mic and commentary.

In other words, the analysis has already been done by humans and they just want to re-publish this analysis as their own, without paying money for it. So they run it through an AI because in today's legal environment this seems to completely exempt you from copyright infringement or plagiarism laws.

brookst3• 1 year ago

Perhaps the most surprising thing about the whole LLM revolution is how quickly attitudes about IP have shifted in the HN and similar communities.

A few years ago, media companies were rent-seeking parasites who leveraged the jack-booted thugs of law enforcement to protect an artificial monopoly using IP laws that were massive overreach and contrary to the interests of humanity.

Today, suddenly, media companies are pillars of society whose valuable contributions must be protected from the scourge of theft by everything from VC backed AI companies to armchair hackers who don’t respect the sanctity of IP.

It’s amazing how mutable these principles are. I’m sure plenty of people are somewhere between the two extreme, but the shift is so dramatic that I am 100% sure many individuals have completely revised their opinions of IP companies based largely on worries about their own work being disrupted.

At the very least it should create some empathy for the lawyers and business folk we all despised for their rent-seeking blah blah blah. They were just honestly espousing the positions their financial incentives aligned them to.

walthamstow• 1 year ago

I'm not a rugger bugger but every 5 seconds doesn't really seem like often enough to be taking screenshots. In soccer anyway, a lot can happen in 5 seconds.

conductr• 1 year ago

My american football brain had the same reaction. Many of the most pivotal plays are replayed in slow motion as commentators and spectators debate on what actually happened and if the refs got the call right. Also, the average play (ie. 'down') is 4-5 seconds, so not nearly enough data to determine what is going on.

dncornholio• 1 year ago

So Rugby is missing a lot of data beside the scoreline, so they created an AI that can extract the scoreline.

patapong• 1 year ago

I want AIs that clean my apartment while I watch rugby, not AIs that watch rugby while I clean the apartment. ;)

In seriousness, this is a cool project and show how sophisticated analysis LLMs can do in a plug and play manner. They may not always be the best solution but a fantastic baseline that can be deployed and adapted to a usecase in less than an hour.

petesergeant• 1 year ago

We can’t hire analysts to watch every match and enter data manually.

I'm surprised there's not enough fans willing to do that if you could gamify it.

securingsincity• 1 year ago

This is a position in baseball. https://www.wbur.org/news/2025/03/30/fenway-park-boston-base... Here's a radio piece about the official fenway park score keeper from two weeks ago

goeiedaggoeie3• 1 year ago

Reading the scoreboard from a TV screen and selling that data is restricted in many jurisdictions. This work is pretty naive I think.

brookst3• 1 year ago

Has there ever been a hacker whose top priority is ensuring compliance with every regulation in every jurisdiction worldwide?

stronglikedan• 1 year ago

Good thing they're in only one jurisdiction, not many.

hash872• 1 year ago

I don't think it's possible to be in compliance with every law in every jurisdiction simultaneously. There are over 300,000 federal laws in the US, and apparently no one knows how many laws each of the 50 states has. That's 1 of the world's 195 countries

arathis• 1 year ago

Ugh. You’re the worst

FiberBundle2• 1 year ago

I'd say it isn't in the US though, at least there's precedent that makes me think that: https://en.m.wikipedia.org/wiki/National_Basketball_Ass%27n_...

goeiedaggoeie3• 1 year ago

I think you misunderstand that case "compiled its scores and statistics by employing people to listen or watch the games, then enter the scores on the computer which transmits the scores to STATS' on-line service, to be sent out to anyone using a SportsTrax pager.[1]"

Notice how they watched the game and got the statistics like that. The restrictions are about using the scoreboard and the data displays and reselling/commercialising that data. It is however legal to watch the game and compile and distribute your own stats due to the game entering public domain.

Due to this many betting companies and data collection companies have to pay people to watch the game vs just scraping the scoreboard (which is the context from which I learnt about this). ironically at venue OCR is a common way to get scoreboard data.

sebastiennight2• 1 year ago

I love that as soon as he writes,

The plan was simple.

You know you're in for a funny read.

More seriously though, the JSON example from a vision language model is interesting but does not take into account how much extrapolation (hallucination) the model will insert over time.

For instance, even if not visible in the image, your VLM will probably start inserting details (such as the color of the team's jersey) based on knowing the team's three-letter identifier.

So the reliability of the system will go down over time, and it probably compounds if you're using some of that info to feed further steps in the loop.

hummuscience• 1 year ago

The moment I started reading this, I got reminded of this recent study: https://arxiv.org/html/2503.10212v1

The scope is a bit different. The study uses an LLM to interpret pose estimation data and describe the behavior in each frame. The output is text which can be used to create embeddings of behavior. As someone who works in ethology, that's a clever (but maybe expensive) idea.

I think the author could use something similar. With multi-person pose estimation models.

chrsw• 1 year ago

Does this mean there's probably AI that's already watching high profile football (soccer) matches?

thom3• 1 year ago

Depends on your definition of AI, but yes, lots of them, and not just the high profile matches.

damnitbuilds• 1 year ago

TL;DR: It extracts the score from the video and gets text from the commentary in the audio.

I was hoping for more.

disjunct• 1 year ago

I wrote a similar script that used a TV tuner during the last World Cup. Since I had an ATSC source, I was able to just pull the CTA-708 captions directly and with little delay.

numpad0• 1 year ago

aw. I thought this would be about an AI cat that makes wrong commentaries that you can make pointless arguments against. There should be one.

cewl123• 1 year ago

I want AI that does my job while I watch rugby

rfdearborn• 1 year ago

Sending a full-resolution screenshot every five seconds gets expensive fast.

For now.

4ndrewl• 1 year ago

My observation is that watching Rugby on TV is no the same as watching a Rugby match. You're watching something where choices have been made around what you're to see, so your model is already restricted in what it can see.

You really need to take a 'full pitch' feed directly from the venue, rather than what is broadcast.

Building an AI that watches rugby

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