How AI Agents Are Transforming Sports Prediction Markets

Decentralised News

Read the complete guide: https://decentralised.news/ai-agents-transforming-sports-prediction-markets  Best crypto exchanges, wallets and trading tools: https://decentralised.news/ecosystem/  The future of sports betting is autonomous — and it’s happening now. In this deep-dive, Decentralised News explores how AI agents like Billy Bets, Sire, DWAIN, PredictBase, and Sportstensor are revolutionizing the $250 billion prediction market industry.  From Coinbase Ventures-backed Billy Bets building self-learning betting terminals, to SportsTensor’s AI miner network and Virtuals Protocol’s Base-native agent ecosystems, this video unpacks how intelligent agents are reshaping the way predictions, odds, and liquidity flow across Web3.

Transcript

00:00Today, I want to talk about AI agents that are transforming sports prediction markets.

00:05So when we look at these prediction markets, where participants actually are betting on outcomes of future events,

00:11they've always been hailed as efficient aggregators of collective information.

00:17So you can see kind of companies argue that these markets often outperform polls

00:24because participants actually put skin in the game and express real beliefs, right?

00:29So that's why we've seen, especially Kalshi and all of these prediction markets really become hot in the financial markets

00:36when it comes to either predicting when there's going to be rate cuts or rate hikes or whatever predictions that people are interested in.

00:43They're really using these platforms as a measure of sentiment and probability.

00:48So now this is like a new paradigm, this emerging AI agents that just don't make predictions

00:54so that they actually enter the trade, optimize, kind of autonomously,

00:59blurring the lines behind or between kind of like where, you know, let's say you're forecasting and acting.

01:05So things are moving from having prediction pundits to agents

01:12and sports betting is literally the final, the natural frontier.

01:16Sports markets are uniquely suited for agent experimentation.

01:19Data richness and cadence games happen constantly, right?

01:25So these outcomes are discrete and verifiable odds and wager flows offer kind of high frequency signals as well.

01:34You also have the transparency of blockchains there with most of these modern prediction markets like Polymarket,

01:40which are public and agents can observe entire order books and bet flows and slippage,

01:46effectively reading the house's logbook, then you've got high liquidity, high stakes,

01:51the sports betting industry handling about $250, I mean $50 billion annually,

01:57yet kind of an agentic betting is still very, very minimal, right?

02:02So this is pretty much where you're seeing kind of new entrants like BillyBets aiming to exploit this massive frontier

02:10that could really kind of come with so much potential.

02:13So BillyBets, which is built on base chain Coinbase's L2,

02:17recently closed a $1 million pre-seed funding round led by Coinbase Ventures,

02:21stating the mission is to build autonomous agent layers over prediction markets,

02:26polymarket, overmarket, to surface confer, edges, route bits, optimize sequencing,

02:34and deliver live ROI tracking via wireless native execution.

02:39So Billy's terminal UI allows commands like show me plus EV, NFL props tonight, for example,

02:47converting natural language orders into bits, right?

02:50So backers believe that over time, smart bettors will use agents,

02:54especially in fast-moving prediction markets.

02:56Another foundational piece in this stack is the SpotTensor, right?

03:01Which is an incentive mechanism designed to reward prediction signals from miners or agents based on both volume and arrow ISO agents

03:10that bet big but wrong get penalized, and agents who bid prudently and profit get rewarded.

03:16So they have a token, SN41, which is live on DEXs via the BitTensor ecosystem, trades publicly as well.

03:24So combining the signal infrastructure with execution layers, new agentic prediction stacks are actually starting to form here.

03:33So you have this kind of anatomy of these prediction agents.

03:38People want to know, like, what do these agents actually do, right?

03:41So you have the data ingestion and the actual features where they harvest live odds and volume movement,

03:47of course, historical outcomes, social sentiment, injury news, weather, et cetera, right?

03:53Signal modeling, prediction models, supervised ensemble, RL, estimating probability and outcomes,

04:02age over market swords, calibration and risk sizing is also what they do,

04:07converting these probability estimates into bettable sizes, Kelly criterion, utility optimization, volatility control,

04:15all of these things, execution and routing, very, very important because they can actually submit orders across markets and paths,

04:22you know, minimizing cost and slippage.

04:25And then they also have the feedback in the lending aspect where, you know, after these outcomes settle,

04:30you can update the model, you can discard weak strategies and adapt regime shifts, all right?

04:36So you've got reputation and token alignment as well.

04:38So some agents must stake, let's say, token collateral or maintain a track record to be deemed trusted on,

04:45and this is kind of spot tensors and center structure, right?

04:49These steps actually run continuously.

04:51Agent effectively becomes age-seeking participants in these prediction markets,

04:55competing with other agents and humans, of course, operating faster and more systematically, though.

05:00That's what the real advantage is.

05:01And obviously, the real deployments to token ecosystems, BillyBits with the token,

05:05as of now, the token trades on decentralized exchanges like Iniswap V2 on base.

05:13You compare it with virtual, for example.

05:16Unlock staking, loyalty access, profit sharing features, day support tensors, Inis41, real utility,

05:24Sire, you know, another agent that's really good there.

05:27I have a little bit of sighting myself, prediction, votes, routing, liquidity, day reports suggesting that this is deployed across base

05:35and agents are balanced up to 70% of the book liquidity for some sport events.

05:40So these tokens actually, and these models actually embed kind of alignment.

05:44Agents need stake, uplift tokens, generating value and capturing fees and commission flows

05:49and kind of having these strategies that they're operating.

05:52But, of course, there's always risks and challenges along the way, of course, overfitting and regime shift.

05:57You've got adversarial behavior, right?

06:00Spoofing an agent that reads bet flows could be manipulated by actors who inject dummy bets, right,

06:05to mislead the signal models.

06:07So it's very, very tricky here.

06:10Execution slippage as well.

06:11Equity contrains things.

06:13Think about the governance, the trust, the regulatory exposure.

06:16And then, I mean, I think at the end of the day, the volume is just going to keep going up with these agents,

06:21kind of really taking up volume in the sports betting markets and prediction markets

06:26and these hybrid models where there's combining human and agent portfolios,

06:31kind of first setting strategies and executing that way,

06:35having proof of performance in the transparency,

06:37especially when you've got on-chain base using blockchains,

06:40cross-domain expansion from sports to politics, climate events, macro agents.

06:45And, you know, kind of a day to generalize and really take things to the next level.

06:49So if you want to learn more, guys, make sure you keep following us.

06:51Go to decentralize.news.

06:53Check out the guide that we actually did on the main site.

06:55And if you want to learn more about the best cryptocurrency exchanges,

06:57the best wallet, best trading tools, best tokens, best AI agents,

07:02go to decentralize.news.

07:03Peace.

07:04Love.

Category

Transcript

Be the first to comment

Recommended