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Top Mistakes to Avoid When Betting on Cricket

By
TI Partners
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0

Cricketer wagers pull in tons of enthusiasts since they mix insight with gut feelings and thrill. Yet super devoted watchers might still slip up badly once feelings override clear thinking. Each round, how the field plays, or shifts in team setup, influences results – while just one rash decision could flip a solid edge into defeat.

So sharp punters stick to a plan. They check numbers, track how players are doing, yet handle dangers on purpose. If you’re keen to level up, solid spots such as the Mel bet app give deep info, live alerts, also safe features helping clearer choices. Not about tossing down extra wagers – just making each one count more.

The Most Common Betting Mistakes in Cricket

Cricket might seem easy to guess at first glance – yet the way it plays out turns things upside down fast. Plenty of punters stumble into silly mistakes, which mess up their results over time. A big cause of these mistakes? Too much confidence. Supporters usually think knowing about squads or star athletes helps them get ahead – still, numbers keep proving that wrong. Staying focused plus doing the groundwork? That’s what actually works.

Look at cricket odds closely – little things like who won the toss or if it might rain can shift chances fast. Just like with football betting sites, staying sharp matters just as much here. One needs time, homework, and while keeping cool under pressure to win steadily.

Common Cricket Betting Mistakes to Watch Out For

Mistakes happen – even to experienced gamblers. Check out these common blunders killing success and eating into winnings:

  1. Failing to check team updates: When players get hurt, take breaks, or aren’t in the starting eleven, everything about the game can change.
  2. Betting without checking facts? Guessing leads to losing cash – common in every kind of cricket game.
  3. Trying to recover losses often leads to impulsive decisions, which fuel more reckless betting over time.
  4. Favorites get too much hype – so smart plays sometimes hide with the outsiders.

These errors come from the same place – feelings instead of facts. Take your time, look at the numbers, also keep hopes realistic, so you win more often.

Before diving into complex number-crunching or risking big money, keep in mind – cricket runs on shifting factors like weather, game plans, or how players feel; these shape results way more than data ever could.

Understanding Risk and Reward

Each wager hides some kind of tale. Picking winners isn’t just about what you choose – your reasons matter more than you think. Being able to judge danger keeps results steady as time goes by.

Risk Type Example Scenario Risk Level Recommendation
Emotional Betting Betting when you’ve just lost High Pause a bit, then tweak your plan
Overconfidence Skipping info once you win a few rounds High Focus on learning through hands-on activities
Blind Favorites Promoting leading squads by default Medium Check worth but also chances
Underdog Strategy Chasing improbable wins Medium Just a tiny bit – no more than a sliver here or there

Just like seen before, feelings can mess things up worse than poor chances. Top gamblers rely on handling risk like a hidden edge – betting less, yet hitting harder when they do.

Knowing about risks? That’s when you slow down. Each game brings chances – though some just aren’t worth chasing.

Using Technology to Improve Betting Decisions

Folks today can check games more clearly using new tech gadgets. These digital helpers use smart systems to spot patterns – like how players are doing, what the field’s like, or how weather affects play.

Take prediction tools – they use old game data, sometimes from thousands of matches, to guess what might happen next. So placing bets isn’t just a gut feeling anymore, but something closer to informed guesses. As algorithms watch players right when they play, folks who wager get a sharper edge before the match starts or while it’s still going.

Same as in other games, the aim isn’t about killing fun – instead, it’s choosing better moves using what numbers actually suggest.

The Game Rewards Patience and Discipline

Betting on cricket isn’t about quick wins – it’s playing the long game. Each match teaches something, if you’re open to it. When you swap gut feelings for solid reviews, fans turn their love into smarter choices.

Info’s easier now thanks to tech, yet staying focused wins in the end. Dodging common errors kicks off sharper bets. When feelings mix with facts just right, cricket turns from a sport into a mindful path full of learning and gains.

From Dominance to Diversification: Stablecoins Surge Globally For A Variety of Use Cases

By
Ojukwu Emmanuel
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0

Stablecoins are entering a new era. Once dominated almost entirely by a few major players and primarily used for trading, the global digital asset is now undergoing a profound shift moving from concentration to diversification.

Regulatory clarity in key jurisdictions, rising institutional participation, and expanding real-world applications have opened the door for a broader mix of stablecoins to thrive. Today, the U.S. dollar-denominated stablecoin market, which makes up around 99% of the global stablecoin market, has grown to $225 billion, accounting for roughly 7% of the broader $3 trillion crypto ecosystem tracked by J.P. Morgan Global Research. There are reports that stablecoins could grow to $2 trillion by the end of 2028.

With regulatory clarity from frameworks like the U.S. GENIUS Act, MiCA (EU), and VARA (UAE), its passage alone has sparked heightened institutional interest. With the GENIUS Act signed into law on July 18, 2025, stablecoin issuance and related activities are formally brought into the federal regulatory perimeter and are poised to have a key role in mainstream finance. In the European Union, the MiCA stablecoin framework has already reshaped the market, enabling the introduction of licensed euro-referenced stablecoins such as EURC.

Despite these regulatory advancements, on-chain data shows that stablecoin transaction activity is still overwhelmingly led by USDT (Tether) and USDC. From June 2024 to June 2025, USDT processed an average of about $703 billion monthly, reaching a peak of $1.01 trillion in June 2025.

USDC’s monthly volume fluctuated significantly during the same period, ranging from $3.21 billion to as high as $1.54 trillion. These figures underscore their continued dominance in crypto market infrastructure, especially for institutional activity and cross-border payments.

While Tether and USDC remained massive but volatile, Chainalysis report revealed that smaller stablecoins including EURC, PYUSD, and DAI recorded rapid acceleration. EURC, for example, grew by nearly 76% on average each month, rising from roughly $42.5 million in June 2024 to over $7.4 billion in June 2025 and further to $9.2 billion in July 2025. PYUSD also showed strong adoption, scaling from about $785 million to $3.74 billion by June 2025 and reaching $4.8 billion the following month.

Regionally, market behavior has begun to diverge. USDC’s growth appears strongly correlated with U.S. institutional payment infrastructure and regulated transaction corridors. EURC’s rising prominence suggests growing European interest in euro-denominated digital assets—likely propelled by MiCA compliance and regional fintech expansion. PYUSD’s upward trajectory may reflect increasing retail and consumer appetite for highly regulated, alternative stablecoins.

Financial Institutions Are Embracing Stablecoins

In recent years, financial institutions around the world have moved from cautiously observing the stablecoin market to actively experimenting with it, and in some cases, fully integrating stablecoin-based products into their operations.

This shift marks a major milestone in the maturation of digital finance, as stablecoins evolve from speculative trading tools into powerful instruments for payments, settlement, liquidity management, and cross-border transactions.

Notably, traditional banks, fintech companies, payment providers, and even global financial infrastructures are now exploring how stablecoins can enhance efficiency, reduce transaction costs, and unlock new forms of financial innovation. Their experiments range from internal settlement pilots to customer-facing products designed to offer faster, cheaper, and more transparent financial services

This period also marked heightened institutional engagement with stablecoins. Stripe, Mastercard, and Visa have rolled out products allowing users to spend stablecoins through familiar payment rails. Likewise, MetaMask, Kraken, and Crypto.com expanded card-linked stablecoin functionality. Merchant-side adoption accelerated as Circle and Paxos partnered with firms like Nuvei to streamline stablecoin settlement.

Meanwhile, traditional banking giants—including Citi and Bank of America—signaled interest in stablecoin-related services, with some even hinting at the possibility of launching their own tokens. Taken together, these developments point to a stablecoin ecosystem that is broadening and becoming more specialized.

Conclusion

Stablecoins are no longer just a mere trading digital asset, they have become programmable interoperable money powering payments, settlements, and financial automation across industries.

As regional use cases evolve and regulatory clarity improves, global stablecoin markets may continue shifting toward a more diversified landscape, one where local demand increasingly shapes global transaction flows.

Luma AI Raises $900m as Saudi-Backed Humain Leads Funding Push, Unveils Massive AI Supercluster Plan

By
Samuel Nwite
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0

Video-generation startup Luma AI has secured $900 million in fresh funding, a blockbuster round led by Humain, a new artificial intelligence company owned by Saudi Arabia’s Public Investment Fund.

The move places both companies squarely in the race to build next-generation multimodal AI systems and the computing muscle needed to run them.

The financing was announced at the U.S.-Saudi Investment Forum on Wednesday and included participation from AMD’s venture arm, along with existing backers Andreessen Horowitz, Amplify Partners, and Matrix Partners. CNBC confirmed that the funding round values Luma at more than $4 billion, a steep climb for a company built around “world models” that learn from video, audio, images, and text.

Luma CEO Amit Jain said the capital will significantly accelerate the company’s ability to train and deploy these models, which he describes as essential for AI systems that operate in the real world. Speaking in an interview with CNBC, Jain said Luma’s approach goes beyond traditional large language models, which are limited to text training.

“With this funding, we plan to scale and accelerate our efforts in training and then deploying these world models today,” he said.

The company has been ramping up product development, releasing Ray3 in September — a reasoning video model capable of interpreting complex prompts to generate video, audio, and images. According to Jain, Ray3 currently benchmarks above OpenAI’s Sora 2 and performs around the same level as Google’s Veo 3, two of the most advanced commercial video-generation systems.

The Saudi-led push behind the funding underscores the kingdom’s ambition to position itself as a global hub for artificial intelligence. Humain, launched in May and led by Tareq Amin, the former chief executive of Rakuten Mobile and ex-head of Aramco Digital, aims to build end-to-end AI infrastructure and model capabilities that can compete globally.

The partnership between Luma and Humain includes one of the most aggressive compute buildouts announced so far. Both companies will collaborate on Project Halo, a 2-gigawatt AI supercluster planned for Saudi Arabia, which Jain described as one of the world’s largest GPU deployments. The move comes amid a global scramble for advanced chips such as Nvidia’s AI accelerators, with big tech companies racing to assemble the data-center horsepower needed to train larger and larger models.

Saudi Arabia’s investment follows similar moves from major U.S. tech players. Meta announced in July that it would build a 1-gigawatt supercluster known as Prometheus, and Microsoft deployed the first GPU cluster using the Nvidia GB300 NVL72 platform in October.

“Our investment in Luma AI, combined with HUMAIN’s 2GW supercluster, positions us to train, deploy, and scale multimodal intelligence at a frontier level,” Amin said in a statement. “This partnership sets a new benchmark for how capital, compute, and capability come together.”

The collaboration will also support Humain Create, an effort to build sovereign Arabic-language AI models trained on regional data sources. Jain said the initiative includes ambitions to develop the world’s first Arabic video-generation model, addressing a long-running issue in AI training: non-Western cultures and languages are not properly represented in most of today’s foundation models.

“Since most models are trained by scraping data from the internet, countries outside the U.S. and Asia are often less represented in AI-generated content,” Jain said. “It’s really important that we bring these cultures, their identities, their representation — visual and behavioral and everything — to our model.”

Luma’s rapid growth has also drawn scrutiny. Dream Machine, its flagship text-to-video platform, faced allegations earlier this year of reproducing copyrighted material. Jain said the company has deployed strong safeguards to prevent unwanted content generation and continues to refine those systems.

“Even if you really try to trick it, we are constantly improving it,” he said. “We have built very robust systems that are actually using models we trained to detect them.”

The latest round cements Luma AI as one of the most heavily funded startups in the video-AI race and underlines Saudi Arabia’s deepening push into artificial intelligence as it spends aggressively to diversify its economy.

Hyperliquid Treasury Merger Vote Delayed, Postponing $888 Million Deal

By
Paul Ugbede Godwin
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0

The shareholder vote on a proposed merger to create Hyperliquid Strategies—a digital asset treasury (DAT) focused on accumulating and holding HYPE tokens, the native asset of the Hyperliquid decentralized perpetuals exchange—has been postponed by two weeks.

The delay, stems from insufficient voter turnout despite strong support from those who have participated. The deal, first revealed in July 2025, involves Nasdaq-listed Sonnet BioTherapeutics merging with Rorschach I LLC an entity tied to Atlas Merchant Capital and Paradigm to form Hyperliquid Strategies Inc.

The new entity would hold approximately 12.6 million HYPE tokens valued at around $583 million, plus $305 million in cash, for a total estimated value of $888 million at announcement. The firm aims to raise up to $1 billion and trade on Nasdaq under a new ticker, providing public market exposure to HYPE.

Over 95% of votes cast so far favor the merger, but it requires more than 50% of all outstanding Sonnet shares to approve. David Schamis, CEO of Hyperliquid Strategies and co-founder of Atlas Merchant Capital, expressed confidence in reaching the threshold by the new deadline of December 2, 2025, and urged shareholders to vote promptly.

This comes amid a cooling DAT trend, where new treasury announcements have slowed. Backers include major players like Paradigm, Galaxy Digital, Pantera Capital, and D1 Capital. Post-merger leadership would feature Bob Diamond (Atlas co-founder) as chairman and Schamis as CEO, with additional board members like former Boston Fed president Eric Rosengren.

A successful close would mark one of the largest publicly traded crypto treasuries centered on a single DEX token, blending traditional finance with DeFi. However, recent HYPE price dips have slightly eroded the deal’s perceived value.

Schamis shared the update on X, noting the frustration but optimism: “Annoyingly we have to delay the shareholder vote for two weeks… We are confident that we will be able to achieve this by the December 2 date.”

Standard Chartered Says Bitcoin Sell-Off Likely Over, Eyes Year-End Rally

In a research note dated November 18, 2025, Standard Chartered’s head of digital asset research, Geoffrey Kendrick, declared that Bitcoin’s recent 30% correction—dropping BTC below $90,000 from its October high above $126,000—is likely complete.

He views this as the third major pullback since the U.S. spot BTC ETF launch last year, mirroring prior patterns, and anticipates a rebound as the base case. Kendrick points to capitulation signals, including: MicroStrategy’s modified net asset value (mNAV) ratio hitting 1.0 parity between market cap and BTC holdings value, a “zero” level indicating seller exhaustion.

On-chain data showing realized BTC loss margins at -16% below the typical -12% capitulation threshold. Technicals like the RSI at 26 deeply oversold, the lowest since BTC’s $76,000 bottom earlier in the cycle.

A year-end rally remains the baseline scenario, potentially disproving persistent halving-cycle theories. Kendrick previously forecasted $200,000 by end-2025 but declined to reaffirm it amid the dip. He emphasized blockchain adoption trends, predicting all global transactions will eventually settle on-chain.

The sell-off intensified on-chain stress and ETF outflows, with $335 million in BTC derivatives liquidated in a single day. Trading volume doubled, but Kendrick sees these as exhaustion rather than further downside. Analysts note BTC must reclaim $95,000–$100,000 to avoid structural weakness.

Policy shifts or deeper corrections could delay recovery, though seasonal Q4 strength in crypto supports optimism. This bullish take contrasts with recent volatility but aligns with historical post-correction rallies, offering hope for investors eyeing December gains.

OpenLedger Launches OPEN Mainnet to Revolutionize AI Data Attribution and Creator Compensation

By
Paul Ugbede Godwin
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0

OpenLedger—a blockchain infrastructure project backed by Polychain Capital—officially launched its OPEN Mainnet, marking a significant step toward addressing one of AI’s most pressing issues.

The lack of fair attribution and compensation for data contributors. This launch introduces a decentralized network designed to trace AI data lineage on-chain, ensuring creators, researchers, and domain experts are automatically rewarded based on how their contributions are used in AI models and outputs.

The move comes amid growing debates over AI “data theft,” where training datasets are often scraped without credit or payment, and positions OpenLedger as a foundational layer for “Payable AI.”

OpenLedger was founded in 2024 by Pryce Adade-Yebesi, Ashtyn Bell, and Ram Kumar with prior exits including Utopia Labs, acquired by Coinbase, OpenLedger is an EVM-compatible Layer 2 blockchain tailored for AI development.

It combines blockchain’s transparency with AI’s computational needs to create a “Data-as-a-Shared-Service” ecosystem. Key components include Permissionless, domain-specific datasets curated by community nodes for specialized AI training.

AI Studio and OpenLoRA: Tools for building and serving models with up to 99% cost reduction compared to traditional methods.

ZK-Verifiable Execution: Ensures secure, tamper-proof computations with sub-second finality.

The project raised $8 million in seed funding in July 2024, led by Polychain Capital and Borderless Capital, with participation from HashKey Capital and angels like Balaji Srinivasan and Sandeep Nailwal.

This capital has fueled rapid development, including an incentivized testnet that ran from December 2024 to February 2025, attracting over 6 million nodes, 25 million transactions, and 20,000+ models deployed.

At the heart of OPEN Mainnet is the Proof of Attribution (PoA) system, a blockchain-based mechanism that logs the entire “lineage” of AI assets—datasets, models, and agents—on-chain. This creates an immutable trail for every AI output, allowing it to be traced back to its original contributors.

When an AI model generates content— a story inspired by a writer’s uploaded work, PoA quantifies the influence (e.g., 30% attribution) and triggers automated payouts via smart contracts. Rewards are distributed in $OPEN tokens based on verified usage, eliminating intermediaries.

Payable AI Model: Inspired by platforms like YouTube, this enables passive earnings for data providers. For instance, a researcher uploading domain-specific data earns royalties every time it’s used in an AI agent’s inference, fostering a fairer AI supply chain.

This addresses AI’s “attribution crisis,” where contributors receive no upside from the $1 trillion+ AI economy projected by 2030. By decentralizing data custody and infrastructure, developers can build AI agents without managing servers or provenance, while complying with emerging regulations like GDPR.

The native $OPEN token powers the ecosystem, serving as the medium for rewards, staking, and fees. 40% to contributors/ecosystem; deflationary via inference ffeesl. Attribution payouts, staking 20-50% APY based on network load, governance.

Increased AI usage ? more on-chain attribution ? higher $OPEN consumption for payouts. $OPEN launched without a traditional TGE, prioritizing network stability. It’s listed on major exchanges like Binance.

With community speculation pointing to strong upside potential—comparable projects like Render ($RNDR) achieved 100x gains on narrower utility, while Bittensor ($TAO) trades at a 60x higher valuation despite similar architecture.

The mainnet rollout has generated buzz in crypto and AI circles, 27 products built, $15M in early revenue, and seamless migration of 6M nodes to the live explorer. Partnerships with Cambridge for a $5M decentralized AI research fund; integrations with KaitoAI for rewards 250K $OPEN in a “YAPENING” leaderboard challenge.

X discussions highlight its asymmetry as an “AI infra play,” with users noting the shift from hype-driven agents to fundamental attribution tech. Early adopters can participate via the AI Studio for model deployment or Datanets for data contributions, earning $OPEN through PoA.

With 50+ dApps in development and grants totaling $25M, OpenLedger is positioning itself as the go-to layer for AI x Web3, potentially bridging ecosystems like Base and MegaETH. This launch isn’t just another token drop—it’s a structural fix for AI’s inequities, turning contributors into stakeholders in the intelligence economy.

As AI lawsuits mount and ethical sourcing becomes mandatory, OpenLedger’s verifiable, on-chain model could become a regulatory moat. At its current valuation, it’s an asymmetric bet on the convergence of AI and blockchain, with real-world utility already proven.

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