# of views of next MrBeast video on week 1? (Higher Brackets)

According to the latest prediction market data for the query “# of views of next MrBeast video on week 1? (Higher Brackets)”, traders have formed a strong consensus.

Currently, 150M+ is dominating the market with an overwhelming 96.3% chance of winning. 140-150M follows in second place at 3.3%, while 130-140M sits in third with 0.3%. The betting volume for this specific market has already reached $77.5K, reflecting intense industry interest.

To better assess where each potential outcome stands, the market can be segmented into three distinct trading tiers based on implied probability and contract pricing:

🥇 Tier 1: The Dominant Leader

• 150M+ (96.3%): Currently commanding the highest probability, 150M+ is heavily favored by the order book. Traders looking to back this outcome face a “Buy Yes” contract price of 96¢, signaling a high degree of market conviction. This contract alone has generated $28.3K in volume.

🥈 Tier 2: The Primary Challengers

• 140-150M (3.3%): Positioned as the most viable alternative, 140-150M maintains a 3.3% chance of resolving true. Its “Buy Yes” shares currently trade at 3¢.
• 130-140M (0.3%): Sitting in third place with a 0.3% probability, the market shows measured skepticism toward 130-140M, treating it as an outside wildcard unless momentum shifts.

🥉 Tier 3: The Long-Tail Options (Combining for ~0.2%)

Beyond the top three choices, a wide field of macro variables and long-shot outcomes are being tracked. While their individual probabilities hover low, they represent crucial hedges for speculative traders:

• Alternative Options: This includes <110M (0.1%), 110-120M (0.1%), and 120-130M (0.1%).
• Speculative Volume: Despite low statistical likelihood, certain long-tail contracts like <110M are still attracting notable interest.

This market will resolve according to the number of views the most recent YouTube video posted by MrBeast gets in the first 7 days after being posted.

If the reported value falls exactly between two brackets, this market will resolve to the higher range bracket.

If the resolution source is not available at the end of the specified duration, this market will resolve according to most recent number of views available before the end of the specified duration.

The resolution source for this is MrBeast's YouTube channel (https://www.youtube.com/@MrBeast), specifically the 'views' counter for the described video.

Note: This market refers only to the video "Eat Everything In A Grocery Store, Win $1,000,000" by MrBeast (see: https://www.youtube.com/watch?v=plN7JMbadRg).

While human consensus and speculative volume shape the broader prediction market, our quantitative algorithms offer a data-driven counter-perspective. By analyzing fundamental signals, underlying trends and historical distributions, our AI Valuation model calculates an independent “Fair Value” probability for each outcome.

Comparing this Fair Value against the current Trade Value uncovers major disparities — known as the Expected Value (EV) Gap. Contracts with a positive EV Gap represent statistically underpriced outcomes, whereas a negative EV Gap flags a potential market overreaction.

Top AI Alpha & Mispriced Arbitrage Opportunities

Based on the latest data model run, several key contracts stand out with significant deviations:

• The Most Overvalued Outcome 150M+ currently trades at 96.3%, but our AI places its Fair Value at just 67.8%. This creates a large negative EV Gap of -28.4%, suggesting the crowd may be overhyping this outcome and driving the premium too high.
• The Best Value Play (Highest EV) Our model identifies 130-140M as the premium value opportunity on the board. While the market only assigns it a 0.3% trading probability, our AI’s Fair Value assessment sits at 6.1% — yielding an impressive +5.9% EV Gap.
• Under-the-Radar Dark Horses Other notable discrepancies include 120-130M (EV Gap: +4.1%) and <110M (EV Gap: +3.9%). These long-tail opportunities are heavily discounted by the live order books despite stronger statistical backing from our predictive model.