# Will MrBeast hit ___ Billion views by June 30 — 129 billion

> Liquidity-weighted aggregate at 95% across 1 contract — refreshed 42 min ago.

URL: https://simplefunctions.dev/odds/mrbeast-hit-billion-views-june-30
Updated: 2026-05-28T19:20:12.097Z
Category: general
Status: active
Closes: 2026-06-30

## Headline

- Probability: 95% (liquidity-weighted across 1 contract)
- Venue: Polymarket (1 contract)
- 24h volume: $72

## Bound contracts (1)

| Outcome | Price | 24h | Volume | Venue | Slug |
|---|---|---|---|---|---|
| 129 billion | 95¢ | +4pp | $72 | polymarket | /markets/will-mrbeast-hit-billion-views-by-june-30-129-bill-polymarket-0x518301a471c1e86c7b11d8eea58be6936f57c6a7d5f8b7f0fbefa6c87f145d31 |

## 30-day trajectory

| Day | Aggregate |
|---|---|
| 2026-05-24 | 79 |
| 2026-05-25 | 84 |
| 2026-05-26 | 87 |
| 2026-05-27 | 91 |

_4 days of price history captured. Each row is the daily mean of intraday 5-min captures._

## What moved the line

- 2026-05-25 · 129 billion +5pp 79→84¢ · polymarket
- 2026-05-27 · 129 billion +4pp 87→91¢ · polymarket
- 2026-05-26 · 129 billion +3pp 84→87¢ · polymarket

## Analysis

This market estimates a 96% probability that MrBeast will reach 129 billion total views on YouTube by June 30, 2026—roughly 37 days from now. The high probability reflects his historical growth trajectory and subscriber base, which have consistently generated substantial view counts. The main factors are his upload frequency, content performance (which determines views per video), and whether YouTube's algorithm amplification continues at recent levels. Any significant slowdown in content release or viewer engagement would lower the probability. The outcome resolves automatically when YouTube's view counter updates, making this a straightforward measurement-based event with no ambiguity about the final result.

### Key factors

- MrBeast's average daily view velocity over the past 30 days compared to the 1.44 billion views per day needed to reach 129B by June 30
- His upload schedule and typical views-per-video in recent months, accounting for seasonal content performance variations
- YouTube's algorithm distribution patterns and whether recent engagement rates represent sustainable baseline performance
- Potential external events (platform changes, content issues, or other unpredictable factors) that could disrupt normal viewing patterns within the 37-day window
- The gap between 127B and 129B (the leading vs. featured threshold) to assess how tight the clustering of near-term outcomes is

## Methodology

Probability is **liquidity-weighted** across all bound Kalshi/Polymarket contracts: Σ(price × volume) ÷ Σ(volume). 30-day trajectory uses the daily mean of intraday 5-min captures. 24h delta = today's mean − yesterday's mean. Movement events are ≥3pp daily moves in the last 7 days.

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