1.2M Assets Tracked Updated 1 min ago Revenue Forecasts
Add an app Create Account Sign In
Home
THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND icon

How much does THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND earn?

YouTube channel from @theoreticalconceptsofphysi6140 · YouTube Channels

✓ Verified MRR ★ 1.3 · 379 Free

~1/mo

Founder-verified via Stripe Connect or App Store Connect.

Confidence band
±15%
High — many comparable apps with verified data

At a glance

THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND's revenue trajectory

Forecast revenue from snapshot history. Last 1 months.

Where THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND sits in YouTube Channels

Revenue distribution of 685093 comparable apps. THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND highlighted.

THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND vs comparable apps

Revenue trajectory side-by-side. Bold = THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND, ghosted = peers.

App spec

Launched
May 06, 2026
Price
Free
Monetization
Free

What THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND actually does (from store listing)

THIS CHANNEL CONTAINS THE BEST CONTENTS OF ALL GENERS related to deep understanding of physics Owned & Managed by : Sangam Suman

Comparable YouTube channels

The five apps in YouTube Channels with the closest revenue to THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND. Click any to see its detail page.

AppRevenueRatingRatings
BeenieTV icon BeenieTV 1 ★ 2.1 13K
Door3 icon Door3 1 ★ 2.7 217K
Varun Kumar icon Varun Kumar 1 ★ 1.4 587
Enduring Legacy Mentors icon Enduring Legacy Mentors 1 ★ 2.7 256K
MotoCross-OfficialChannel icon MotoCross-OfficialChannel 1 ★ 1.9 5K
Own THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND? Replace our estimate with your real revenue via Stripe Connect or ASC. Get a public Verified badge.
Claim & verify →

How we calculated this

Each forecast combines App Store rating, ratings count, monetisation model, pricing tier, IAP signals and ad-supported flag. The base estimate is then multiplied by a per-category scaling factor learned from apps with founder-verified MRR. Every number on this page comes from public APIs and bumetric's own snapshot history.

Full methodology covers input variables, accuracy bands per category and how we treat apps without comparable anchors. See also the live data on THEORETICAL CONCEPTS OF PHYSICS BY LEONARD SUSSKIND's tracker page for current rating, reviews and snapshot timeline.

Building something similar? Get a free AI audit with $-revenue forecasts for every recommendation.
Audit my app →