FaZe Jsmooth
Content Creator for @fazeclan @nukesquad |Pro WZ Player| Business email: [email protected]
87,203
Followers
1,046
Following
16,085
Tweets
534.5
Avg Engagement
78
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @JSmooth's Twitter/X presence across multiple dimensions. We analyze tweet content, engagement patterns, audience demographics, posting habits, and network connections to provide actionable insights about this account's social media strategy and influence.
Account Classification
- Account Size: Mid-Tier (10K+)
- Account Age:2013-06-07
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:500
- Avg Likes per Tweet:79.8
- Avg Retweets per Tweet:454.7
- Followers Analyzed:50,000
Engagement Analysis
Based on 500 tweetsJSmooth's tweets receive high engagement, with an average of 798 likes and 29 retweets. His interactions often involve celebrating other creators and gaming milestones.
79.8
Avg Likes/Tweet
454.7
Avg Retweets/Tweet
39,878
Total Likes
227,373
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
35
Median Likes
2
Median Retweets
94
75th Percentile
46,642
Top Tweet
6.13
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
49.4%
Original
36.6%
Replies
7.0%
Retweets
7.0%
Quotes
0.0%
Threads
0.4%
With Media
32.4%
With Links
2.4%
With #Tags
43.6%
With @Mentions
13.8%
With Emojis
56
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.74
Reply/Original Ratio
1.0
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
71.6%
Weekday Posts
28.4%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 500 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This is a content-creator focused account that primarily shares original thoughts, ideas, and media. With original content dominating their feed, they position themselves as a source of new information rather than a curator. This strategy works well for establishing thought leadership.
The 35 retweets (7% of activity) show they also amplify content from others, which helps build relationships with other accounts and provides value to followers by surfacing relevant content.
Posting Patterns & Optimal Timing
Based on 500 tweetsEngagement by Hour (UTC)
Posting Frequency Over Time
Timing Insights
Understanding when an account posts and when their audience is most responsive provides valuable competitive intelligence. The charts above show when this account's content receives the most engagement, which often correlates with when their specific audience is most active on the platform.
Peak posting times vary significantly based on an account's audience demographics, timezone distribution, and content type. Accounts with global audiences often see engagement spread across multiple time windows, while those with regional focus may have more concentrated peaks.
Audience Demographics
Based on 50,000 followersHis audience primarily consists of gaming enthusiasts and fans of Faze Clan and Nukesquad. The content appeals to both casual and competitive gamers.
Average
Audience Quality
27.8%
Suspicion Index
33.3%
Low-Quality %
12
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
41.5%
Empty Bio
37.3%
<10 Tweets
5.2%
Mass Following (>2K)
0.0%
New (<90 days)
64.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
82.5%
No URL
25.1%
<3 Tweets
Free Mode Analysis: These quality metrics use heuristic signals (empty bios, low tweets, suspicious ratios). For ML-powered bot detection with 95%+ accuracy, use our dedicated tool.
Try Bot DetectorFollower Reach & Influence
This account's followers have their own audiences, creating potential for secondary amplification.
88,325,391
Total Potential Reach
12
Median Follower Reach
75
75th Percentile Reach
3.0%
>1K followers
0.6%
>10K followers
0.3%
>50K followers
0.2%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
39.2%
Creators
19,622 accounts
23.5%
Consumers
11,730 accounts
37.3%
Dormant
18,648 accounts
Follower Influence Distribution
How many followers do their followers have?
Follower Account Age
How long have followers been on Twitter?
Geographic Distribution
Top locations where followers are based (from those who share location data):
1,281
Verified Followers
1.48% of total
7,769
Protected Accounts
8.98% of total
5 years
Avg Account Age
of their followers
Notable Followers (By Influence)
Top accounts following this user, sorted by their follower count:
| Username | Followers | Profession | Interests |
|---|---|---|---|
| @JohnCena | 14,105,705 | Wrestler | Wrestling, Motivation, Self-promotion |
| @FaZeClan | 5,754,345 | Esports | Esports, Champions, FaZeUp |
| @McDonalds | 4,769,108 | Fast Food | Fast Food, Grimace, Friendship |
| @DJPaulyD | 3,608,521 | DJ | Music, DJing, Booking |
| @MiaMalkova | 3,329,316 | Adult entertainer | Nature, Instagram, Onlyfans |
| @FaZe_Rain | 3,183,395 | Gamer | Gaming, eSports, Improvement |
| @Nadeshot | 2,973,852 | Professional Gamer | Gaming, Esports, Entrepreneurship |
| @timthetatman | 2,855,789 | Streamer | Gaming, Entertainment, Nerd |
| @Banks | 2,816,466 | Gamer | gaming, internet, music |
| @FaZeAdapt | 2,792,826 | Influencer | adventure, uncertainty, humor |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
52,210
Followers With Bio
34,286
Followers Without Bio
60.36%
% With Bio
39.64%
% Without Bio
Why Audience Demographics Matter
Understanding who follows an account reveals the type of influence they hold. Accounts followed primarily by users with few followers indicate broad, mainstream appeal. Those with many high-follower followers have greater potential for content amplification through secondary sharing.
Account age distribution also tells a story: a follower base with many new accounts might indicate recent viral growth, while established followers suggest long-term, stable influence. Geographic data helps understand the cultural context and timezone spread of the audience.
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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 500 analyzed155,688
Combined Engagement
0
Total Likes
155,688
Total Retweets
31,138
Avg per Tweet
Key Metrics for Viral Tweets
20%
With Media
0%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @MrBeast: Twitter - Rich people should help others with their money Me - Okay, I’ll use my money to help people and I promise to give a…
RT @druski: Dudes in Jail be making Prison LOOK FUN 😂😂😭 https://t.co/PK0pjRkDL7
RT @ESPNNBA: THIS PHOTO. HISTORY. https://t.co/qirvlCifG5
RT @PontiacMadeDDG: you lose value when you too accessible.. make them miss you
RT @KingJosiah54: Kanye watching Rihanna sing All of the Lights at the Super Bowl https://t.co/U5izsxtYGI
Key Insights & Takeaways
He frequently interacts with other content creators and gamers, which boosts his engagement. His tweets often include celebratory messages and milestones, which resonate well with his audience. He uses hashtags and links to enhance the visibility and reach of his posts.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 87,203
- + Strong original content creation
- + Active presence with consistent posting
Opportunities
- ~ Optimize posting times for peak engagement windows
- ~ Analyze top-performing content for replicable patterns
- ~ Leverage geographic concentration for targeted content
- ~ Explore collaboration potential with followed accounts
Summary
This analysis of @JSmooth reveals an well-established Twitter presence with 87,203 followers. The account demonstrates a content-creator strategy, averaging 534.5 engagements per tweet. Key strengths include consistent posting and an engaged audience, with opportunities to further optimize timing and content strategy based on the patterns identified in this report.
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