100T bang
19 | VALORANT player for @100Thieves | https://www.twitch.tv/bangzerra | [email protected] For Business Inquiries
100,156
Followers
682
Following
1,987
Tweets
525.5
Avg Engagement
288
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @bangzerra'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: Macro Influencer (100K+)
- Account Age:2020-08-13
- Verification:No
- Location:Los Angeles, CA
Data Summary
- Tweets Analyzed:1,885
- Avg Likes per Tweet:496.4
- Avg Retweets per Tweet:29.1
- Followers Analyzed:50,000
Engagement Analysis
Based on 1,885 tweetsBangzerra's tweets receive high engagement, indicating a loyal and active fan base. His content is well-received, with a mix of gameplay highlights, promotions, and interactive posts.
496.4
Avg Likes/Tweet
29.1
Avg Retweets/Tweet
935,706
Total Likes
54,910
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
43
Median Likes
0
Median Retweets
264
75th Percentile
32,947
Top Tweet
5.25
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Conversationalist
Highly engaged in discussions
29.5%
Original
56.6%
Replies
11.1%
Retweets
2.8%
Quotes
0.0%
Threads
0.0%
With Media
26.7%
With Links
3.2%
With #Tags
79.0%
With @Mentions
8.9%
With Emojis
55
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.92
Reply/Original Ratio
0.25
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
70.5%
Weekday Posts
29.5%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 1,885 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This account prioritizes community engagement over content broadcasting. With replies making up the majority of their activity, they invest significant time in conversations, building relationships with followers and participating in discussions. This approach typically leads to higher loyalty and more authentic connections.
The 209 retweets (11% 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 1,885 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 is primarily interested in Valorant and gaming content, with a focus on professional players and fans. The audience also shows interest in giveaways and community-driven events.
Average
Audience Quality
24.7%
Suspicion Index
28.9%
Low-Quality %
12
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
40.6%
Empty Bio
26.7%
<10 Tweets
3.0%
Mass Following (>2K)
0.0%
New (<90 days)
64.9%
Low Ratio (<0.1)
0.0%
New (<180 days)
85.5%
No URL
17.1%
<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.
42,079,116
Total Potential Reach
12
Median Follower Reach
53
75th Percentile Reach
2.0%
>1K followers
0.3%
>10K followers
0.2%
>50K followers
0.1%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
48.2%
Creators
24,094 accounts
25.1%
Consumers
12,545 accounts
26.7%
Dormant
13,361 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):
372
Verified Followers
0.38% of total
11,554
Protected Accounts
11.89% of total
4 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 | 14,106,673 | Wrestler | Wrestling, Motivation, Self-promotion |
| @verified | 4,201,444 | - | - |
| @Nadeshot | 2,975,433 | Professional Gamer | Gaming, Esports, Entrepreneurship |
| @Myth_ | 2,555,642 | Gamer | Gaming, Esports, Business |
| @TSM | 2,221,227 | Esports Team | Esports, LCS, Champions |
| @bugha | 1,953,789 | Professional Gamer | Fortnite, Gaming, Esports |
| @CouRageJD | 1,941,760 | Gamer | Gaming, Soup, Merch |
| @100Thieves | 1,277,118 | Gaming | Gaming, entertainment, apparel |
| @kyedae | 1,065,318 | Content Creator | Gaming, Esports, Content Creation |
| @LeBronJames | 1,006,918 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
59,493
Followers With Bio
37,699
Followers Without Bio
61.21%
% With Bio
38.79%
% 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.
Buy Follower Data
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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 1,885 analyzed113,675
Combined Engagement
96,151
Total Likes
17,524
Total Retweets
22,735
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
0%
With @Mentions
60%
With Links
Topical Analysis:
I am doing a PC giveaway thanks to winning the FaZe Smeag Cup! -Follow -Like and retweet -Picking a winner November 21st https://t.co/322HgkrQBC
The fake reload https://t.co/zbxZi2kEsp
back2back https://t.co/X34jZKAA5g
day 3 of having my job until marved takes it
Finally graduated high school, I will be putting my full time and effort into competing and streaming Valorant 😈
Key Insights & Takeaways
He leverages his platform to promote his portfolio and business opportunities. He frequently shares gameplay highlights and community-focused content. He runs giveaways and interactive campaigns to boost engagement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 100,156
- + High community engagement through conversations
- + 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 @bangzerra reveals an well-established Twitter presence with 100,156 followers. The account demonstrates a conversation-first approach, averaging 525.5 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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