Mike LaBelle
Creator, Presenter & Multi National Champion 🏆 @NewYorkRedBulls
84,295
Followers
1,067
Following
27,937
Tweets
37.3
Avg Engagement
289
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @MikeLaBelle'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:2010-04-09
- Verification:No
- Location:[email protected]
Data Summary
- Tweets Analyzed:3,249
- Avg Likes per Tweet:26.0
- Avg Retweets per Tweet:11.3
- Followers Analyzed:10,999
Engagement Analysis
Based on 3,249 tweetsHis tweets receive a high number of likes and retweets, indicating strong audience interaction. The content is well-received and often shared across the community.
26.0
Avg Likes/Tweet
11.3
Avg Retweets/Tweet
84,423
Total Likes
36,804
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
5
Median Likes
0
Median Retweets
21
75th Percentile
14,453
Top Tweet
0.44
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
44.7%
Original
48.3%
Replies
5.5%
Retweets
1.5%
Quotes
0.0%
Threads
0.1%
With Media
37.3%
With Links
4.3%
With #Tags
48.2%
With @Mentions
16.7%
With Emojis
58
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.08
Reply/Original Ratio
0.28
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
69.3%
Weekday Posts
30.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,249 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 179 retweets (6% 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 3,249 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 10,999 followersHis followers are likely sports enthusiasts, gamers, and fans of football-related content. They are engaged and interested in both entertainment and informative posts.
Average
Audience Quality
24.0%
Suspicion Index
28.1%
Low-Quality %
23
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
41.6%
Empty Bio
22.1%
<10 Tweets
9.0%
Mass Following (>2K)
0.0%
New (<90 days)
58.9%
Low Ratio (<0.1)
0.0%
New (<180 days)
88.3%
No URL
14.6%
<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.
26,178,602
Total Potential Reach
23
Median Follower Reach
126
75th Percentile Reach
5.0%
>1K followers
1.2%
>10K followers
0.4%
>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).
57.4%
Creators
6,313 accounts
20.5%
Consumers
2,260 accounts
22.1%
Dormant
2,426 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):
106
Verified Followers
0.96% of total
803
Protected Accounts
7.3% 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 | 14,097,884 | Wrestler | Wrestling, Motivation, Self-promotion |
| @cloakzy | 1,614,647 | Streamer | streaming, youtube, gaming |
| @ImAllexx | 548,109 | YouTuber | YouTube, Fashion, Business |
| @iiTzTimmy | 429,448 | Streamer | gaming, memes, streaming |
| @blxckoutz | 402,885 | Professional Gamer | Fortnite, Tournament, Cloud9 |
| @DonkTrading | 383,953 | - | - |
| @JulianMarley | 271,926 | Musician | Reggae, Music, Family |
| @KittyPlays | 233,804 | Gamer | Transformation, Connection, Creation |
| @TroopzAFC | 227,184 | Influencer | Football, YouTube, Enquiries |
| @MLGPuckett | 220,612 | Esports Broadcaster | Esports, Broadcaster, Commentator |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
6,421
Followers With Bio
4,578
Followers Without Bio
58.38%
% With Bio
41.62%
% 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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Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,249 analyzed34,448
Combined Engagement
17,632
Total Likes
16,816
Total Retweets
6,890
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
60%
With @Mentions
40%
With Links
Topical Analysis:
Jungkook killed that lowkey #jungkookxfifa
RT @SHAQ: Change nothing and nothing will change
FIFA 23 Best Controller Settings. https://t.co/5mdqxeOyr1
RT @FabrizioRomano: Marcel Sabitzer arrives at Carrington to complete Manchester United move as Bayern & #MUFC have full agreement on loan deal. 🚨🔴 #DeadlineDay Documents are being prepared right now. https://t.co/H81jCVnn3o
RT @rebekkarnold: This time nine years ago I was 4 days into labour whilst my boyfriend was trying to win the Champions League with Newcastle on Football manager.
Key Insights & Takeaways
He frequently shares content related to football and gaming, which aligns with his audience's interests. His tweets often include trending topics and pop culture references, increasing their reach and engagement. He uses a mix of personal opinions and factual information to maintain a balanced and engaging presence.
Strengths
- + Established follower base of 84,295
- + 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 @MikeLaBelle reveals an growing Twitter presence with 84,295 followers. The account demonstrates a conversation-first approach, averaging 37.3 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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