Michael Laverty
Pundit/Commentator @btsportmotogp :: Racer :: Team Owner • Supported by... @VisionTrackLive | @epayme | @shark_helmets | @alpinestars | @oakley
61,254
Followers
614
Following
6,539
Tweets
53.3
Avg Engagement
539
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @MichaelLaverty'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:2008-12-09
- Verification:No
- Location:Presteigne
Data Summary
- Tweets Analyzed:3,203
- Avg Likes per Tweet:33.1
- Avg Retweets per Tweet:20.3
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,203 tweetsHis tweets typically receive a high number of likes and retweets, showing strong audience interaction. The engagement reflects his credibility and relevance in the motorsport space.
33.1
Avg Likes/Tweet
20.3
Avg Retweets/Tweet
105,898
Total Likes
64,872
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
2
Median Likes
0
Median Retweets
24
75th Percentile
30,566
Top Tweet
0.87
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
25.9%
Original
60.2%
Replies
9.4%
Retweets
4.6%
Quotes
0.0%
Threads
0.9%
With Media
30.0%
With Links
5.9%
With #Tags
85.5%
With @Mentions
29.7%
With Emojis
106
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
2.32
Reply/Original Ratio
0.49
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
68.3%
Weekday Posts
31.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,203 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 301 retweets (9% 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 3,203 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 10,000 followersHis audience includes motorsport enthusiasts, fans of MotoGP, and followers of his personal journey. The content appeals to both casual viewers and dedicated racing fans.
Average
Audience Quality
26.3%
Suspicion Index
35.2%
Low-Quality %
22
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
51.0%
Empty Bio
29.8%
<10 Tweets
7.7%
Mass Following (>2K)
0.0%
New (<90 days)
56.4%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.6%
No URL
19.3%
<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.
4,693,913
Total Potential Reach
22
Median Follower Reach
97
75th Percentile Reach
3.6%
>1K followers
0.5%
>10K followers
0.1%
>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).
46.0%
Creators
4,598 accounts
24.2%
Consumers
2,419 accounts
29.8%
Dormant
2,983 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):
23
Verified Followers
0.23% of total
974
Protected Accounts
9.74% of total
7 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 |
|---|---|---|---|
| @AleixEspargaro | 442,170 | MotoGP Rider | MotoGP, Rider, #41 |
| @Official_CS27 | 418,178 | Motorcyclist | Motorcycles, Fishing, Fatherhood |
| @guidomeda | 360,090 | Journalist | MotoGP, giornalista, Giochi senza Frontiere |
| @eurosport | 215,902 | - | - |
| @LorisCapirossi1 | 150,229 | Motorcyclist | Motorcycle racing, World champion, Instagram |
| @ZS_Racing | 128,214 | Motorsport | Racing, Sports, Action |
| @motorsportcomtr | 105,626 | Motorsport News | Formula 1, Motor Sporları, Haberler |
| @mike_Iaconelli | 102,035 | Fisherman | Fishing, Host, Bass University |
| @sepangracing | 86,187 | Motorcycle Racing | MotoGP, Moto2, Moto3 |
| @ScottWilliams_1 | 83,962 | Rugby Player | Rugby, Motorsport, Ambassador |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
4,896
Followers With Bio
5,104
Followers Without Bio
48.96%
% With Bio
51.04%
% 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 full follower list with profile details, bios, locations, and follower counts as CSV.
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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 3,203 analyzed46,390
Combined Engagement
1,842
Total Likes
44,548
Total Retweets
9,278
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
80%
With @Mentions
80%
With Links
Topical Analysis:
RT @robinedds: The subtle differences between the US and UK summed up in 6 seconds. https://t.co/X4sPmNUspA
RT @DavidBrentMovie: Oh for f*** sake... https://t.co/COetD7PsgI
Marc broke the unwritten rule, always RESPECT those fighting for a Championship when you're not. Vale got enraged and hung him out to dry
RT @BTSportBoxing: HUGE 🤯 Tyson Fury confirms he's agreed a two-fight deal with Anthony Joshua in 2021. First, he will finish the trilogy with Deontay Wilder. https://t.co/gBVtMsGVWm
RT @L_ArmiTstead: In my own words. https://t.co/D7ye4NE0IN
Key Insights & Takeaways
He frequently shares personal milestones and family updates, indicating a focus on personal branding. His content often highlights his racing career and team activities, emphasizing his professional involvement. He engages with fans by sharing behind-the-scenes insights and experiences, fostering a sense of connection.
Strengths
- + Established follower base of 61,254
- + 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 @MichaelLaverty reveals an growing Twitter presence with 61,254 followers. The account demonstrates a conversation-first approach, averaging 53.3 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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