Martyn Waghorn
Professional football player ⚽️ Represented by @wasserman
71,114
Followers
559
Following
3,596
Tweets
477.0
Avg Engagement
104
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Mwaghorn_9'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:2016-01-12
- Verification:No
- Location:Derby, England
Data Summary
- Tweets Analyzed:3,167
- Avg Likes per Tweet:194.0
- Avg Retweets per Tweet:283.0
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,167 tweetsHis tweets receive an average of 6,000 likes and 1,363 retweets, showing strong interaction with followers. The high engagement rate indicates a dedicated and active community around his content.
194.0
Avg Likes/Tweet
283.0
Avg Retweets/Tweet
614,384
Total Likes
896,356
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
9
Median Likes
2
Median Retweets
182
75th Percentile
161,458
Top Tweet
6.71
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
18.8%
Original
44.0%
Replies
28.2%
Retweets
9.0%
Quotes
0.0%
Threads
0.4%
With Media
45.0%
With Links
19.0%
With #Tags
84.7%
With @Mentions
78.7%
With Emojis
90
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
2.34
Reply/Original Ratio
0.32
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69.4%
Weekday Posts
30.6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,167 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 893 retweets (28% 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 3,167 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 followersThe audience primarily consists of football fans and followers of his career, likely from the UK given the team mentions. The engagement suggests a loyal fan base interested in his personal and professional updates.
Average
Audience Quality
21.0%
Suspicion Index
28.5%
Low-Quality %
63
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
42.5%
Empty Bio
23.6%
<10 Tweets
11.1%
Mass Following (>2K)
0.0%
New (<90 days)
37.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
93.0%
No URL
14.5%
<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.
63,402,496
Total Potential Reach
63
Median Follower Reach
234
75th Percentile Reach
6.4%
>1K followers
0.7%
>10K followers
0.3%
>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).
55.2%
Creators
5,520 accounts
21.2%
Consumers
2,119 accounts
23.6%
Dormant
2,361 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):
33
Verified Followers
0.33% of total
937
Protected Accounts
9.37% of total
6 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 |
|---|---|---|---|
| @NiallOfficial | 40,613,908 | Singer | Music, Collaboration, Release |
| @JohnCena | 14,093,946 | Wrestler | Wrestling, Motivation, Self-promotion |
| @sportbible | 2,113,575 | Sports Media | Sport, Lifestyle, Entertainment |
| @FootballManager | 446,353 | Video Game Developer | Football, Gaming, Future |
| @zammit_marc | 385,497 | Filmmaker | Film, Acting, Producing |
| @JulianMarley | 271,358 | Musician | Reggae, Music, Family |
| @htafc | 243,046 | Football Club | Football, Huddersfield, Club |
| @BeefGolf | 173,705 | Golfer | Golf, Normal, Geezer |
| @Coventry_City | 166,761 | Football Club | Football, Coventry, #PUSB |
| @Paul_Gravette | 158,633 | Entrepreneur | business, philanthropy, consulting |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
5,747
Followers With Bio
4,253
Followers Without Bio
57.47%
% With Bio
42.53%
% 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 3,167 analyzed373,995
Combined Engagement
0
Total Likes
373,995
Total Retweets
74,799
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
80%
With Links
Topical Analysis:
RT @MarcusRashford: https://t.co/bs9lksGM4q
RT @_SJPeace_: THIS IS TERRIFYING! Video shows a little girl hiding from a suspicious car following her through California neighborhood. Remind your kids to ALWAYS be aware of their surroundings & to scream as loud as they can for help when someone is following them! This
RT @MeredithFrost: So cool: Unearthed footage of Sylvester Stallone/Carl Weathers Choreography for Rocky in 1976 https://t.co/depECkYTak
RT @MarcusRashford: MBE 🇬🇧 https://t.co/BYkeKY2chP
RT @WayneRooney: I find it amazing that I equal sir Bobby Charltons record and this is a headline in the mail. https://t.co/MXCs1HFooT
Key Insights & Takeaways
The account frequently interacts with football teams and fans, indicating a strong connection to the sport and its community. The use of emojis and personal messages suggests a focus on building a friendly and relatable brand image. The presence of team-specific links implies a strategic effort to engage with specific fan bases and promote team-related content.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 71,114
- + 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 @Mwaghorn_9 reveals an well-established Twitter presence with 71,114 followers. The account demonstrates a conversation-first approach, averaging 477.0 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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