Samuel Marsden
write for @espn, talk @siemprepod 〓〓
56,619
Followers
1,298
Following
39,711
Tweets
320.5
Avg Engagement
793
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @samuelmarsden'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:2009-06-11
- Verification:No
- Location:Poblenou
Data Summary
- Tweets Analyzed:3,244
- Avg Likes per Tweet:138.9
- Avg Retweets per Tweet:181.6
- Followers Analyzed:9,998
Engagement Analysis
Based on 3,244 tweetsHis tweets receive a high number of likes and retweets, indicating strong audience interaction. The content is likely shared widely due to its relevance and timeliness.
138.9
Avg Likes/Tweet
181.6
Avg Retweets/Tweet
450,568
Total Likes
589,121
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
35
Median Likes
5
Median Retweets
157
75th Percentile
99,015
Top Tweet
5.66
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
40.4%
Original
35.2%
Replies
20.9%
Retweets
3.4%
Quotes
0.0%
Threads
0.2%
With Media
39.8%
With Links
2.9%
With #Tags
52.5%
With @Mentions
7.5%
With Emojis
133
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.87
Reply/Original Ratio
0.16
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
70.2%
Weekday Posts
29.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,244 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 679 retweets (21% 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 3,244 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 9,998 followersHis audience primarily consists of football fans and followers of ESPN and SIemprePod. The engagement metrics suggest a dedicated fan base interested in player movements and team updates.
Below Average
Audience Quality
37.5%
Suspicion Index
100.0%
Low-Quality %
51
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
100.0%
Empty Bio
100.0%
<10 Tweets
0.0%
Mass Following (>2K)
0.0%
New (<90 days)
0.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
92.1%
No URL
100.0%
<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.
9,659,746
Total Potential Reach
51
Median Follower Reach
191
75th Percentile Reach
6.2%
>1K followers
0.8%
>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).
0.0%
Creators
0 accounts
0.0%
Consumers
0 accounts
100.0%
Dormant
9,998 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):
0
Verified Followers
0.0% of total
984
Protected Accounts
9.84% 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 |
|---|---|---|---|
| @David_Ornstein | 2,284,345 | Football Correspondent | - |
| @IamMzilikazi | 554,960 | Musician | Pan-African music, Album, Rise |
| @eurofootcom | 440,556 | Sports Media | Football, Europe, Home |
| @Moreno | 429,264 | Influencer | Business, Manager, Serious |
| @TheAdrianDurham | 410,710 | Sports Commentator | Football, Sports, Radio |
| @ChrisWheatley | 306,575 | Sports Journalist | Football, Arsenal, Reporting |
| @ChelsTransfer | 259,127 | Sports Journalist | Chelsea news, Transfer gossip, Business |
| @AitanaBonmati | 140,236 | - | - |
| @EduPolo | 136,694 | Journalist | Ciclismo, Real Oviedo, ASICS Frontrunner |
| @bentalksutd | 133,533 | Sports News | Read, Watch, Listen |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
6,256
Followers With Bio
3,744
Followers Without Bio
62.56%
% With Bio
37.44%
% 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 3,244 analyzed281,675
Combined Engagement
37,485
Total Likes
244,190
Total Retweets
56,335
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
80%
With @Mentions
80%
With Links
Topical Analysis:
RT @3gerardpique: Culers, us he de dir una cosa. https://t.co/k3V919pm1T
RT @ManCity: Manchester City can confirm that we have reached an agreement in principle with Borussia Dortmund for the transfer of striker Erling Haaland to the Club on 1st July 2022. The transfer remains subject to the Club finalising terms with the player.
RT @MinoRaiola: https://t.co/xuZWBNA62N
Don't hit the translate button on this one https://t.co/Gx8UiZmiVL
RT @ToniKroos: Yellow card. Of course. https://t.co/DZncR5vPMt
Key Insights & Takeaways
He frequently shares links to articles and videos, suggesting a focus on content curation and media promotion. His tweets often highlight player movements and team updates, indicating a focus on transfer news and player activities. He maintains a consistent posting schedule, which helps in keeping his audience engaged and informed.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 56,619
- + 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 @samuelmarsden reveals an well-established Twitter presence with 56,619 followers. The account demonstrates a content-creator strategy, averaging 320.5 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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