James Marshment
Editor @TEAMtalk and lifelong fan of @LUFC. Marcelo Bielsa devotee. james.marshment@planetsport.com
25,898
Followers
881
Following
18,353
Tweets
204.6
Avg Engagement
187
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @marshyleeds'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:2012-03-21
- Verification:No
- Location:Leeds Leeds Leeds
Data Summary
- Tweets Analyzed:500
- Avg Likes per Tweet:179.9
- Avg Retweets per Tweet:24.7
- Followers Analyzed:24,116
Engagement Analysis
Based on 500 tweetsTheir tweets receive a moderate level of engagement, with an average of 2,002 likes and 97 retweets per post. This suggests a dedicated but niche following.
179.9
Avg Likes/Tweet
24.7
Avg Retweets/Tweet
89,958
Total Likes
12,337
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
12
Median Likes
0
Median Retweets
249
75th Percentile
3,594
Top Tweet
7.9
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
31.0%
Original
58.2%
Replies
6.2%
Retweets
4.6%
Quotes
0.0%
Threads
0.0%
With Media
21.0%
With Links
9.6%
With #Tags
60.8%
With @Mentions
4.8%
With Emojis
154
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.88
Reply/Original Ratio
0.74
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
70.8%
Weekday Posts
29.2%
Weekend Posts
Top Hashtags
Most Mentioned
Want This Report as PDF?
We're building PDF export for these analytics reports. Register your interest to get early access.
Content Strategy Analysis
Based on 500 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 31 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 500 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 24,116 followersTheir followers are likely football fans, especially those interested in Leeds United and Premier League updates. The audience is engaged with detailed analysis and player news.
Good
Audience Quality
17.3%
Suspicion Index
23.1%
Low-Quality %
129
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
38.1%
Empty Bio
13.7%
<10 Tweets
14.9%
Mass Following (>2K)
0.0%
New (<90 days)
28.8%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.7%
No URL
8.2%
<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.
41,539,155
Total Potential Reach
129
Median Follower Reach
398
75th Percentile Reach
11.0%
>1K followers
1.1%
>10K followers
0.3%
>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).
69.4%
Creators
16,745 accounts
16.9%
Consumers
4,069 accounts
13.7%
Dormant
3,302 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):
224
Verified Followers
0.93% of total
2,590
Protected Accounts
10.74% of total
8 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 |
|---|---|---|---|
| @FabrizioRomano | 14,416,557 | Journalist | Football, Transfers, News |
| @6BillionPeople | 2,038,025 | - | - |
| @ZachBoychuk | 830,517 | Hockey Player | Hockey, Meme/NFT Trading, Ethereum |
| @footballdaily | 706,943 | Sports Journalist | Breaking news, press conferences, interviews |
| @IamMzilikazi | 540,101 | Musician | Pan-African music, Album, Rise |
| @zammit_marc | 388,071 | Filmmaker | Film, Acting, Producing |
| @nawaf__oga | 367,305 | Media | English Football, Football Organizations, Strategic Communication |
| @bootlegger1974 | 351,056 | Unemployed | Fish & chips, Jobseeker's allowance, Chicken factory |
| @eljonesuk | 331,001 | Sports Broadcaster | Football, Betting, Podcasting |
| @nataliesawyer | 314,485 | Sports Broadcaster | Mum, Radio, Football |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
14,928
Followers With Bio
9,188
Followers Without Bio
61.9%
% With Bio
38.1%
% 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
Export full follower list with profile details, bios, locations, and follower counts as CSV.
Buy Followers - from $15Buy Tweet Data
Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 500 analyzed14,502
Combined Engagement
8,288
Total Likes
6,214
Total Retweets
2,900
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
60%
With Hashtags
40%
With @Mentions
20%
With Links
Topical Analysis:
RT @FabrizioRomano: Jesse Marsch has just been sacked by Leeds United. Decision made after the recent negative results, confirmed. 🚨⚪️ #LUF…
Speaking to L'Equipe, Illan Meslier has made clear his wish to stay at Leeds, potentially beyond his current deal. “No, it could potentially go through an even bigger development of our team.” On his progress at #LUFC: "They made me who I am today. It's beyond my expectations." h
Leeds Utd had won 4 in 23 Premier League games this season, prior to Javi Gracia’s appointment - a win percentage of just 17.39% Since the appointment of the Spaniard, Leeds have three wins in six games. 50 bloody per cent. Looking like an inspired decision ⚪️ 🟡 🔵 https://t.co/f1
RT @FabrizioRomano: Weston McKennie has accepted Leeds United contract proposal, personal terms are not an issue - it's on Leeds and Juvent…
Very promising start for Gracia. Four games, two wins, seven points. Prior to his appointment, we’d averaged 0.82pts per game. A small sample, of course, but Gracia has 1.75pts per game. Been impressed by the way #LUFC have adapted for each opponent under him. Smart coach. htt
Key Insights & Takeaways
They provide in-depth analysis of Leeds United's performance under new managers like Javi Gracia. They highlight player developments, such as Illan Meslier's desire to stay at the club. They focus on statistical insights and team progress, offering a data-driven perspective on the club's performance.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 25,898
- + 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 @marshyleeds reveals an well-established Twitter presence with 25,898 followers. The account demonstrates a conversation-first approach, averaging 204.6 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.
Need Programmatic Access?
We're building an API for developers and researchers. Get access to Twitter data programmatically for your applications and analysis.
Register Interest for API Access