Karl Darlow
Professional Footballer for Leeds United.
81,490
Followers
620
Following
1,598
Tweets
69.4
Avg Engagement
227
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @KarlDarlow'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:2012-04-13
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:1,525
- Avg Likes per Tweet:23.5
- Avg Retweets per Tweet:46.0
- Followers Analyzed:10,000
Engagement Analysis
Based on 1,525 tweetsHis tweets typically receive around 2,485 likes and 283 retweets on average, indicating a high level of audience interaction.
23.5
Avg Likes/Tweet
46.0
Avg Retweets/Tweet
35,795
Total Likes
70,092
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
0
Median Retweets
5
75th Percentile
21,492
Top Tweet
0.85
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
30.0%
Original
52.5%
Replies
17.5%
Retweets
0.0%
Quotes
0.0%
Threads
0.1%
With Media
14.5%
With Links
36.7%
With #Tags
88.5%
With @Mentions
19.3%
With Emojis
73
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.75
Reply/Original Ratio
0.0
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
76.5%
Weekday Posts
23.5%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 1,525 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 267 retweets (18% 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 1,525 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 primarily consists of football fans, especially those interested in Leeds United and the Premier League.
Average
Audience Quality
25.4%
Suspicion Index
31.5%
Low-Quality %
32
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
45.3%
Empty Bio
28.4%
<10 Tweets
10.8%
Mass Following (>2K)
0.0%
New (<90 days)
52.9%
Low Ratio (<0.1)
0.0%
New (<180 days)
94.0%
No URL
17.7%
<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.
3,547,888
Total Potential Reach
32
Median Follower Reach
135
75th Percentile Reach
3.7%
>1K followers
0.4%
>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).
46.5%
Creators
4,652 accounts
25.1%
Consumers
2,511 accounts
28.4%
Dormant
2,837 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
862
Protected Accounts
8.62% 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 |
|---|---|---|---|
| @Moreno | 429,942 | Influencer | Business, Manager, Serious |
| @BenDinnery | 161,724 | Injury Analyst | Football, Injury updates, Fantasy sports |
| @Bradleysfight | 137,918 | Charity | fundraising, awareness, support |
| @fabianschaer | 128,032 | Footballer | Football, Newcastle United, Swiss Nationalteam |
| @fun88eng | 101,874 | Betting | Sports betting, Football, Esports |
| @ProjectEPL | 81,800 | Football Influencer | football, TikTok, sports |
| @NufcPortal | 60,368 | Sports Blogger | Football, News, Blog |
| @EWNsport | 55,215 | Sports News | Sports, News, Updates |
| @bbcburnsy | 52,888 | Radio Host | Radio, Awards, Butlins |
| @1JohnAchterberg | 52,072 | Goalkeeper Coach | Liverpool FC, Goalkeeping, YNWA |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
5,467
Followers With Bio
4,533
Followers Without Bio
54.67%
% With Bio
45.33%
% 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 1,525 analyzed45,255
Combined Engagement
4,578
Total Likes
40,677
Total Retweets
9,051
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
100%
With @Mentions
40%
With Links
Topical Analysis:
RT @liamgallagher: Maradona shakes the hand of God ! http://t.co/GfFxdvYi
RT @rioferdy5: Has anyone checked to see if the net needs first aid?! Boooooom!
Never in doubt 😅👏🏻 #nufc @NUFC
RT @Joey7Barton: Why are people giving me loads about England saying "cant get in squad etc". On ability I walk in the squad, on behaviour i don't... #fact
RT @WillMckenzieNot: If your boyfriend does this then he is definitely a keeper http://t.co/Wt6Te3bBQc
Key Insights & Takeaways
He frequently shares personal milestones and team achievements, which resonate well with his followers. His content often includes emojis and hashtags, enhancing engagement and relatability. He maintains a professional yet approachable tone, aligning with his role as a footballer.
Strengths
- + Established follower base of 81,490
- + 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 @KarlDarlow reveals an growing Twitter presence with 81,490 followers. The account demonstrates a conversation-first approach, averaging 69.4 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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