Liv Cooke
Freestyle Football World Champion and reigning 7x World record holder ⚽️🥇
92,669
Followers
1,344
Following
6,243
Tweets
215.3
Avg Engagement
97
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @LivCookefs'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:2015-02-22
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,162
- Avg Likes per Tweet:112.5
- Avg Retweets per Tweet:102.9
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,162 tweetsHer tweets receive high average likes and retweets, indicating strong audience interaction and interest in her content.
112.5
Avg Likes/Tweet
102.9
Avg Retweets/Tweet
355,604
Total Likes
325,241
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
4
Median Likes
2
Median Retweets
97
75th Percentile
145,313
Top Tweet
2.32
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
33.5%
Original
24.8%
Replies
29.3%
Retweets
12.4%
Quotes
0.0%
Threads
0.2%
With Media
64.0%
With Links
10.6%
With #Tags
60.2%
With @Mentions
55.5%
With Emojis
105
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.74
Reply/Original Ratio
0.42
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 3,162 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 925 retweets (29% 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 3,162 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 followersHer audience is primarily sports enthusiasts and football fans, with a global reach due to her international reputation.
Good
Audience Quality
19.7%
Suspicion Index
20.1%
Low-Quality %
137
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
33.7%
Empty Bio
10.7%
<10 Tweets
23.1%
Mass Following (>2K)
0.0%
New (<90 days)
37.5%
Low Ratio (<0.1)
0.0%
New (<180 days)
88.7%
No URL
6.5%
<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.
29,871,150
Total Potential Reach
137
Median Follower Reach
412
75th Percentile Reach
10.8%
>1K followers
1.5%
>10K followers
0.4%
>50K followers
0.3%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
75.1%
Creators
7,507 accounts
14.2%
Consumers
1,421 accounts
10.7%
Dormant
1,072 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):
70
Verified Followers
0.7% of total
1,306
Protected Accounts
13.06% 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 |
|---|---|---|---|
| @JohnCena | 14,094,626 | Wrestler | Wrestling, Motivation, Self-promotion |
| @Sporf | 1,383,381 | Sports Media | Sport, Conversation, Social Chain Group |
| @SinghLions | 1,330,452 | Restaurateur | Food, Travel, Influencer |
| @RexChapman | 1,253,655 | Commentator | Basketball, Horse racing, Commentary |
| @sportrelief | 625,885 | Charity | charity, fundraising, BBC |
| @itvfootball | 492,972 | Sports Media | Football, Instagram, YouTube |
| @Moreno | 430,836 | Influencer | Business, Manager, Serious |
| @danielcorralmx | 287,854 | Gymnast | Olympics, Gymnastics, Medals |
| @GiaPratamaMD | 265,397 | Doctor | Humanitarian, Doctor, Service |
| @comicrelief | 235,262 | Charity | Comedy, Charity, Poverty |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
6,634
Followers With Bio
3,366
Followers Without Bio
66.34%
% With Bio
33.66%
% 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 3,162 analyzed218,550
Combined Engagement
13,674
Total Likes
204,876
Total Retweets
43,710
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
100%
With @Mentions
80%
With Links
Topical Analysis:
RT @EliudKipchoge: HISTORY! https://t.co/qjLfofhL5s
RT @vdsar1970: Dear @ManUtd, Enjoy the Future. ♥️ #DreamLikeDonny https://t.co/QVKS3Q0Snk
RT @Tyson_Fury: Monday Motivation. #MentalHealthMatters https://t.co/c7MwaJR84B
Do you prefer 1,2 or 3? ⚽️ @FCBarcelona https://t.co/SSEuF07XF5
RT @GaryLineker: Messi wins his 6th Ballon d’Or. His numbers this year are once again truly extraordinary. He’s head and shoulders the best player in world football. He plays a game that is both joyous and incomprehensible to mere mortals. The award is totally meritorious. 👏🏻👏🏻
Key Insights & Takeaways
Her content often includes interactive questions and challenges, encouraging audience participation. She frequently collaborates with other athletes and brands, expanding her reach. Her use of emojis and casual tone makes her tweets more relatable and engaging.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 92,669
- + 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 @LivCookefs reveals an well-established Twitter presence with 92,669 followers. The account demonstrates a content-creator strategy, averaging 215.3 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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