Leah Galton
@manutdwomen #11 ⚽️ @adidas athlete. Agent: luca@volantesports.com
28,719
Followers
180
Following
573
Tweets
133.5
Avg Engagement
104
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @leah_galton21'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:2017-08-03
- Verification:No
- Location:United Kingdom
Data Summary
- Tweets Analyzed:559
- Avg Likes per Tweet:73.6
- Avg Retweets per Tweet:60.0
- Followers Analyzed:27,064
Engagement Analysis
Based on 559 tweetsHer tweets receive an average of 239 likes and 20 retweets, indicating a consistent but not highly interactive audience.
73.6
Avg Likes/Tweet
60.0
Avg Retweets/Tweet
41,121
Total Likes
33,513
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
1
Median Likes
8
Median Retweets
134
75th Percentile
4,722
Top Tweet
4.65
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Curator
Amplifies others content frequently
8.1%
Original
7.7%
Replies
48.7%
Retweets
35.6%
Quotes
0.0%
Threads
0.0%
With Media
72.6%
With Links
28.8%
With #Tags
61.4%
With @Mentions
61.4%
With Emojis
80
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.96
Reply/Original Ratio
0.73
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
62.6%
Weekday Posts
37.4%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 559 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 272 retweets (49% 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 559 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 27,064 followersHer audience appears to be fans of football, especially Manchester United Women, and Adidas enthusiasts.
Average
Audience Quality
25.0%
Suspicion Index
23.3%
Low-Quality %
62
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
32.8%
Empty Bio
22.4%
<10 Tweets
20.1%
Mass Following (>2K)
0.0%
New (<90 days)
54.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.6%
No URL
13.8%
<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.
70,712,811
Total Potential Reach
62
Median Follower Reach
250
75th Percentile Reach
7.9%
>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).
56.0%
Creators
15,154 accounts
21.6%
Consumers
5,842 accounts
22.4%
Dormant
6,068 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):
177
Verified Followers
0.65% of total
2,693
Protected Accounts
9.95% 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 |
|---|---|---|---|
| @ManUtd | 35,590,625 | Sports Team | Football, Manchester, United |
| @adidasfootball | 4,046,316 | Sports Brand | Sport, Change, Power |
| @BBCMOTD | 3,358,178 | Football Coverage | football, coverage, follow |
| @IanWright0 | 2,282,653 | Footballer | Football, Podcasting, Writing |
| @UnitedStandMUFC | 1,913,235 | Fan Channel | Manchester United, Global Fanbase, Latest News |
| @ManUtdMEN | 1,618,409 | Sports Journalist | Football, Manchester United, News |
| @ManUtd_Es | 1,552,074 | Fútbol | Football, Manchester United, Español |
| @EamonnHolmes | 1,103,778 | TV Presenter | TV, Trustee, Television |
| @UtdDistrict | 739,694 | Sports Journalist | Football, Manchester United, Coverage |
| @Moreno | 430,153 | Influencer | Business, Manager, Serious |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
18,198
Followers With Bio
8,866
Followers Without Bio
67.24%
% With Bio
32.76%
% 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 559 analyzed13,986
Combined Engagement
1,815
Total Likes
12,171
Total Retweets
2,797
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @ManUtd: Introducing our 18/19 @adidasfootball away shirt. On sale 13.09.18 from adidas and club stores. https://t.co/ZFJ03Eiuvp
RT @CaseyStoney: An absolute honour and privilege to be the head coach on this exciting journey with the biggest club in the world #MUFC ht…
RT @adidas: https://t.co/qEvnRs86dc
RT @AnneMarie: I miss football.
People need to stop with the abusive messages. It’s ridiculous @StanwayGeorgia I hope you are okay. Thankyou for your apology. 🤝 https://t.co/ODgFFWXTpG
Key Insights & Takeaways
She leverages her association with Manchester United Women and Adidas to build her personal brand. Her content often includes links to social media profiles and brand-related posts. She uses emojis and hashtags to enhance visibility and engagement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 28,719
- + 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 @leah_galton21 reveals an well-established Twitter presence with 28,719 followers. The account demonstrates a content-creator strategy, averaging 133.5 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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