Oliver Kay
Senior football writer @TheAthleticFC @TheAthletic Author of Forever Young: The Story of Adrian Doherty @ForeverYoungAD https://www.amazon.co.uk/Forever-Young-Adrian-Doherty-Footballs/dp/1848669879/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=&sr=
426,813
Followers
4,652
Following
64,232
Tweets
118.6
Avg Engagement
6,079
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @OliverKay'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: Macro Influencer (100K+)
- Account Age:2010-02-16
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,250
- Avg Likes per Tweet:26.8
- Avg Retweets per Tweet:91.8
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,250 tweetsHis tweets typically receive a high number of likes and retweets, indicating strong audience interaction. The engagement rate suggests his content is well-received and relevant.
26.8
Avg Likes/Tweet
91.8
Avg Retweets/Tweet
87,237
Total Likes
298,248
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
6
Median Retweets
42
75th Percentile
26,747
Top Tweet
0.28
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
10.9%
Original
39.3%
Replies
48.7%
Retweets
1.1%
Quotes
0.0%
Threads
0.3%
With Media
23.3%
With Links
21.2%
With #Tags
89.0%
With @Mentions
17.2%
With Emojis
170
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
3.61
Reply/Original Ratio
0.02
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
80.9%
Weekday Posts
19.1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,250 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 1,583 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 3,250 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 50,000 followersHis followers are likely football fans and enthusiasts interested in in-depth analysis and updates. The audience is engaged with sports news and discussions.
Average
Audience Quality
26.0%
Suspicion Index
28.2%
Low-Quality %
45
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
40.4%
Empty Bio
24.6%
<10 Tweets
15.5%
Mass Following (>2K)
0.0%
New (<90 days)
58.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.6%
No URL
16.0%
<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.
66,827,508
Total Potential Reach
45
Median Follower Reach
189
75th Percentile Reach
6.2%
>1K followers
1.0%
>10K followers
0.3%
>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).
53.6%
Creators
26,814 accounts
21.8%
Consumers
10,886 accounts
24.6%
Dormant
12,300 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):
1,085
Verified Followers
1.07% of total
10,170
Protected Accounts
10.07% 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 | 14,104,177 | Wrestler | Wrestling, Motivation, Self-promotion |
| @midoahm | 5,544,972 | Entrepreneur | Dogs, Father, Founder |
| @UnitedStandMUFC | 1,922,922 | Fan Channel | Manchester United, Global Fanbase, Latest News |
| @toddcarey | 1,685,832 | Musician | Music, Collaboration, Community |
| @TrendEPL | 1,464,233 | Sports Journalist | English Premier League, Different preferences, Best league |
| @utdreport | 1,384,269 | Sports News | Football, Manchester United, News |
| @ManUnitedZone_ | 1,372,817 | - | - |
| @MichelleDBeadle | 1,364,128 | Sports Commentator | Sports, Entertainment, Pop Culture |
| @Robbie9Fowler | 1,163,296 | Footballer | Football, Nike, Podcasts |
| @WatfordFC | 905,789 | Football Club | Football, Hornets, Women |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
61,624
Followers With Bio
39,374
Followers Without Bio
61.02%
% With Bio
38.98%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,250 analyzed69,725
Combined Engagement
10,731
Total Likes
58,994
Total Retweets
13,945
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
80%
With @Mentions
0%
With Links
Topical Analysis:
RT @GrantWahl: Just now: Security guard refusing to let me into the stadium for USA-Wales. “You have to change your shirt. It’s not allowed…
French interior minister says 70% of tickets coming into Stade de France were fake. That would mean 175,000 fake tickets on top of 75,000 attendance Given that, while held at a checkpoint for an hour, I saw zero evidence of any fake tickets, this sounds like TOTAL bullshit
RT @David_Ornstein: 🚨 EXCLUSIVE: Christian Eriksen has verbally agreed to join Manchester United as a free agent. 30yo playmaker has commun…
RT @TheAthleticFC: The Glazer family have instructed banks to handle the sale of Manchester United. The American owners of the Premier Lea…
RT @David_Ornstein: 🚨 EXCLUSIVE: Liverpool have been put up for sale by Fenway Sports Group. Sale deck has been produced for interested par…
Key Insights & Takeaways
His top tweets often highlight significant football-related news and controversies, such as fake tickets at major events. He frequently covers player contracts and transfers, showing interest in club dynamics and player movements. His content is tailored to a niche audience of football fans looking for detailed and timely updates.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 426,813
- + 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 @OliverKay reveals an well-established Twitter presence with 426,813 followers. The account demonstrates a conversation-first approach, averaging 118.6 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.
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