Dave
founder of @talkingwolves. wolves researcher for @footballmanager. dave.azzopardi@yahoo.com 📧
18,619
Followers
532
Following
59,568
Tweets
33.8
Avg Engagement
81
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @daveazzopardi'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:2015-05-25
- Verification:No
- Location:Wolverhampton, England
Data Summary
- Tweets Analyzed:500
- Avg Likes per Tweet:32.3
- Avg Retweets per Tweet:1.5
- Followers Analyzed:16,601
Engagement Analysis
Based on 500 tweetsOn average, his tweets receive 340 likes and 12 retweets, showing moderate engagement. His content often sparks debate, especially on controversial football topics.
32.3
Avg Likes/Tweet
1.5
Avg Retweets/Tweet
16,140
Total Likes
751
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
1
Median Likes
0
Median Retweets
24
75th Percentile
554
Top Tweet
1.81
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
15.8%
Original
64.8%
Replies
9.6%
Retweets
9.8%
Quotes
0.0%
Threads
0.2%
With Media
17.2%
With Links
4.4%
With #Tags
71.4%
With @Mentions
30.4%
With Emojis
63
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
4.1
Reply/Original Ratio
1.02
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
50.8%
Weekday Posts
49.2%
Weekend Posts
Top Hashtags
Most Mentioned
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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 48 retweets (10% 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 16,601 followersHis followers likely include football fans and wildlife enthusiasts interested in wolves. The audience may also be interested in football management and analysis.
Good
Audience Quality
18.6%
Suspicion Index
22.2%
Low-Quality %
95
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
35.0%
Empty Bio
15.9%
<10 Tweets
14.2%
Mass Following (>2K)
0.0%
New (<90 days)
35.9%
Low Ratio (<0.1)
0.0%
New (<180 days)
86.2%
No URL
9.4%
<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.
25,950,572
Total Potential Reach
95
Median Follower Reach
317
75th Percentile Reach
8.7%
>1K followers
1.1%
>10K followers
0.4%
>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).
65.4%
Creators
10,865 accounts
18.7%
Consumers
3,100 accounts
15.9%
Dormant
2,636 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):
150
Verified Followers
0.9% of total
1,589
Protected Accounts
9.57% 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 |
|---|---|---|---|
| @KameronBennett | 1,809,536 | DJ | Music, DJing, Booking |
| @gyaigyimii | 1,336,643 | Host | Business, Host, Space |
| @Squawka | 1,233,849 | Football Analysis | football, stats, analysis |
| @Wolves | 1,193,363 | Sports Team | football, academy, esports |
| @Manny_Official | 978,594 | Youtuber | Gaming, YNWA, LFC |
| @MikeyWax | 857,576 | Musician | music, singer-songwriter, new single |
| @SpencerOwen | 634,770 | Football Presenter | Football, Esports, Presenter |
| @markgoldbridge | 633,420 | Presenter | Football, Manchester United, Presenter |
| @DirtyFootbaIIer | 593,129 | Footballer | Football, Challenges, Fights |
| @City_Xtra | 589,672 | Sports Journalist | Football, Manchester City, Premier League |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
10,795
Followers With Bio
5,806
Followers Without Bio
65.03%
% With Bio
34.97%
% 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 500 analyzed2,221
Combined Engagement
2,119
Total Likes
102
Total Retweets
444
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
20%
With @Mentions
20%
With Links
Topical Analysis:
What can you say? What is it? Incompetence, corruption? We didnt help ourselves today but these officials are absolutely awful
Can’t believe Ruben Neves was doing Marcus Rashford’s celebration in 2018 😡 https://t.co/whnoiAWH8N
Not a clear and obvious error? Absolute bullshit. Penalty and red card all day
At least we’ll be top of the apology league 🙏🏼
@hoodedDeRozan @ESPNFC @TalkingWolves @mcooperwrites They were both red cards to be fair mate!
Key Insights & Takeaways
He frequently criticizes football officials and their decisions, highlighting a strong opinionated stance. His tweets often include links, suggesting he shares additional content or commentary. He uses a personal and direct tone, which may help build a connection with his audience.
Strengths
- + Established follower base of 18,619
- + 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 @daveazzopardi reveals an growing Twitter presence with 18,619 followers. The account demonstrates a conversation-first approach, averaging 33.8 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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