PMU Sport 🔞
🔞 | Avec de meilleures cotes, les émotions sont plus fortes !
100,064
Followers
1,720
Following
50,325
Tweets
66.6
Avg Engagement
246
Listed
Yes
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @PMU_Sport'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:2010-05-12
- Verification:Yes
- Location:France
Data Summary
- Tweets Analyzed:3,247
- Avg Likes per Tweet:24.3
- Avg Retweets per Tweet:42.3
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,247 tweetsThe account has a high average number of likes and retweets, indicating strong audience interaction and interest in the content.
24.3
Avg Likes/Tweet
42.3
Avg Retweets/Tweet
78,873
Total Likes
137,422
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
4
Median Likes
0
Median Retweets
11
75th Percentile
2,424
Top Tweet
0.67
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
55.5%
Original
38.1%
Replies
3.3%
Retweets
3.1%
Quotes
0.0%
Threads
0.1%
With Media
28.2%
With Links
34.8%
With #Tags
42.3%
With @Mentions
74.7%
With Emojis
137
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.69
Reply/Original Ratio
0.93
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
83.7%
Weekday Posts
16.3%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,247 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 107 retweets (3% 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 3,247 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 followersThe audience is primarily interested in football and betting, likely male and aged between 18-45.
Average
Audience Quality
25.4%
Suspicion Index
32.4%
Low-Quality %
18
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
50.2%
Empty Bio
22.6%
<10 Tweets
7.9%
Mass Following (>2K)
0.0%
New (<90 days)
61.1%
Low Ratio (<0.1)
0.0%
New (<180 days)
94.3%
No URL
14.6%
<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.
1,511,742
Total Potential Reach
18
Median Follower Reach
74
75th Percentile Reach
1.9%
>1K followers
0.2%
>10K followers
0.0%
>50K followers
0.0%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
58.5%
Creators
5,847 accounts
18.9%
Consumers
1,889 accounts
22.6%
Dormant
2,264 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):
18
Verified Followers
0.18% of total
431
Protected Accounts
4.31% of total
4 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 |
|---|---|---|---|
| @franju | 72,048 | Influencer | TV, Glass, MegaSn |
| @FredLamboNFT | 46,713 | - | - |
| @web3swiss | 42,760 | Blockchain Expert | Blockchain, Web3, Technology |
| @OM_LeReseau | 40,569 | Football Fan | Football, News, Community |
| @ValueBet3 | 35,653 | - | - |
| @NylonsFet | 25,863 | - | - |
| @theo69prono | 22,496 | - | - |
| @Jo_8313 | 21,436 | - | - |
| @fredpiqoff | 20,880 | - | - |
| @CeDiableDeNgolo | 18,731 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
4,977
Followers With Bio
5,023
Followers Without Bio
49.77%
% With Bio
50.23%
% 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 3,247 analyzed6,180
Combined Engagement
798
Total Likes
5,382
Total Retweets
1,236
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
40%
With @Mentions
100%
With Links
Topical Analysis:
RT @OM_Officiel: 𝗣𝗼𝘂𝗿 𝘁𝗼𝘂𝗷𝗼𝘂𝗿𝘀 𝗱𝗮𝗻𝘀 𝗻𝗼𝘀 𝗰𝗼𝗲𝘂𝗿𝘀 💙 La @Ligue1UberEats ne pouvait reprendre à l’@orangevelodrome sans une pensée pour toi @philousports 🙏 https://t.co/v9gvkXdw88
🤑 20h22, l'heure des freeeeeeebets ! On clôture cette belle journée en vous en offrant 10x22€ 💥 🔃 RT + Follow pour participer ⏳ Tirage demain dans l'après-midi https://t.co/g3pe0jo5Fw
RT @equipedefrance: C'est terminé. Victoire de la Suisse lors de la séance de tirs au but (4-5) #FRASUI #FiersdetreBleus #FRA https://t.co/QundnJWkoX
🥳 Et pour fêter la fin d'année comme il se doit, voici encore un petit concours pour clôturer la journée comme il se doit ! ➡ Tentez de remporter 10x20€ de freebets sans trop forcer, c'est pour nous c'est 🎁 ! 👌 RT + Follow pour participer 🍀 Tirage demain matin https://t.co/NsV
🎁 Et comme d'habitude pour clôturer ces journées, on vous régale une dernière fois pour finir en beauté 🥳 ! ➡ Tentez de remporter 10x20€ de freebets sans trop forcer 😉 ! 👉 RT + Follow pour participer ⏳ Tirage demain matin https://t.co/K7RxHNLW5D
Key Insights & Takeaways
The account uses hashtags and promotions to drive engagement and clicks. It focuses on major football matches and betting opportunities to attract followers. It leverages real-time events to create urgency and increase interaction.
Strengths
- + Established follower base of 100,064
- + 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 @PMU_Sport reveals an growing Twitter presence with 100,064 followers. The account demonstrates a content-creator strategy, averaging 66.6 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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