Holger Badstuber
Former player @FCBayern, @s04, @VfB & @FCL_1901 / @DFB_Team
774,517
Followers
235
Following
1,899
Tweets
368.2
Avg Engagement
960
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Badstuber'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:2013-03-20
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:1,861
- Avg Likes per Tweet:286.4
- Avg Retweets per Tweet:81.8
- Followers Analyzed:50,000
Engagement Analysis
Based on 1,861 tweetsHis tweets receive a significant number of likes and retweets, indicating strong audience interaction. The content is well-received and often shared, reflecting his popularity among followers.
286.4
Avg Likes/Tweet
81.8
Avg Retweets/Tweet
533,001
Total Likes
152,189
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
199
Median Likes
31
Median Retweets
446
75th Percentile
12,299
Top Tweet
0.48
Engagement per 1K Followers
Normalized influence metric
Long Tail
Engagement Pattern
Mix of hits and regular posts
Posting Behavior
Content style and format preferences
Broadcaster
Primarily shares original content
81.0%
Original
6.4%
Replies
6.6%
Retweets
6.0%
Quotes
0.0%
Threads
0.4%
With Media
77.0%
With Links
68.7%
With #Tags
37.0%
With @Mentions
56.7%
With Emojis
86
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.08
Reply/Original Ratio
0.92
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69.2%
Weekday Posts
30.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 1,861 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 122 retweets (7% 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 1,861 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 audience primarily consists of football fans and followers of his career journey. The engagement suggests a loyal and active fan base interested in his personal and professional updates.
Below Average
Audience Quality
41.5%
Suspicion Index
54.1%
Low-Quality %
4
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
60.8%
Empty Bio
60.8%
<10 Tweets
10.3%
Mass Following (>2K)
0.0%
New (<90 days)
86.2%
Low Ratio (<0.1)
0.0%
New (<180 days)
95.3%
No URL
47.4%
<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.
23,103,992
Total Potential Reach
4
Median Follower Reach
28
75th Percentile Reach
1.4%
>1K followers
0.1%
>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).
19.8%
Creators
9,879 accounts
19.5%
Consumers
9,734 accounts
60.8%
Dormant
30,387 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):
51
Verified Followers
0.05% of total
3,835
Protected Accounts
3.8% of total
5 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 | 14,105,278 | Wrestler | Wrestling, Motivation, Self-promotion |
| @KameronBennett | 1,811,638 | DJ | Music, DJing, Booking |
| @tawarayat | 518,514 | Technologist | technology, community radio, education |
| @Moreno | 430,284 | Influencer | Business, Manager, Serious |
| @BixeLizarazu | 354,996 | Footballer | Football, Champion, Ligue des Champions |
| @YourDailyInt | 258,941 | Curiosity Expert | Curious, Learning, Events |
| @ThomasHitz | 241,466 | - | - |
| @HarryGoaz | 236,357 | - | - |
| @BenPavard28 | 202,793 | Footballer | Football, Bayern Munich, France |
| @_cosatu | 170,521 | Labor Union | Labor, Workers' Rights, Solidarity |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
28,533
Followers With Bio
72,466
Followers Without Bio
28.25%
% With Bio
71.75%
% 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 1,861 analyzed29,271
Combined Engagement
20,678
Total Likes
8,593
Total Retweets
5,854
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
60%
With @Mentions
40%
With Links
Topical Analysis:
Liebe Fans… nach 13 Jahren Profi-Fußball gebe ich das Ende meiner Karriere als aktiver Spieler bekannt.
Congrats @FCBayern 🙌💪
GO GERMANY 🇩🇪🇩🇪🇩🇪🏆🏆🏆🏆
RT @FCBayern: #MiaSanMeister 2014/15 http://t.co/6WLpnAGV6g
Happy Birthday, @BSchweinsteiger. All the best, my friend! 🎂🎁👊 https://t.co/hV18d7gsgS
Key Insights & Takeaways
He leverages his football background to connect with fans and maintain relevance. His top tweets often include emotional and career-related messages, which resonate with his audience. He uses hashtags and mentions of clubs to increase visibility and engagement.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 774,517
- + 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 @Badstuber reveals an well-established Twitter presence with 774,517 followers. The account demonstrates a content-creator strategy, averaging 368.2 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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