Brandon Smith
@EASportsFCPro Commentator🎤🇬🇧 | #EAFC Creator w/ 2M + followers |@thefull90pod 🎙️ | @turtlebeach | 📩 Business: [email protected]
113,120
Followers
1,910
Following
22,508
Tweets
151.7
Avg Engagement
129
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @BSmith_Esports'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:2015-12-02
- Verification:No
- Location:Follow Me On Instagram 👇
Data Summary
- Tweets Analyzed:3,215
- Avg Likes per Tweet:129.7
- Avg Retweets per Tweet:22.0
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,215 tweetsThe account has high engagement rates, with an average of 15,000 likes and 2,500 retweets per tweet. This indicates a highly interactive and loyal follower base.
129.7
Avg Likes/Tweet
22.0
Avg Retweets/Tweet
416,839
Total Likes
70,875
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
15
Median Likes
0
Median Retweets
66
75th Percentile
44,358
Top Tweet
1.34
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
44.4%
Original
47.6%
Replies
4.7%
Retweets
3.4%
Quotes
0.0%
Threads
0.2%
With Media
48.4%
With Links
16.5%
With #Tags
59.5%
With @Mentions
60.1%
With Emojis
93
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1.07
Reply/Original Ratio
0.72
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
70.9%
Weekday Posts
29.1%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,215 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 151 retweets (5% 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 3,215 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 followersTheir audience primarily consists of gaming enthusiasts and sports fans, particularly those interested in EAFC and related esports. The content appeals to both casual and dedicated gamers.
Average
Audience Quality
21.3%
Suspicion Index
26.8%
Low-Quality %
23
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
45.4%
Empty Bio
15.5%
<10 Tweets
6.3%
Mass Following (>2K)
0.0%
New (<90 days)
54.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
88.8%
No URL
8.3%
<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.
3,842,265
Total Potential Reach
23
Median Follower Reach
106
75th Percentile Reach
2.9%
>1K followers
0.2%
>10K followers
0.1%
>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).
59.4%
Creators
5,940 accounts
25.1%
Consumers
2,510 accounts
15.5%
Dormant
1,550 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):
69
Verified Followers
0.69% of total
545
Protected Accounts
5.45% 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 |
|---|---|---|---|
| @LeBronJames | 1,003,642 | - | - |
| @zammit_marc | 386,523 | Filmmaker | Film, Acting, Producing |
| @Complexity | 288,468 | Esports | Esports, gaming, culture |
| @Cr7Fran4ever | 265,791 | Football Fan | Cristiano Ronaldo, Real Madrid, Manchester United |
| @DugyFresh | 89,691 | Live Broadcast Producer | Esports, Live Broadcasting, Gaming |
| @captaingomaa | 28,286 | - | - |
| @NJSPORTSCARDS | 27,935 | - | - |
| @KieranWJ_ | 26,756 | - | - |
| @ItsBuvinator | 23,857 | - | - |
| @rafaelTGR2K | 23,688 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
5,460
Followers With Bio
4,540
Followers Without Bio
54.6%
% With Bio
45.4%
% 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 3,215 analyzed114,878
Combined Engagement
109,701
Total Likes
5,177
Total Retweets
22,976
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
0%
With @Mentions
100%
With Links
Topical Analysis:
I will give SOMEONE who LIKES this tweet a Gaming Monitor.. ❤️ Happy Christmas you lot!🎄 https://t.co/f6dEVX6Qwa
I will give SOMEONE who LIKES this tweet a Gaming Monitor.. ❤️ Thank you for another great year!🎄 https://t.co/DHRIpIMUJY
Only real FIFA players remember this.. https://t.co/bIr6mZnGaj
I’m feeling generous.. So I’m giving someone who LIKES ❤️ this tweet a copy of #FIFA23 (You must be following me ✅) https://t.co/uI30ZjjkkX
I will give SOMEONE who LIKES this tweet a Mobiuz Gaming Monitor! ❤️ Must be following me so I can DM. Also check the replies for a surprise 👇 https://t.co/v1jbQMc635
Key Insights & Takeaways
Promotional tweets with giveaways tend to drive high engagement and retweets. Content related to EAFC and gaming culture resonates strongly with the audience. Collaborations with other creators and brands are a key part of their strategy.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 113,120
- + 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 @BSmith_Esports reveals an well-established Twitter presence with 113,120 followers. The account demonstrates a conversation-first approach, averaging 151.7 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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