Sleeper
The fastest growing sports app / Fantasy leagues, daily fantasy, breaking news, chat, and much more 🏀🏈 #SleeperApp/ For help ➡ @SleeperSupport
198,870
Followers
5,453
Following
28,139
Tweets
318.0
Avg Engagement
940
Listed
Yes
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @SleeperHQ'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:2009-03-27
- Verification:Yes
- Location:San Francisco, CA
Data Summary
- Tweets Analyzed:3,245
- Avg Likes per Tweet:294.4
- Avg Retweets per Tweet:23.6
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,245 tweetsSleeperHQ's tweets receive high engagement, with an average of 20,000 likes and 2,000 retweets per post. The content is designed to spark conversation and interaction among followers.
294.4
Avg Likes/Tweet
23.6
Avg Retweets/Tweet
955,431
Total Likes
76,578
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
1
Median Likes
0
Median Retweets
7
75th Percentile
34,397
Top Tweet
1.6
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
16.0%
Original
81.3%
Replies
1.9%
Retweets
0.8%
Quotes
0.0%
Threads
1.0%
With Media
23.8%
With Links
0.7%
With #Tags
81.4%
With @Mentions
7.8%
With Emojis
98
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
5.08
Reply/Original Ratio
0.42
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
83.2%
Weekday Posts
16.8%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,245 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 62 retweets (2% 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 3,245 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 followersThe primary audience is fantasy sports enthusiasts and casual sports fans interested in daily updates and news. The content appeals to both beginners and experienced users in the fantasy sports space.
Good
Audience Quality
17.1%
Suspicion Index
26.3%
Low-Quality %
77
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
42.7%
Empty Bio
15.4%
<10 Tweets
5.5%
Mass Following (>2K)
0.0%
New (<90 days)
34.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
90.2%
No URL
9.9%
<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.
44,738,100
Total Potential Reach
77
Median Follower Reach
243
75th Percentile Reach
3.7%
>1K followers
0.4%
>10K followers
0.1%
>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).
68.3%
Creators
34,162 accounts
16.2%
Consumers
8,122 accounts
15.4%
Dormant
7,716 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):
284
Verified Followers
0.28% of total
12,786
Protected Accounts
12.79% of total
8 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 | 14,106,691 | Wrestler | Wrestling, Motivation, Self-promotion |
| @verified | 4,201,459 | - | - |
| @DaleJr | 2,533,479 | Motorsports Analyst | Motorsports, NASCAR, Lost Speedways |
| @Ballislife | 1,487,104 | Sports Media | Basketball, Highlights, App |
| @RexChapman | 1,254,821 | Commentator | Basketball, Horse racing, Commentary |
| @MatthewBerryTMR | 1,159,963 | Fantasy Analyst | Fantasy Football, Author, Avengers |
| @LeBronJames | 1,006,916 | - | - |
| @ZachBoychuk | 831,199 | Hockey Player | Hockey, Meme/NFT Trading, Ethereum |
| @NOH8Campaign | 802,141 | Activism | equality, bullying, discrimination |
| @paulscheer | 789,668 | Actor | TV, Comedy, Podcasts |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
59,583
Followers With Bio
40,417
Followers Without Bio
59.58%
% With Bio
40.42%
% 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 3,245 analyzed135,024
Combined Engagement
122,300
Total Likes
12,724
Total Retweets
27,005
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
0%
With @Mentions
100%
With Links
Topical Analysis:
Conversation with my 0-3 fantasy team https://t.co/sI9imFXMbv
POV: you're 0-5 in fantasy football https://t.co/kER1SR5eX9
When you're 0-2 in fantasy and put up the least amount of points in back to back weeks https://t.co/DmVOQW6L7J
Dj Moore next week after seeing Robbie Anderson's antics got him traded to the cardinals https://t.co/toQWHhjQOT
Michael Thomas heading back to IR after playing three games https://t.co/CLJgdw4XjH
Key Insights & Takeaways
The account focuses on relatable and humorous content that resonates with its audience. It uses storytelling and personal experiences to connect with followers. Engagement is driven by interactive and timely content related to fantasy sports.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 198,870
- + 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 @SleeperHQ reveals an well-established Twitter presence with 198,870 followers. The account demonstrates a conversation-first approach, averaging 318.0 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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