UNLV Athletics
Official account of UNLV Athletics #BEaREBEL
56,098
Followers
4,104
Following
36,257
Tweets
24.9
Avg Engagement
482
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @UNLVathletics'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:2009-03-07
- Verification:No
- Location:Las Vegas
Data Summary
- Tweets Analyzed:3,250
- Avg Likes per Tweet:10.7
- Avg Retweets per Tweet:14.2
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,250 tweetsThe account maintains a consistent level of engagement with an average of 704 likes and 122 retweets per tweet. This suggests a loyal and active fan base that interacts with the content regularly.
10.7
Avg Likes/Tweet
14.2
Avg Retweets/Tweet
34,842
Total Likes
46,186
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
7
Median Retweets
23
75th Percentile
2,789
Top Tweet
0.44
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Curator
Amplifies others content frequently
14.7%
Original
0.6%
Replies
81.7%
Retweets
3.0%
Quotes
0.0%
Threads
0.5%
With Media
98.7%
With Links
65.3%
With #Tags
91.5%
With @Mentions
63.0%
With Emojis
171
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.04
Reply/Original Ratio
0.04
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
69.1%
Weekday Posts
30.9%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,250 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 2,655 retweets (82% 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 3,250 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 primary audience includes UNLV students, alumni, and sports fans who are interested in college athletics. The content is also likely to attract broader audiences interested in sports events and university culture.
Below Average
Audience Quality
37.5%
Suspicion Index
100.0%
Low-Quality %
81
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
100.0%
Empty Bio
100.0%
<10 Tweets
0.0%
Mass Following (>2K)
0.0%
New (<90 days)
0.0%
Low Ratio (<0.1)
0.0%
New (<180 days)
71.5%
No URL
100.0%
<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.
8,747,210
Total Potential Reach
81
Median Follower Reach
257
75th Percentile Reach
5.5%
>1K followers
0.8%
>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).
0.0%
Creators
0 accounts
0.0%
Consumers
0 accounts
100.0%
Dormant
10,000 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):
0
Verified Followers
0.0% of total
606
Protected Accounts
6.06% 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 |
|---|---|---|---|
| @GuyFieri | 3,505,363 | Chef | Food, Flavor, Cooking |
| @GoodmanHoops | 311,476 | Basketball Analyst | Basketball, Analyst, Hoops |
| @gilliankemmerer | 133,513 | Sports Journalist | KHL, kdrama, archery |
| @DonteWhitner | 125,237 | Football Analyst | Football, Analyst, Capital |
| @TheTateMartell | 122,575 | Entrepreneur | Consulting, Club, Technology |
| @AndrewSportss4 | 94,823 | - | - |
| @BradPyatt | 82,360 | Entrepreneur | Football, Entrepreneurship, Coaching |
| @NCAAFNation247 | 82,279 | Sports Journalist | College Football, Predictions, Fantasy Rankings |
| @JeanChatzky | 81,461 | Financial journalist | finance, writing, podcasting |
| @BrennanMarion4 | 79,092 | Coach | Football, Coaching, Faith |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
7,439
Followers With Bio
2,561
Followers Without Bio
74.39%
% With Bio
25.61%
% 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 3,250 analyzed6,630
Combined Engagement
3,977
Total Likes
2,653
Total Retweets
1,326
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
80%
With @Mentions
100%
With Links
Topical Analysis:
Welcome @Coach_Odom to the Rebel family! 📰 https://t.co/91OJHKS6Sp https://t.co/lxEYL0NlqP
RT @Phillies: Announcing: Bryson Stott. Welcome to the Show, kid. https://t.co/D9VcUtfXBK
🏆 WNBA CHAMPIONS 🏆 @LVAces | #RaiseTheStakes https://t.co/TrSMtZb5g4
Welcome Coach Jeter to the Rebel Family‼️🤩 More info: link in bio #BEaREBEL https://t.co/9RHDNGQIcM
RT @BleacherReport: .@unlvfootball celebrating a TD with their custom slot machine 🎰 🔥 https://t.co/JW8pHL3UGr
Key Insights & Takeaways
The account frequently highlights new coaching hires, which helps build excitement and connection with the community. It celebrates major achievements, such as WNBA championships, to showcase the success of its teams. The use of branded hashtags like #BEaREBEL reinforces team identity and encourages fan participation.
Strengths
- + Established follower base of 56,098
- + 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 @UNLVathletics reveals an growing Twitter presence with 56,098 followers. The account demonstrates a content-creator strategy, averaging 24.9 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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