UNLV Football
The official twitter account of UNLV Football #UNLVFB
64,856
Followers
722
Following
8,505
Tweets
88.7
Avg Engagement
319
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @unlvfootball'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:2014-12-15
- Verification:No
- Location:Las Vegas
Data Summary
- Tweets Analyzed:3,250
- Avg Likes per Tweet:66.2
- Avg Retweets per Tweet:22.5
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,250 tweetsThe account averages 1,776 likes and 261 retweets per tweet, indicating moderate to high engagement. The use of multimedia links and hashtags likely contributes to this level of interaction.
66.2
Avg Likes/Tweet
22.5
Avg Retweets/Tweet
215,238
Total Likes
73,183
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
26
Median Likes
14
Median Retweets
116
75th Percentile
3,887
Top Tweet
1.37
Engagement per 1K Followers
Normalized influence metric
Long Tail
Engagement Pattern
Mix of hits and regular posts
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
63.7%
Original
1.4%
Replies
30.1%
Retweets
4.8%
Quotes
0.0%
Threads
0.4%
With Media
82.6%
With Links
54.2%
With #Tags
63.8%
With @Mentions
42.3%
With Emojis
123
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.02
Reply/Original Ratio
0.16
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
54.0%
Weekday Posts
46.0%
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 978 retweets (30% 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 football fans, students, alumni, and sports enthusiasts interested in college football. The content is tailored to appeal to both casual followers and dedicated supporters of the team.
Below Average
Audience Quality
37.5%
Suspicion Index
100.0%
Low-Quality %
117
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)
57.8%
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.
4,805,137
Total Potential Reach
117
Median Follower Reach
252
75th Percentile Reach
3.8%
>1K followers
0.5%
>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).
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
347
Protected Accounts
3.47% of total
2 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 |
|---|---|---|---|
| @NOH8Campaign | 799,389 | Activism | equality, bullying, discrimination |
| @nocontextcfb | 184,521 | - | - |
| @REDBLACKS | 121,625 | Football Team | Football, Ottawa, #RNation |
| @AndrewSportss4 | 94,812 | - | - |
| @BradPyatt | 82,356 | Entrepreneur | Football, Entrepreneurship, Coaching |
| @BrennanMarion4 | 79,074 | Coach | Football, Coaching, Faith |
| @WifeyYoung | 75,329 | - | - |
| @CarmelitaJeter | 68,487 | Sprinter | Track and field, Motivation, Coaching |
| @GoMVB | 56,006 | Athlete Recruiter | Athlete Recruiting, Promotion, College Coaches |
| @BradPowers7 | 54,304 | Sports Bettor | CFB, Betting, Podcast |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
8,958
Followers With Bio
1,042
Followers Without Bio
89.58%
% With Bio
10.42%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,250 analyzed13,349
Combined Engagement
11,756
Total Likes
1,593
Total Retweets
2,670
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
20%
With @Mentions
100%
With Links
Topical Analysis:
UNLV Mourns Passing Of Football Student-Athlete Ryan Keeler https://t.co/wn1xtKZ0OZ https://t.co/1Z4pOyrP0F
That Monday Mood. 🤩 #BEaREBEL https://t.co/txaVbTFXgd
Welcome Coach Marion to the Rebel Family 🤟 📰: https://t.co/SBj64e3WyK https://t.co/P8SRT8VVwQ
Congrats to former @unlvfootball player Javin White for signing with the Raiders‼️ #Stayinghome #BEaREBEL https://t.co/WY1G56F68j
Home. https://t.co/2gQlKtMX1C
Key Insights & Takeaways
The account frequently shares news about players and team events, which helps maintain relevance and connection with followers. It uses hashtags like #BEaREBEL to foster a sense of community and brand identity. The inclusion of multimedia links suggests an effort to drive traffic to official websites or social media pages.
Strengths
- + Established follower base of 64,856
- + 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 @unlvfootball reveals an growing Twitter presence with 64,856 followers. The account demonstrates a content-creator strategy, averaging 88.7 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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