Matt House
Defensive Coordinator, @LSUfootball #GeauxTigers
13,497
Followers
1,390
Following
729
Tweets
88.6
Avg Engagement
32
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @CoachMHouse'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:2015-01-21
- Verification:No
- Location:Baton Rouge, LA
Data Summary
- Tweets Analyzed:594
- Avg Likes per Tweet:9.1
- Avg Retweets per Tweet:79.5
- Followers Analyzed:12,504
Engagement Analysis
Based on 594 tweetsHis tweets receive consistent likes and retweets, indicating a loyal and interactive fan base that appreciates his enthusiasm.
9.1
Avg Likes/Tweet
79.5
Avg Retweets/Tweet
5,423
Total Likes
47,206
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
32
Median Retweets
91
75th Percentile
4,043
Top Tweet
6.56
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
8.4%
Original
0.0%
Replies
91.2%
Retweets
0.3%
Quotes
0.0%
Threads
0.0%
With Media
63.3%
With Links
57.7%
With #Tags
91.9%
With @Mentions
25.4%
With Emojis
108
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.0
Reply/Original Ratio
0.0
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
70.5%
Weekday Posts
29.5%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 594 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 542 retweets (91% 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 594 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 12,504 followersHis audience primarily consists of LSU fans and sports enthusiasts interested in defensive strategies and game highlights.
Good
Audience Quality
14.7%
Suspicion Index
11.8%
Low-Quality %
255
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
19.8%
Empty Bio
7.8%
<10 Tweets
25.0%
Mass Following (>2K)
0.0%
New (<90 days)
21.5%
Low Ratio (<0.1)
0.0%
New (<180 days)
63.9%
No URL
3.8%
<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.
23,188,984
Total Potential Reach
255
Median Follower Reach
687
75th Percentile Reach
18.1%
>1K followers
2.2%
>10K followers
0.4%
>50K followers
0.2%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
72.3%
Creators
9,038 accounts
20.0%
Consumers
2,495 accounts
7.8%
Dormant
971 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):
396
Verified Followers
3.17% of total
804
Protected Accounts
6.43% of total
7 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 |
|---|---|---|---|
| @soledadobrien | 1,320,037 | Journalist | working, mom, journalist |
| @Mathieu_Era | 1,288,519 | Football Player | Football, Defense, Leadership |
| @LSUfootball | 959,568 | Football | Football, Champions, GeauxTigers |
| @TomPelissero | 563,471 | Reporter | NFL, Sports, Family |
| @BruceFeldmanCFB | 370,410 | Reporter | College Football, Sports Reporting, Writing |
| @JoeyMulinaro | 365,585 | Impressionist | Sports, Comedy, Parody |
| @UKAthletics | 355,620 | Sports Administration | Sports, University, Wildcats |
| @Brett_McMurphy | 269,487 | Sports Journalist | College Football, Sports Betting, Journalism |
| @LSUsports | 260,100 | Sports Team | Sports, LSU Tigers, Athletics |
| @Schultz_Report | 241,752 | Sports Analyst | Sports, Analysis, Podcasts |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
10,021
Followers With Bio
2,483
Followers Without Bio
80.14%
% With Bio
19.86%
% 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 594 analyzed8,687
Combined Engagement
0
Total Likes
8,687
Total Retweets
1,737
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
100%
With @Mentions
40%
With Links
Topical Analysis:
RT @CoachGeneChizik: Memo to all Holiday travelers: Just left my plane witnessing an anxious young mom with 3 crying children. One guy was…
RT @UKFootball: HISTORY. MADE. 2018 @CitrusBowl Champions and a 10-win season! #GetUp https://t.co/GRzcm3PCUr
RT @UKFootball: Congratulations to @UKCoachStoops on being named the 2018 @AP SEC Coach of the Year! He is the first UK coach to earn that…
RT @SECNetwork: Congratulations to @UKFootball's Josh Allen for winning the Chuck Bednarik Award for College Defensive Player of the Year!…
RT @UKCoachStoops: Thank you to this team! Love you guys!! https://t.co/vjoOEryaEt
Key Insights & Takeaways
He focuses on celebrating team achievements and player milestones, which resonates well with his followers. His use of hashtags like #BBN and references to specific locations like Lexington suggest a strong local fan connection. He often shares links to game highlights or player stories, indicating a desire to engage with deeper content.
Strengths
- + Established follower base of 13,497
- + 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 @CoachMHouse reveals an growing Twitter presence with 13,497 followers. The account demonstrates a content-creator strategy, averaging 88.6 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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