81,036
Followers
3,050
Following
5,479
Tweets
193.4
Avg Engagement
286
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @coachchadmorris'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:2011-07-21
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:3,144
- Avg Likes per Tweet:128.8
- Avg Retweets per Tweet:64.7
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,144 tweetsHis tweets typically receive a high number of likes and retweets, indicating strong audience interaction and support.
128.8
Avg Likes/Tweet
64.7
Avg Retweets/Tweet
404,914
Total Likes
203,273
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
32
Median Retweets
136
75th Percentile
6,907
Top Tweet
2.39
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
13.4%
Original
1.3%
Replies
73.1%
Retweets
12.2%
Quotes
0.0%
Threads
0.1%
With Media
94.1%
With Links
60.4%
With #Tags
85.1%
With @Mentions
40.3%
With Emojis
119
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.1
Reply/Original Ratio
0.17
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
75.4%
Weekday Posts
24.6%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,144 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 2,299 retweets (73% 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 3,144 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 followersHis audience appears to be primarily fans of the University of Arkansas football team, given the frequent use of #WPS and references to the Razorbacks.
Good
Audience Quality
18.7%
Suspicion Index
20.1%
Low-Quality %
170
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
27.6%
Empty Bio
17.8%
<10 Tweets
20.7%
Mass Following (>2K)
0.0%
New (<90 days)
30.3%
Low Ratio (<0.1)
0.0%
New (<180 days)
72.5%
No URL
12.5%
<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.
11,729,754
Total Potential Reach
170
Median Follower Reach
491
75th Percentile Reach
12.2%
>1K followers
1.6%
>10K followers
0.3%
>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).
63.8%
Creators
6,382 accounts
18.4%
Consumers
1,843 accounts
17.8%
Dormant
1,775 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):
142
Verified Followers
1.42% of total
742
Protected Accounts
7.42% of total
6 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 |
|---|---|---|---|
| @FootbaIl_Tweets | 438,862 | Football Influencer | Football, Twitter, Advertising |
| @Moreno | 430,045 | Influencer | Business, Manager, Serious |
| @EsfandTV | 368,242 | Streamer | Gaming, Shows, OTKnetwork |
| @JoeyMulinaro | 364,362 | Impressionist | Sports, Comedy, Parody |
| @CoachGusMalzahn | 253,104 | Football Coach | Football, Family, Coaching |
| @LewisHowes | 240,327 | Author/Podcaster | author, podcasting, athlete |
| @Schultz_Report | 200,316 | Sports Analyst | Sports, Analysis, Podcasts |
| @TheRealLilEdd | 166,961 | Mix Engineer | Music, Mixing, Engineering |
| @USFFootball | 147,854 | Football | Football, University, Bulls |
| @dctf | 111,886 | Sports Journalism | Texas football, high school sports, Texas culture |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
7,242
Followers With Bio
2,758
Followers Without Bio
72.42%
% With Bio
27.58%
% 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 3,144 analyzed26,882
Combined Engagement
16,741
Total Likes
10,141
Total Retweets
5,376
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
100%
With Hashtags
20%
With @Mentions
100%
With Links
Topical Analysis:
RT @MySportsUpdate: #Texans rookie QB DeShaun Watson donated his first game check to stadium employees recovering from Hurricane Harvey. https://t.co/mfnbC8OfMG
Ready to get it in the left lane & put the #HammerDown! Let’s go get some Hogs! #WPS https://t.co/dyGKlBzYu9
How’d I do Razorbacks? #WPS #HammerDown https://t.co/QjUrv86mkS
Thanks D-Mac! You know you’re welcome on The Hill anytime! #WPS https://t.co/EB0eQaLNws
Sprinting out the door for this home visit with a game changer tonight be like.... #WPS #RazorbackFAST18 https://t.co/Wb0oFtj8cc
Key Insights & Takeaways
He frequently uses team-specific hashtags like #WPS and #HammerDown, which likely foster a sense of community among fans. His content often includes motivational and team-focused messages, reinforcing his role as a coach and leader. He engages with fans by acknowledging them and encouraging support, which helps build loyalty and connection.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 81,036
- + 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 @coachchadmorris reveals an well-established Twitter presence with 81,036 followers. The account demonstrates a content-creator strategy, averaging 193.4 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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