Alex Kennedy
Chief Content Officer at @basketbllnews | @ESPN contributor | Host of “Running Up The Score” | Previous: @HoopsHype, @USATODAYSports | AlexKennedyNBA@gmail.com
170.133
Followers
4.355
Following
110.176
Tweets
123,6
Avg Engagement
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @AlexKennedyNBA'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:2009-03-06
- Verification:No
- Location:Florida
Data Summary
- Tweets Analyzed:3.250
- Avg Likes per Tweet:12,9
- Avg Retweets per Tweet:110,7
- Followers Analyzed:50.000
Engagement Analysis
Based on 3.250 tweetsThe account maintains a high level of engagement, with consistent likes and retweets, indicating a loyal and active fan base. The content is well-received and often shared across the NBA community.
12,9
Avg Likes/Tweet
110,7
Avg Retweets/Tweet
41.783
Total Likes
359.822
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
4
Median Retweets
18
75th Percentile
35.391
Top Tweet
0,73
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
16,6%
Original
18,6%
Replies
63,4%
Retweets
1,5%
Quotes
0,0%
Threads
0,2%
With Media
30,2%
With Links
2,0%
With #Tags
86,5%
With @Mentions
22,7%
With Emojis
134
Avg Length
Audience Reaction Profile
Conversational
Engages heavily in discussions
1,12
Reply/Original Ratio
0,02
Quote/RT Ratio
Posting Rhythm
Highly Bursty
Posts in concentrated bursts
74,6%
Weekday Posts
25,4%
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 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 2.059 retweets (63% 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 50.000 followersHis audience is primarily NBA fans and sports enthusiasts interested in the latest news, player dynamics, and major league events. The content appeals to both casual and dedicated basketball followers.
Average
Audience Quality
23,2%
Suspicion Index
23,6%
Low-Quality %
74
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
36,4%
Empty Bio
16,9%
<10 Tweets
19,0%
Mass Following (>2K)
0,0%
New (<90 days)
51,6%
Low Ratio (<0.1)
0,0%
New (<180 days)
84,2%
No URL
10,8%
<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.
136.113.953
Total Potential Reach
74
Median Follower Reach
289
75th Percentile Reach
9,3%
>1K followers
1,7%
>10K followers
0,5%
>50K followers
0,3%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
66,6%
Creators
33.305 accounts
16,5%
Consumers
8.231 accounts
16,9%
Dormant
8.464 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):
968
Verified Followers
0.96% of total
12.564
Protected Accounts
12.44% of total
9 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 |
|---|---|---|---|
| @jimmyfallon | 50.764.919 | Comedian | Comedy, TV, Music |
| @TwitterSports | 14.734.170 | - | - |
| @kobebryant | 14.680.455 | Entrepreneur | Basketball, Writing, Producing |
| @JohnCena | 14.100.433 | Wrestler | Wrestling, Motivation, Self-promotion |
| @mcuban | 8.848.891 | Entrepreneur | NFTs, Entrepreneurship, Investing |
| @jack | 6.523.931 | Cryptocurrency Trader | bitcoin, chill, #nostr |
| @DwightHoward | 6.284.386 | Athlete | Basketball, Greatness, Motivation |
| @Wale | 6.217.811 | Writer | anti-hero, super genius, music |
| @wojespn | 5.899.140 | Sports Journalist | NBA, Insider, Podcasting |
| @whoisaddison | 4.836.841 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
61.620
Followers With Bio
39.377
Followers Without Bio
61.01%
% With Bio
38.99%
% 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 analyzed96.954
Combined Engagement
0
Total Likes
96.954
Total Retweets
19.391
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
60%
With Links
Topical Analysis:
RT @HilltopNBA: Kobe & LeBron in the 2008 Olympics 😳 https://t.co/35Q9MmGuu7
RT @CardChronicle: Fake arguing with your coach to distract the defense before throwing a half-look pass for a reverse alley-oop to break a…
RT @spidadmitchell: 😌 https://t.co/QquHyd7DOZ
RT @kobehighlight: RIP Bill Russell. Legends are forever. 🙏 https://t.co/5ADklOjKRy
RT @mikal_bridges: Omygod lol
Key Insights & Takeaways
Focus on NBA milestones and player stories Highlighting major events and their social media impact Emphasis on player relationships and team dynamics
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 170.133
- + 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 @AlexKennedyNBA reveals an well-established Twitter presence with 170.133 followers. The account demonstrates a conversation-first approach, averaging 123,6 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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