Wanindu Hasaranga
professional cricketer
69,644
Followers
51
Following
115
Tweets
4,336.3
Avg Engagement
52
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @Wanindu49'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:2019-06-05
- Verification:No
- Location:Not specified
Data Summary
- Tweets Analyzed:105
- Avg Likes per Tweet:4,150.1
- Avg Retweets per Tweet:186.2
- Followers Analyzed:50,000
Engagement Analysis
Based on 105 tweetsHis tweets receive a high number of likes and retweets, showing strong audience interaction. The use of hashtags and links to events like the Asia Cup 2022 helps drive engagement.
4,150.1
Avg Likes/Tweet
186.2
Avg Retweets/Tweet
435,758
Total Likes
19,553
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
773
Median Likes
50
Median Retweets
3,356
75th Percentile
82,702
Top Tweet
62.26
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Mixed
Balanced content approach
55.2%
Original
12.4%
Replies
32.4%
Retweets
0.0%
Quotes
0.0%
Threads
0.0%
With Media
66.7%
With Links
50.5%
With #Tags
50.5%
With @Mentions
49.5%
With Emojis
120
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.22
Reply/Original Ratio
0.0
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
74.3%
Weekday Posts
25.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 105 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 34 retweets (32% 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 105 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 followersThe audience primarily consists of cricket enthusiasts and fans, likely from Sri Lanka and other South Asian countries. They are interested in updates about the player and his team's performance.
Average
Audience Quality
34.7%
Suspicion Index
39.6%
Low-Quality %
8
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
48.4%
Empty Bio
46.8%
<10 Tweets
7.1%
Mass Following (>2K)
0.0%
New (<90 days)
80.7%
Low Ratio (<0.1)
0.0%
New (<180 days)
94.8%
No URL
30.8%
<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.
64,038,484
Total Potential Reach
8
Median Follower Reach
36
75th Percentile Reach
1.5%
>1K followers
0.2%
>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).
28.0%
Creators
13,981 accounts
25.3%
Consumers
12,633 accounts
46.8%
Dormant
23,386 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):
148
Verified Followers
0.23% of total
5,203
Protected Accounts
7.97% of total
3 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 |
|---|---|---|---|
| @ImRaina | 20,922,255 | Cricketer | Cricket, Co-Founder, Care |
| @JohnCena | 14,105,748 | Wrestler | Wrestling, Motivation, Self-promotion |
| @RCBTweets | 6,592,318 | Sports Team | Cricket, Bangalore, Official App |
| @cricbuzz | 4,921,277 | Sports News | Cricket, Sports, News |
| @yuzi_chahal | 3,571,210 | Cricketer | Cricket, RCB, Business |
| @TeamQuetta | 1,366,049 | Cricket Team | Cricket, PSL, Quetta |
| @OfficialSLC | 1,265,674 | Sports Organization | Cricket, Sri Lanka, Official |
| @vikranth_offl | 607,593 | Actor | Actor, Admin, Vikranth |
| @MohammadNabi007 | 579,065 | Cricketer | Cricket, Afghanistan, Player |
| @JhaSanjay | 570,914 | Author | Politics, Writing, Chess |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
35,312
Followers With Bio
29,971
Followers Without Bio
54.09%
% With Bio
45.91%
% 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 105 analyzed210,554
Combined Engagement
203,763
Total Likes
6,791
Total Retweets
42,111
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
20%
With Hashtags
20%
With @Mentions
80%
With Links
Topical Analysis:
Champions!! ♥️ #AsiaCup2022 https://t.co/t9mieIC7zi
📍kolkata 🤙 https://t.co/1vKwOVCSNz
Finally got verified on @Twitter. Thank You @IamThilanka! 💫
It has been an honour and privilege. Proud as a Sri Lankan to be representing at the top with these amazing legends. ❤️ https://t.co/fl4BdF8cdr
We experienced it all, amazing highs to heartbreaking lows. We conquered mountains and slipped through the cracks a few times. But what a Journey it was? I am so proud of the RCB family. [1/2] https://t.co/xGWM3TN0jg
Key Insights & Takeaways
High engagement suggests a loyal and active fan base interested in cricket updates and personal milestones. Verified status indicates credibility and recognition within the cricket community. Top tweets highlight key moments like team victories and personal achievements, which resonate well with followers.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 69,644
- + 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 @Wanindu49 reveals an exceptionally influential Twitter presence with 69,644 followers. The account demonstrates a content-creator strategy, averaging 4,336.3 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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