Matthew Booth OLY 🇿🇦⚽️

Matthew Booth OLY 🇿🇦⚽️

@MatthewBoothZA

@SuperSportTV @unisa BA (PLC) @drugfreesportZA & @OfficialPSL DC tribunal member @ArtificialGraSA @SAFootyLegends Cassock Footballer Olympian

Johannesburg, South Africa https://t.co/jHSMcYnqjV Joined 2016-03-31 Date of Analysis: Dec 16, 2025

38,061

Followers

1,134

Following

3,970

Tweets

373.8

Avg Engagement

17

Listed

No

Verified

Account Overview

What This Report Covers

This comprehensive analysis examines @MatthewBoothZA'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:2016-03-31
  • Verification:No
  • Location:Johannesburg, South Africa

Data Summary

  • Tweets Analyzed:3,165
  • Avg Likes per Tweet:13.6
  • Avg Retweets per Tweet:360.2
  • Followers Analyzed:37,659

Engagement Analysis

Based on 3,165 tweets

His tweets receive a moderate to high level of engagement, with an average of 3,063 likes and 468 retweets per tweet. This suggests a dedicated and interactive audience.

13.6

Avg Likes/Tweet

360.2

Avg Retweets/Tweet

43,032

Total Likes

1,140,091

Total Retweets

Engagement Quality Analysis

Median-based metrics that resist fake virality and outliers.

1

Median Likes

0

Median Retweets

5

75th Percentile

349,686

Top Tweet

9.82

Engagement per 1K Followers

Normalized influence metric

Viral Spikes

Engagement Pattern

Few posts get most engagement

Posting Behavior

Content style and format preferences

Conversationalist

Highly engaged in discussions

15.9%

Original

70.5%

Replies

10.9%

Retweets

2.7%

Quotes

0.0%

Threads

0.3%

With Media

22.9%

With Links

17.6%

With #Tags

93.7%

With @Mentions

40.0%

With Emojis

102

Avg Length

Audience Reaction Profile

Conversational

Engages heavily in discussions

4.43

Reply/Original Ratio

0.25

Quote/RT Ratio

Posting Rhythm

Highly Bursty

Posts in concentrated bursts

75.8%

Weekday Posts

24.2%

Weekend Posts

Top Hashtags

#opinionbooth (24) #exfootballer (15) #sageadvice (14) #armsdeal (13) #agameoftwohalves (13) #safootballlegends (11) #noexcuse (11) #lovechange (9) #afcon2019 (9) #battleofthesports (8)

Most Mentioned

@nealcol (269) @yeswecrann (104) @officialpsl (102) @zulushark (93) @bafanabafana (88) @soniaboothza (88) @matthewboothza (85) @supersporttv (74) @robertmarawa (68) @masandawana (64)

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Content Strategy Analysis

Based on 3,165 tweets

Content Type Distribution

Content Breakdown

Original Tweets 503 (16%)
Replies 2,230 (70%)
Retweets 345 (11%)
Quote Tweets 87 (3%)

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 345 retweets (11% 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 3,165 tweets

Engagement 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 37,659 followers

His audience likely includes sports enthusiasts, students, and professionals in the sports industry. They are interested in his insights on sports, education, and legal matters.

Average

Audience Quality

23.4%

Suspicion Index

22.7%

Low-Quality %

117

Median Reach

Audience Quality Signals

Lower percentages indicate healthier, more authentic followers.

32.3%

Empty Bio

22.2%

<10 Tweets

25.2%

Mass Following (>2K)

0.0%

New (<90 days)

40.1%

Low Ratio (<0.1)

0.0%

New (<180 days)

91.9%

No URL

13.1%

<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.

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Follower Reach & Influence

This account's followers have their own audiences, creating potential for secondary amplification.

86,782,329

Total Potential Reach

117

Median Follower Reach

444

75th Percentile Reach

13.1%

>1K followers

1.5%

>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).

52.4%

Creators

19,726 accounts

25.4%

Consumers

9,557 accounts

22.2%

Dormant

8,376 accounts

132

Verified Followers

0.35% of total

5.8%

Professional Bios

founder, dev, analyst, etc.

0.13

Median Follow Ratio

follower/following

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):

South Africa (2,100) Johannesburg, South Africa (1,879) Pretoria, South Africa (1,129) Cape Town, South Africa (721) Durban, South Africa (691) Johannesburg (385) Pretoria (322) Soweto, South Africa (276) Polokwane, South Africa (257) Bloemfontein, South Africa (239)

132

Verified Followers

0.35% of total

2,598

Protected Accounts

6.9% 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
@JohnCena 14,106,870 Wrestler Wrestling, Motivation, Self-promotion
@verified 4,201,696 - -
@KaizerChiefs 2,771,244 Football Club Football, Soccer, Marketing
@MmusiMaimane 1,984,495 Politician Building, One South Africa, Committed
@ChrisExcel102 1,624,132 Influencer Savage, AssHole, King
@tito_mboweni 1,472,757 Politician Economics, Politics, Agriculture
@OfficialPSL 1,415,907 Sports Organization Soccer, Premier League, Official
@FloydShivambu 1,390,872 Politician Dialectical Materialism, Labour Theory of Value, Revolution
@UlrichJvV 1,147,209 Activist Digital media, Global development, Gardening and sustainability
@Soccer_Laduma 1,063,495 Sports Journalist Soccer, Publication, Africa

Top Keywords in Follower Bios

god (1,828) love (1,603) football (1,469) life (1,467) music (906) sport (834) soccer (747) chiefs (737) father (693) sports (687)

Top Hashtags in Follower Bios

#oncealways (29) #ynwa (20) #sundowns (16) #orlandopirates (15) #khosi4life (13) #god (12) #mufc (12) #upthebucs (9) #kaizerchiefs (9) #the (9)

25,479

Followers With Bio

12,180

Followers Without Bio

67.66%

% With Bio

32.34%

% 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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Viral Tweets

Top 5 by likes+RTs from 3,165 analyzed

680,022

Combined Engagement

0

Total Likes

680,022

Total Retweets

136,004

Avg per Tweet

Key Metrics for Viral Tweets

0%

With Media

0%

With Hashtags

100%

With @Mentions

80%

With Links

Topical Analysis:

Sports Education Social Issues Law Personal Tributes Professional Affiliations

Key Insights & Takeaways

He frequently shares personal and emotional content, such as tributes to fallen individuals, which resonates with his audience. He is active in sports-related discussions and often references specific teams and events. He uses Twitter to highlight his professional roles and affiliations, which helps in building his personal brand.

Strengths

  • + Strong engagement rates above platform average
  • + Established follower base of 38,061
  • + 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 @MatthewBoothZA reveals an well-established Twitter presence with 38,061 followers. The account demonstrates a conversation-first approach, averaging 373.8 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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About This Analysis: This analysis is based on a snapshot of followers, following, and recent tweets. It evaluates structure, quality, and behavior, not historical growth. Metrics like growth rate, momentum, churn, or spike analysis require time-series data which is not available from a single snapshot.

Data collected and analyzed by twtData | Analysis date: Dec 16, 2025