Major League Soccer
Championship mode. | En español: @MLSes
3,521,911
Followers
9,389
Following
192,309
Tweets
324.7
Avg Engagement
9,380
Listed
Yes
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @MLS'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: Mega Influencer (1M+)
- Account Age:2010-01-21
- Verification:Yes
- Location:U.S. and Canada
Data Summary
- Tweets Analyzed:3,247
- Avg Likes per Tweet:230.2
- Avg Retweets per Tweet:94.6
- Followers Analyzed:50,000
Engagement Analysis
Based on 3,247 tweetsThe account maintains high engagement through timely updates and event promotions. Its verified status and large following contribute to its influence and reach.
230.2
Avg Likes/Tweet
94.6
Avg Retweets/Tweet
747,412
Total Likes
307,047
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
87
Median Likes
17
Median Retweets
283
75th Percentile
81,769
Top Tweet
0.09
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
52.8%
Original
14.3%
Replies
27.8%
Retweets
5.1%
Quotes
0.0%
Threads
0.2%
With Media
68.6%
With Links
42.2%
With #Tags
62.1%
With @Mentions
55.1%
With Emojis
98
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.27
Reply/Original Ratio
0.18
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
62.7%
Weekday Posts
37.3%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,247 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 903 retweets (28% 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 3,247 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 is primarily soccer fans in the U.S. and globally, with a strong interest in MLS teams and players. The content appeals to both casual fans and dedicated supporters.
Average
Audience Quality
28.0%
Suspicion Index
38.0%
Low-Quality %
17
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
48.2%
Empty Bio
37.3%
<10 Tweets
7.3%
Mass Following (>2K)
0.0%
New (<90 days)
57.6%
Low Ratio (<0.1)
0.0%
New (<180 days)
88.8%
No URL
27.8%
<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.
55,633,575
Total Potential Reach
17
Median Follower Reach
101
75th Percentile Reach
3.8%
>1K followers
0.5%
>10K followers
0.2%
>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).
42.5%
Creators
21,226 accounts
20.3%
Consumers
10,133 accounts
37.3%
Dormant
18,641 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):
1,030
Verified Followers
1.02% of total
10,686
Protected Accounts
10.58% of total
4 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 |
|---|---|---|---|
| @BBCSport | 10,747,285 | Sports News | Sports, News, Updates |
| @AppleMusic | 10,299,461 | Music streaming | Music, Social Justice, Diversity |
| @McDonalds | 4,768,716 | Fast Food | Fast Food, Grimace, Friendship |
| @chiellini | 2,624,201 | Calciatore | calcio, Juventus, tecnologia |
| @ctello91 | 1,826,806 | Footballer | Football, Real Betis, Spain |
| @lnstantFoot | 1,696,246 | Football Blogger | Football, Instant, Vivons |
| @Lions | 1,537,151 | Sports Team | Football, Detroit, #OnePride |
| @AppleTV | 1,534,272 | Entertainment | TV, Film, Original Stories |
| @CBSSports | 1,377,907 | Sports Media | Sports, News, Updates |
| @XS_11official | 1,141,047 | Footballer | Football, Music, Fashion |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
55,160
Followers With Bio
45,837
Followers Without Bio
54.62%
% With Bio
45.38%
% 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 3,247 analyzed136,588
Combined Engagement
25,477
Total Likes
111,111
Total Retweets
27,318
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
40%
With Hashtags
60%
With @Mentions
80%
With Links
Topical Analysis:
RT @GarethBale11: https://t.co/QF7AogJXHE
RT @USMNT: WE'RE NOT PACKING OUR BAGS. WE'RE NOT GOING HOME. WE'RE MOVING ON!!!!!!!
Legend of the game. RIP, Pele. ❤️ https://t.co/smRk1zi5gt
Matt Turner's preparing the Gunners for a stateside trip to remember. @Arsenal will face the best of MLS in Washington, DC, for the 2023 #MLSAllStar Game presented by @Target! https://t.co/hYuCW0eb0y
GARETH BALE EQUALIZES IN STOPPAGE TIME OF EXTRATIME!! #MLSCUP https://t.co/iWqfU9FAWG
Key Insights & Takeaways
The account frequently highlights major events like the MLS All-Star Game and MLS Cup, which drive engagement. It uses emotional content, such as tributes to legends like Pele, to connect with fans. Promoting player stories and team preparations helps build a sense of community and excitement around the league.
Strengths
- + Strong engagement rates above platform average
- + Established follower base of 3,521,911
- + 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 @MLS reveals an well-established Twitter presence with 3,521,911 followers. The account demonstrates a content-creator strategy, averaging 324.7 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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