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Tactical Football Analysis engagement report

@TFA_Analysis - 57K followers on X

Measured over 20 original posts from a 30-day window, last computed on October 6, 2026.

Engagement

Middle of its size range
Per follower
0.045%
of 57K followers
Per impression
1.20%
2.2K views on a typical post
Reach
3.80%
of its followers see a post
Typical post
26
interactions (median)
Saved
0.161%
4 bookmarks on a typical post
Posting rate
0.67/day
active 63% of days
Peak time
08:00 UTC
Monday

A typical post picks up 26 interactions against 57K followers, an engagement rate of 0.045%. Measured over 20 original posts, its engagement rate beats 33% of 19,933 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 2.2K times each, and 1.20% of those impressions turn into an interaction. That is about 3.80% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.67 post a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 08:00 UTC, and Monday is the busiest day of the week. Of the 20 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 173 interactions, about 6.7x its own typical post.

Measured over 20 original posts from a 30-day window, last computed on October 6, 2026.

Compared with accounts its own size

Tactical Football Analysis's engagement rate beats 33% of the tracked X accounts closest to it in follower count (19,933 accounts, accounts of similar size (decile 5 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.

On engagement per impression rather than per follower it beats 42% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.

Where this sits in the catalog

At 0.045%, Tactical Football Analysis sits above the 25th percentile of the 201,130 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.141%.

p100.004%
p250.024%
p50 (median)0.141%
p750.671%
p902.53%
p9982.4%
Engagement rate as a share of followers, across the 201,130 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,900 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.004%
25th percentile0.024%
50th percentile0.141%
75th percentile0.671%
90th percentile2.53%
99th percentile82.4%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 08:00 UTC, and Monday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 08:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 08:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%89K
01:00 UTC-2%90K
02:00 UTC-3%88K
03:00 UTC-4%94K
04:00 UTC-5%76K
05:00 UTC-4%75K
06:00 UTC-5%86K
07:00 UTC-5%93K
08:00 UTC-4%108K
09:00 UTC-4%124K
10:00 UTC-3%129K
11:00 UTC-3%141K
12:00 UTC-3%154K
13:00 UTC-3%167K
14:00 UTC-4%173K
15:00 UTC-2%176K
16:00 UTC-3%171K
17:00 UTC-3%159K
18:00 UTC-2%149K
19:00 UTC-2%141K
20:00 UTC-1%131K
21:00 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Monday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Monday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Formats this account uses

Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video100% of posts+111%+108% to +115%34K
Outbound link100% of posts-41%-42% to -40%32K
Typical length-no effect-2% to -1%42K
  • 100% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
  • 100% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
  • Its average post runs 279 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.

These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.

Best tweets

  • Sep 8, 20266.7x their median

    Arsenal moved Rice deeper to get Saka inside. Rice joined the back three, freeing White to push high and Saka to leave the touchline. On the left, Calafiori stepped into midfield. How Arsenal found space against Chelsea’s compact block: https://t.co/qLn3X6Z1Kn https://t.co/L9vumrS86O

    15117418.4K viewsView on X
  • Aug 26, 20263.5x their median

    Chelsea’s front three shaped the game without the ball. They screened midfield, pressed back-foot passes and forced Fulham’s short build-up to go long. The first-minute goal came from that exact trap. How Alonso’s press created the breakthrough: https://t.co/pPQnuQV3PH https://t.co/4zE3vKj2pt

    847105.8K viewsView on X
  • Aug 18, 20263.5x their median

    Arsenal made Phil Foden defend two midfielders at once. Bruno Guimarães and Lewis-Skelly held the same line. Arsenal shifted right, used two wall passes and released Bruno facing forward beyond City’s press. One mechanism behind a 3-0 win 👇 https://t.co/DLyOAb73RH https://t.co/LKhMCsqVES

    7811206.3K viewsView on X
  • Aug 31, 20263.0x their median

    Spurs tried to lock the centre-backs and force Newcastle inside. Nico González turned the trap into an exit: dropping into the back three, releasing full-backs, then finding Dedić diagonally in the move for Elanga’s opener. How Jaissle built a 2-0 win: https://t.co/Tho6LTQ9eq https://t.co/xpAZTcmmXm

    716116.1K viewsView on X
  • Aug 12, 20262.6x their median

    Positional play didn’t die. It forced pressing to evolve, and pressing forced positional play to mutate. In 2017/18, City’s PPDA was 7.15. By 2022/23, four PL teams pressed more aggressively, pushing Guardiola towards a 3-2-4-1. The Tactical Arms Race: https://t.co/aMbcWjIIgT https://t.co/ZYlvXAvzoy

    588205.5K viewsView on X
  • Sep 4, 20262.3x their median

    Ben White created Arsenal’s width at Villa Park by starting inside. His position pulled Villa’s winger and full-back narrow, opening the diagonal for Lewis-Skelly to release him outside. 50% of Arsenal’s attacks came down that flank. The full mechanism: https://t.co/hRYLxFtrTw https://t.co/8bsCpvhw7r

    508103.5K viewsView on X
  • Sep 8, 20262.2x their median

    Man United were too slow to switch play, then too slow to defend the switch. Everton slid across to force them backwards. United left the far side open, and Everton exploited it for their first equaliser. Why United couldn’t protect their lead: https://t.co/C24UNE7W3y https://t.co/mmbqBjjARX

    479102.7K viewsView on X
  • Aug 27, 20261.7x their median

    Manchester United have bought a contradiction in Carlos Baleba. 87th percentile for Defensive IQ. 85th for Activity. 38th for Reliability. He reads danger early and attacks it often. But United need the right partner to turn disruption into control. https://t.co/crrB0gBdqI https://t.co/bYW2YLnUee

    339303.4K viewsView on X
  • Aug 19, 20261.7x their median

    These two frames show why Bruno Guimarães is not another Declan Rice. He drops beside the centre-backs, drives through the first line and finds the forward pass. Rice is then free to cover ground and arrive higher. Why the combination changes Arsenal: https://t.co/gVIh7TEG84 https://t.co/rIBacnkDKN

    385103.1K viewsView on X
  • Aug 25, 20261.6x their median

    Liverpool's warning under Iraola came four minutes in. Both midfielders and full-backs advanced. An underhit pass left Van Dijk and Jacquet alone. Elanga punished the empty rest defence 13 seconds later. But the second goal actually exposed a different problem: https://t.co/8aVortevom

    354213.6K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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Reading these numbers

A typical post picks up 26 interactions against 57K followers, an engagement rate of 0.045%. Measured over 20 original posts, its engagement rate beats 33% of 19,933 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 2.2K times each, and 1.20% of those impressions turn into an interaction. That is about 3.80% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.67 post a day over the last 30 days, with activity on roughly 63% of days. Most posts go out around 08:00 UTC, and Monday is the busiest day of the week. Of the 20 posts sampled, 100% carry an image or video and 100% link out. The account's strongest tracked post pulled 173 interactions, about 6.7x its own typical post.

What is Tactical Football Analysis's engagement rate on X?
Tactical Football Analysis (@TFA_Analysis) has an engagement rate of 0.045%, based on the median interactions across 20 original posts from the last 30 days against 57,160 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.045%, Tactical Football Analysis sits above the 25th percentile of the 201,130 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @TFA_Analysis have real engagement?
Its engagement rate beats 33% of the tracked X accounts closest to it in follower count (19,933 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
When does @TFA_Analysis post?
Most posts go out around 08:00 UTC, and Monday is its busiest day, at roughly 0.67 posts per day across the measured window.

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