XO engagement report
@Trader_XO - 551K followers on X
Measured over 12 original posts from a 30-day window, last computed on October 14, 2026.
Engagement
A typical post picks up 402 interactions against 551K followers, an engagement rate of 0.073%. Measured over 12 original posts, its engagement rate beats 66% of 20,444 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 56K times each, and 0.724% of those impressions turn into an interaction. That is about 10.1% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, with activity on roughly 77% of days. Most posts go out around 15:00 UTC, and Tuesday is the busiest day of the week. Of the 12 posts sampled, 58% carry an image or video and 25% are part of a thread. The account's strongest tracked post pulled 1.6K interactions, about 4.8x its own typical post.
Measured over 12 original posts from a 30-day window, last computed on October 14, 2026.
Compared with accounts its own size
XO's engagement rate beats 66% of the tracked X accounts closest to it in follower count (20,444 accounts, accounts of similar size (decile 10 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 39% 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 0.073%, XO sits above the 25th percentile of the 205,048 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.678% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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 15:00 UTC, and Tuesday 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 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 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
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.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 58% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 0% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 58% 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.
- 0% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 302 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
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
- Aug 11, 20254.8x their median
Auction Context – Market Profile as Your Map Before you think about placing a trade, you want to know where in the auction cycle the market is. Market Profile gives you the structure that most traders don’t see when they’re staring at candlesticks. 5 Core Concepts to Track: 1. Value Area High (VAH) / Value Area Low (VAL) Defines the 70% of the session’s volume where most business was done. Outside of value = “expensive” or “cheap” to the market participants. 2. Point of Control (POC) Price with the most activity = a magnet in balance conditions. 3. Main Day Type Recognition (there are others) 3.1 Balanced -> Mean reversion more likely. 3.2Trend Day -> Initiative activity dominates which means profile elongates in one direction. 3.3 Double Distribution → Two distinct value zones; mid-point acts as a pivot. 4. Structural References Single prints, low-volume nodes (LVNs) and (HVNs), poor highs/lows, unfinished auctions, each can act as magnets or barriers. 5. Why this matters: Knowing the auction context lets you pre-define where business is likely to occur and where rejections are probable = which stops you from chasing every micro move. NOW ONTO GAME PLAN: Auction context feeds into your game plan. You’re answering the following: “Am I a buyer, seller, or observer today?” “Where is my line in the sand?” Premarket Prep Routine: - Mark prior session VAH, VAL, POC. - Mark overnight high/low and see how they relate to prior value. - Note anomalies (e.g., single prints) that could be filled. Decide if you’re looking for: Initiative trades (price driving away from value) ? Responsive trades (price returning to value) ? Bias Examples: Open above VAH + holding → Look for longs if order flow supports continuation. Open inside prior value → Fade moves to VAH or VAL unless initiative order flow breaks out. Mindset: You should be able to write your bias in one sentence before the open. If you can’t, you’re not ready to trade. Anyway just my 1 cent whilst Im watching a trade develop - cheers
- May 28, 20263.0x their median
https://t.co/Zl3zv8d69B
- Jul 11, 20263.6x their median
$BTC Higher Time Frame Having shorted this move from the 125s, I personally see little value in continuing to press swing shorts at these levels. My focus has shifted back toward spot accumulation, where I believe the more attractive asymmetric play lies in identifying high-quality buying opportunities for the longer-term move over the next several quarters.
- Jul 17, 20262.7x their median
I just want to say a genuine thank you to everyone who took part in the XO Mentorship. What was initially meant to run for four weeks ended up continuing from March last year, becoming far more substantial than I had ever anticipated. It was practically free, but we covered what I consider to be the core foundations of a real trading process. More specifically, the core framework I’ve built and refined over several years through hands-on experience, costly mistakes, and strict accountability. We worked through the full development cycle of a discretionary trader: • Building the necessary tracking & review sheets • Developing a repeatable strategy / playbook • Reading order flow & refining trade execution • Managing risk & navigating psychological demands I also shared some of my own trade execution strategies which many had asked for, and seeing many of you apply them effectively within your own processes has been incredible. More importantly, the mentorship was about learning how to think independently. How to review your decisions honestly, isolate recurring flaws, refine what works, and ultimately carve out an edge through repetition, data, and deliberate performance review. These same foundations shaped my own development and played a major role in helping me become successful over the long term. They are not a shortcut. In my view, they represent the absolute minimum level of structure, discipline, and effort required to give yourself a genuine chance because this is a very hard game. The most rewarding part has been watching that progression unfold. The quality of your analysis, journaling, market commentary, and independent thinking has improved significantly. I see so many of you now approach the market with far greater clarity, context, structure, and accountability than when you first joined. That progress belongs entirely to those who stayed committed, remained open-minded, and did the work. Teaching also forced me to look inward. Breaking down ideas that had become instinctive pushed me to question, organise, and understand my own process at a deeper level, sharpening my own game along the way. I’ve already started working on further topics that interest me, so keep an eye out for Jan 2027 for whatever comes next. Thank you again for taking part, contributing, and trusting the process. I am genuinely proud of the development I’ve seen. Wishing you all continued progress, success, and prosperity in trading and in life. Stay blessed. XO
- Apr 27, 20262.9x their median
Beyond A Decade of Setups The technicals, the probabilities, the execution, and the trader. ---THE TECHNICALS--- For me, technical improvements came from being able to read the market in real time and understand what was likely happening underneath the surface at inflection points: the flows, the positioning, and the reaction at a level. That’s where microstructure started to matter. The signs of price failure. The shift in momentum. Tape speed and volume being supported by flows. Understanding price and flow mechanics when the same conditions kept showing up again and again. I saw it enough times that eventually it stopped feeling like noise. It became data I could interpret and reason about. Once I could define the structure, understand the pattern, and recognise the flows behind it, I knew I could read the market in almost real time and identify a possible execution trigger. But from experience, that was still only a small part of the game. ---THE PROBABILITIES--- One of the questions I started asking myself was: how do I grade my performance if I don’t even know how to measure or quantify what I’m actually trading? For example, placing a stop at some random swing high. How do I measure that over 100 trades? What parameters am I actually tuning? How do I know what’s improving and what’s just noise? Are my MAE/MFE stats meaningful at all? That was a big realisation for me. How could I really perform at a high level if parts of my process were still random and carrying a high degree of variance? Maybe I could do okay. But was okay good enough? The real question became whether I could trade this with a measurable probability in my favour. Not perfectly. But consistently enough to know I wasn’t just operating from randomness. I was operating with purpose and probability. ---THE EXECUTION--- The deeper work, for me, has been myself as the trader and the process - not just the technicals alone. I spent a long time obsessing over price action, order flow, and technicals, while neglecting the part that was actually affecting my performance. I realised I could study price charts all I wanted. Technical skill alone wasn’t going to move the needle. I got better technically, but the same flaws in my game kept resurfacing because I hadn’t dealt with them properly. For me, the strategy in isolation was never really the issue. It was executing when emotion was at its highest. In my own trading, the problem often wasn’t that I lacked a setup. It was the execution around it - entering too early, exiting too late, cutting too soon, sizing poorly, or freezing when the decision actually mattered. So I had to ask myself... Could I explain one of my execution strategies in detail, beyond just saying “look for an SFP”? Could I explain the logic behind it? Why it works? Where it should work? What I’m actually trying to capture? Because “look for an SFP” isn’t a strategy. It’s a label. Second-guessing, hesitating, cutting too early, oversizing, and letting fear, frustration, or ego influence the decision-making process. I’ve dealt with all of it for years. And if I’m not fully locked in, it can still creep back in. For me, the struggle hasn’t always been finding opportunity. Opportunities always exist. The challenge is executing cleanly when it matters. The entry. The management. The exit. The full trade life cycle and the statistics around it. That’s the part I obsess over most now. It serves as a constant feedback loop - the quality of which depends on how honest I’m willing to be with myself. I know what I’m looking for. The countless hours spent testing, reviewing trades, studying price, and collecting data are all part of turning that into a real strategy. So the focus is simple: better preparation, better review, better sizing, more patience, and cleaner execution. Small improvements, repeated consistently. The 1% changes that compound - think Atomic Habits. ---THE TRADER--- At some point, trading became less about proving I was right and more about executing what I said I would execute. Not forcing trades. Not reacting emotionally. Not needing to be right. Not caring as much about what everyone else is doing on X. Just trying to execute a defined process with purpose. Variance will always exist. Losses will always be part of the game. But with enough data, review, and self-awareness, I started to move away from randomness. I started narrowing the window of variance - which, in my opinion, is one of the hardest parts of becoming a better trader. Because if the parameters I journal aren’t quantifiable, what am I really journaling? Dogshit data. Randomness. This matters with things like stop placement, sizing, and trade management. By bringing more systemisation into my execution - whether that’s structured sizing, defined risk, Kelly Criterion, or whatever framework suits the way I trade - I can narrow the window of variance and trade with more intent. Let the process do its work. That’s what it comes down to for me: Building the structure. Refining the performance. Becoming the trader capable of executing it. Because performance isn’t just the setup. Performance is how I execute the setup and manage the entire trade life cycle - from strategy creation, to initiation, to execution, to performance review. Not really giving a flying f**k what anyone else says or does. Just me against me - sharing my experiences and own journey... mainly talking to myself but hope someone finds it insightful.
- Sep 25, 20262.1x their median
You aim to make 5-6% per month on a perps account - compounded over 12 months - your starting balance is 100k For the next 5 years Note* this is seperate from going all in on some alt / stock A repeatable process…. Would you be content with that or not - and why ?
- Sep 15, 20252.1x their median
$BTC Inflection points... GM https://t.co/NQe4XtHLQX
- Oct 9, 20261.7x their median
Having an opinion on the market and actually expressing that view with real risk are two entirely different things. Market analysis and execution are completely separate disciplines tbh Trading requires a level of edge, execution, and total accountability, not just talking about price action after the fact... or stating the obvious... Shit loads of crypto YouTubers dropping daily commentary are usually the furthest removed from actual trading. Zero risk, no skin in the game, churning out useless noise every 24 hours just to funnel people into a some dogshit paid service / flogging some indicator... It is what it is...
- Jul 2, 20261.9x their median
Bitcoin has never followed a negative June with a negative July. Since 2013: • 7/7 positive Julys after a negative June • Average July: +13.9% • Median July: +16.8% https://t.co/5clWIwb6CL
- Sep 5, 2026
ok back to normal trades this trench stuff is fun but its very dangerous it puts you in a hyper gambling state of mind and its destructive the only really way to make money in this is to have a) sophisticated system/software where you can identify opportunities appropriately, size in accordingly, and have strict trade management skills b) bid known winners and size into those appropriately c) insider info c) deploy your own tokens and rug everyone
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 402 interactions against 551K followers, an engagement rate of 0.073%. Measured over 12 original posts, its engagement rate beats 66% of 20,444 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 56K times each, and 0.724% of those impressions turn into an interaction. That is about 10.1% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, with activity on roughly 77% of days. Most posts go out around 15:00 UTC, and Tuesday is the busiest day of the week. Of the 12 posts sampled, 58% carry an image or video and 25% are part of a thread. The account's strongest tracked post pulled 1.6K interactions, about 4.8x its own typical post.
- What is XO's engagement rate on X?
- XO (@Trader_XO) has an engagement rate of 0.073%, based on the median interactions across 12 original posts from the last 30 days against 550,673 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.073%, XO sits above the 25th percentile of the 205,048 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 @Trader_XO have real engagement?
- Its engagement rate beats 66% of the tracked X accounts closest to it in follower count (20,444 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 @Trader_XO post?
- Most posts go out around 15:00 UTC, and Tuesday is its busiest day, at roughly 2.63 posts per day across the measured window.