> For the complete documentation index, see [llms.txt](https://polyhelper.gitbook.io/polyhelper-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://polyhelper.gitbook.io/polyhelper-docs/analytics-tools/x-analytics.md). # X Analytics **X Analytics** gives you deep posting statistics for any X (Twitter) account directly inside Polymarket — no browsing, no external tools. Built specifically for tweet count markets. Open it via the **Analytics** icon in the right-side panel navigation. The panel has two tabs: **Feed** and **Analytics**. | | | | --------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- | | ![X Analytics Panel](https://raw.githubusercontent.com/polymarkethelper/gitbook/main/.gitbook/assets/x-analytics.png) | ![X Analytics Panel 2](https://raw.githubusercontent.com/polymarkethelper/gitbook/main/.gitbook/assets/x-analytics-2.png) | *** ## What the Panel Shows ### Posts in Window Real-time tracking of posts within the market's resolution period: * **Posts in window** — how many posts have been made so far in the counting period * **Time to close** — how much time remains in the window * **Progress bar** — visual fill of the window * **Avg posts/day** — current average rate within the active window ### Projection Statistical projection of where the final count will land: | Metric | Description | | ------------------------ | ------------------------------------------------------------------------------- | | **Projected (by close)** | Estimated total posts when the market resolves | | **Weekday rate** | Average posts/day on Mon–Fri | | **Weekend rate** | Average posts/day on Sat–Sun | | **vs Linear** | Difference between the statistical projection and a simple linear extrapolation | *Note: statistics-based estimate, not trading advice.* *** ## Tweet History Historical posting data for the account, with a **7d / 30d** selector: | Metric | Description | | ------------- | ---------------------------------------------- | | **Daily avg** | Average posts per day over the selected period | | **Range** | Min–max posts in a single day | | **Weekday** | Average posts/day on Mon–Fri | | **Weekend** | Average posts/day on Sat–Sun | Includes a **line chart** showing daily post count over time — lets you spot spikes, slowdowns, and whether recent activity is above or below historical baseline. *** ## When Does X Post? (UTC) Posting time analysis with **All / Weekday / Weekend** selector: | Metric | Description | | -------------------- | --------------------------------------------------------- | | **Most active hour** | Hour with the highest post count (e.g., 07:00 — 78 posts) | | **Quietest hour** | Hour with the lowest activity | | **Avg/hour** | 24h average across all hours | **Bar chart by time of day** — broken into NIGHT / MORNING / AFTERNOON / EVENING segments, showing the account's typical posting schedule across the full 24-hour cycle. *** ## Avg Posts/Day by Weekday Bar chart showing average daily post count for each day of the week (Mon–Sun) — reveals whether the account posts more on weekdays or weekends, and which specific days are the most active. **Example (@elonmusk):** Mon 31.8 / Tue 15.4 / Wed 28.2 / Thu 25 / Fri 29.8 / Sat 32 / Sun 22.3 *** ## Weekly Totals A week-by-week breakdown showing total posts per calendar week — helps identify trends (increasing activity, quiet periods, etc.) and spot outlier weeks. *** ## Activity Heatmap A GitHub-style calendar heatmap showing posting intensity by day, with a **7d / 14d / 30d** selector. * **Darker blue** = more posts on that day * **Light blue** = below-average activity * **Empty** = no posts The heatmap immediately shows consistency: does the account post every single day, or are there frequent gaps? *** ## How to Use It **For tweet count markets** (e.g., "Will @elonmusk post 100+ tweets May 8–15?"): 1. Check **Posts in window** — how far is the current count from the target? 2. Look at the **Projection** — does the statistical model put the final count above or below the threshold? 3. Check the **Weekly totals** — are recent weeks running above or below the market's implied count? 4. Look at the **Posting time chart** — if most posts happen in the morning (UTC) and the window closes at noon, most activity may already be in **For "will they post at all?" markets:** 1. Check the **Activity heatmap** — does this account ever go silent? 2. Look at the **Weekday/Weekend split** — if the window falls over a weekend and the account typically posts less then, adjust your estimate *** ## Feed Tab Alongside the Analytics tab, the **Feed** tab shows the account's actual recent posts directly in the panel — so you can read the content without leaving Polymarket. *** ## Markets Where This Panel Activates * [Tweet count and posting frequency markets](https://polymarket.com/tech/elon-musk) * [Elon Musk # tweets July 7 – July 14, 2026?](https://polymarket.com/event/elon-musk-of-tweets-july-7-july-14) * Any market about a specific X account's activity --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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