♡ E d D i E [ٿ]™ — CS2 Stats
76561198171453297[U:1:211187569]✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -30pp win rate · -0.04 avg rating
Player DNA
Primary style: Support — Utility contribution leads the profile while opening activity stays low.
Strong CT-side openerHigh utility contribution
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
Your pro match
Plays most like Twistzz 85% playstyle similarity
Most alike: positioning profile, utility contribution.
Where you differ: lower opening-fight frequency; lower aim profile.
Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →
Strengths & areas to improve
Strengths
Utility. Utility score of 76 — grenade impact well above the norm.
Areas to improve
T-side openings. Opening success drops from 58% on CT to 4% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 669ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.
CSDB Rating breakdown
Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.
Trends
Rolling 5-match average across the last 58 tracked matches, oldest to newest. The delta compares the first third of the window with the last.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 mirage | D | 24 | 7–17 | 29% | -0.00 |
 inferno | B | 11 | 5–6 | 45% | 0.01 |
 dust2 | D | 7 | 2–5 | 29% | -0.01 |
 nuke | — | 4 | 3–1 | 75% | 0.05 |
 overpass | — | 4 | 3–1 | 75% | 0.01 |
 vertigo | — | 3 | 2–1 | 67% | 0.02 |
 cache | — | 2 | 1–1 | 50% | 0.01 |
 ancient | — | 1 | 1–0 | 100% | 0.05 |
 anubis | — | 1 | 0–1 | 0% | -0.05 |
 train | — | 1 | 1–0 | 100% | 0.00 |
Across the last 58 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (29% over 24). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 5 | 20% | 1.21 | 17.8 |
| Inferno | 2 | 100% | 2.52 | 23.0 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Skill profile
Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.
Recommended for you
Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.
- Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 4.324% — below the 40% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
29% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| mirage | 1–7 | -0.11 | 11% | 18 Jun → | |
| dust2 | 11–13 | 0.02 | 19% | 18 Jun → | |
| dust2 | 15–15 | -0.04 | 19% | 17 Jun → | |
| vertigo | 13–10 | 0.03 | 26% | 30 May → | |
| dust2 | 13–5 | -0.03 | 34% | 30 May → | |
| mirage | 11–13 | -0.00 | 12% | 30 May → | |
| mirage | 9–13 | 0.00 | 20% | 28 May → | |
| dust2 | 4–13 | -0.02 | 19% | 28 May → | |
| inferno | 12–16 | 0.03 | 18% | 13 Nov → | |
| ancient | 13–9 | 0.05 | 8% | 13 Nov → | |
| inferno | 14–16 | -0.01 | 19% | 13 Nov → | |
| anubis | 5–13 | -0.05 | 17% | 13 Nov → | |
| mirage | 13–9 | 0.03 | 15% | 10 Nov → | |
| vertigo | 13–11 | 0.04 | 25% | 10 Nov → | |
| nuke | 13–10 | 0.04 | 23% | 10 Nov → | |
| mirage | 4–13 | 0.02 | 23% | 7 Oct → | |
| mirage | 7–13 | -0.02 | 24% | 6 Oct → | |
| mirage | 13–6 | 0.07 | 29% | 6 Oct → | |
| inferno | 13–2 | 0.21 | 38% | 6 Oct → | |
| inferno | 16–12 | 0.01 | 26% | 5 Oct → | |
| mirage | 11–13 | -0.04 | 18% | 5 Oct → | |
| mirage | 11–13 | 0.04 | 29% | 3 Oct → | |
| inferno | 1–13 | 0.00 | 3% | 28 Sept → | |
| mirage | 13–8 | 0.09 | 30% | 28 Sept → | |
| mirage | 13–10 | 0.01 | 17% | 28 Sept → | |
| inferno | 13–8 | 0.02 | 23% | 28 Sept → | |
| mirage | 13–9 | 0.04 | 25% | 28 Sept → | |
| overpass | 13–3 | 0.12 | 27% | 28 Sept → | |
| vertigo | 6–13 | -0.02 | 15% | 28 Sept → | |
| nuke | 13–7 | 0.03 | 23% | 28 Sept → | |
| inferno | 13–3 | 0.00 | 21% | 28 Sept → | |
| nuke | 13–1 | 0.13 | 12% | 28 Sept → | |
| inferno | 6–13 | -0.03 | 19% | 27 Sept → | |
| mirage | 4–13 | -0.10 | 22% | 27 Sept → | |
| mirage | 10–13 | -0.01 | 12% | 26 Sept → | |
| overpass | 13–9 | -0.00 | 16% | 26 Sept → | |
| mirage | 10–16 | -0.00 | 8% | 31 Aug → | |
| nuke | 4–16 | -0.02 | 18% | 29 Aug → | |
| overpass | 1–16 | -0.07 | 11% | 22 Aug → | |
| mirage | 14–16 | -0.01 | 24% | 18 Aug → | |
| mirage | 10–16 | -0.05 | 8% | 16 Aug → | |
| inferno | 16–14 | 0.04 | 23% | 16 Aug → | |
| mirage | 10–16 | 0.05 | 25% | 16 Aug → | |
| dust2 | 5–16 | 0.01 | 26% | 16 Aug → | |
| inferno | 12–16 | -0.06 | 19% | 15 Aug → | |
| dust2 | 8–16 | -0.02 | 14% | 13 Aug → | |
| mirage | 2–9 | -0.06 | 37% | 13 Aug → | |
| mirage | 10–16 | 0.03 | 15% | 11 Aug → | |
| inferno | 8–16 | -0.05 | 31% | 11 Aug → | |
| mirage | 9–2 | 0.04 | 3% | 9 Aug → | |
| mirage | 16–9 | -0.05 | 13% | 2 Aug → | |
| mirage | 9–16 | -0.01 | 12% | 7 Jul → | |
| dust2 | 16–12 | 0.03 | 33% | 7 Jul → | |
| cache | 16–7 | 0.01 | 22% | 7 Jul → | |
| mirage | 4–16 | -0.04 | 20% | 26 Apr → | |
| overpass | 16–11 | 0.00 | 6% | 16 Oct → | |
| train | 16–12 | 0.00 | 16% | 1 Apr → | |
| cache | 14–16 | 0.00 | 21% | 1 Apr → |
Match data via Leetify.
