chona — CS2 Stats
76561198879558678[U:1:919292950]✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · +0.04 avg rating
Player DNA
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 NiKo 75% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower utility contribution; 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
Areas to improve
T-side openings. Opening success drops from 43% on CT to 18% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 673ms 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 4.5/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.
Trends
Rolling 5-match average across the last 100 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 | C | 33 | 14–19 | 42% | -0.00 |
 inferno | B | 19 | 9–10 | 47% | 0.03 |
 overpass | C | 14 | 6–8 | 43% | 0.00 |
 nuke | A | 13 | 8–5 | 62% | 0.00 |
 dust2 | C | 12 | 5–7 | 42% | -0.01 |
 train | — | 3 | 0–3 | 0% | 0.02 |
 vertigo | — | 2 | 0–2 | 0% | -0.05 |
 ancient | — | 2 | 1–1 | 50% | 0.01 |
 anubis | — | 2 | 1–1 | 50% | 0.04 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (42% over 33). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 6 | 33% | 0.87 | 13.3 |
| Dust2 | 4 | 75% | 0.92 | 15.5 |
| Overpass | 2 | 50% | 1.44 | 14.5 |
| Nuke | 1 | 100% | 1.07 | 16.0 |
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.
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4442 — below the 0.5 mark we flag
- 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 18.0556% — 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.
42% win rate across 33 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| mirage | 13–11 | 0.01 | 15% | 3 Apr → | |
| inferno | 7–9 | -0.02 | 14% | 3 Apr → | |
| inferno | 8–8 | 0.06 | 19% | 3 Apr → | |
| nuke | 9–6 | -0.03 | 15% | 3 Apr → | |
| vertigo | 6–9 | -0.07 | 59% | 3 Apr → | |
| inferno | 4–9 | 0.05 | 14% | 3 Apr → | |
| inferno | 9–1 | 0.28 | 16% | 3 Apr → | |
| overpass | 13–9 | 0.05 | 18% | 2 Apr → | |
| mirage | 8–13 | -0.03 | 7% | 24 Jan → | |
| mirage | 13–10 | -0.06 | 23% | 24 Jan → | |
| mirage | 11–13 | -0.05 | 8% | 30 Dec → | |
| dust2 | 13–6 | -0.01 | 10% | 29 Dec → | |
| nuke | 5–13 | -0.02 | 13% | 20 Dec → | |
| mirage | 7–13 | -0.03 | 20% | 30 Nov → | |
| overpass | 13–9 | 0.06 | 11% | 30 Nov → | |
| dust2 | 16–13 | -0.03 | 11% | 29 Nov → | |
| dust2 | 3–13 | -0.06 | 12% | 29 Nov → | |
| mirage | 2–13 | -0.07 | 19% | 29 Nov → | |
| mirage | 13–7 | 0.04 | 17% | 29 Nov → | |
| overpass | 12–0 | 0.06 | 4% | 29 Nov → | |
| dust2 | 15–15 | -0.04 | 22% | 29 Nov → | |
| nuke | 10–1 | 0.07 | 33% | 29 Nov → | |
| mirage | 12–16 | -0.03 | 15% | 29 Nov → | |
| inferno | 1–13 | -0.05 | 21% | 28 Nov → | |
| train | 13–16 | -0.06 | 15% | 28 Nov → | |
| dust2 | 14–16 | 0.02 | 19% | 28 Nov → | |
| mirage | 13–11 | -0.01 | 6% | 28 Nov → | |
| inferno | 11–13 | -0.05 | 14% | 27 Nov → | |
| nuke | 6–13 | -0.06 | 21% | 21 Nov → | |
| overpass | 13–9 | -0.00 | 16% | 21 Nov → | |
| nuke | 13–10 | -0.02 | 19% | 21 Nov → | |
| nuke | 16–13 | -0.06 | 30% | 21 Nov → | |
| dust2 | 9–13 | 0.01 | 13% | 21 Nov → | |
| mirage | 16–14 | -0.03 | 19% | 18 Nov → | |
| inferno | 16–13 | 0.01 | 8% | 18 Nov → | |
| dust2 | 13–4 | 0.06 | 20% | 18 Nov → | |
| mirage | 13–7 | 0.02 | 11% | 18 Nov → | |
| dust2 | 13–16 | -0.04 | 15% | 18 Nov → | |
| nuke | 13–5 | 0.03 | 13% | 18 Nov → | |
| dust2 | 13–10 | -0.08 | 10% | 18 Nov → | |
| dust2 | 13–6 | 0.02 | 16% | 17 Nov → | |
| mirage | 8–13 | -0.03 | 16% | 17 Nov → | |
| overpass | 5–13 | -0.12 | 16% | 17 Nov → | |
| mirage | 13–9 | -0.00 | 14% | 17 Nov → | |
| mirage | 9–13 | -0.03 | 14% | 17 Nov → | |
| inferno | 8–8 | -0.11 | 42% | 31 Oct → | |
| ancient | 3–13 | -0.07 | 22% | 31 Oct → | |
| mirage | 9–13 | -0.05 | 24% | 11 Oct → | |
| inferno | 13–10 | 0.13 | 18% | 11 Oct → | |
| train | 13–16 | 0.09 | 8% | 10 Oct → | |
| dust2 | 6–13 | -0.00 | 21% | 6 Oct → | |
| mirage | 11–3 | 0.02 | 19% | 6 Oct → | |
| train | 4–13 | 0.02 | 18% | 31 May → | |
| anubis | 13–11 | 0.06 | 16% | 9 Jul → | |
| mirage | 13–1 | 0.11 | 32% | 9 Jul → | |
| ancient | 13–4 | 0.08 | 21% | 19 Jun → | |
| inferno | 10–13 | 0.01 | 32% | 19 Jun → | |
| mirage | 13–4 | 0.01 | 35% | 19 Jun → | |
| mirage | 7–13 | -0.00 | 14% | 19 Jun → | |
| mirage | 0–16 | -0.11 | 0% | 1 Jul → | |
| mirage | 9–16 | -0.04 | 10% | 30 Jun → | |
| inferno | 16–8 | 0.08 | 13% | 30 Jun → | |
| nuke | 13–16 | 0.04 | 15% | 30 Jun → | |
| overpass | 16–7 | 0.11 | 16% | 15 Jun → | |
| nuke | 16–10 | -0.01 | 8% | 11 Jun → | |
| inferno | 10–1 | 0.13 | 21% | 11 Jun → | |
| nuke | 10–0 | 0.10 | 13% | 11 Jun → | |
| mirage | 2–16 | 0.01 | 27% | 11 Jun → | |
| overpass | 2–16 | -0.12 | 8% | 11 Jun → | |
| nuke | 12–16 | -0.04 | 6% | 11 Jun → | |
| overpass | 9–16 | 0.05 | 9% | 10 Jun → | |
| inferno | 16–4 | -0.01 | 11% | 10 Jun → | |
| mirage | 15–15 | -0.02 | 5% | 10 Jun → | |
| mirage | 14–16 | -0.10 | 17% | 9 Jun → | |
| inferno | 9–5 | -0.04 | 5% | 30 May → | |
| anubis | 8–16 | 0.02 | 15% | 27 May → | |
| inferno | 5–3 | -0.05 | 7% | 27 May → | |
| mirage | 9–4 | 0.05 | 22% | 27 May → | |
| mirage | 9–4 | 0.13 | 9% | 8 May → | |
| mirage | 13–16 | -0.05 | 10% | 30 Jan → | |
| inferno | 9–10 | 0.11 | 26% | 21 Nov → | |
| mirage | 6–16 | 0.05 | 17% | 21 Nov → | |
| mirage | 13–16 | 0.06 | 16% | 14 Nov → | |
| mirage | 16–12 | 0.05 | 13% | 29 Oct → | |
| inferno | 16–2 | 0.04 | 13% | 25 Oct → | |
| overpass | 5–16 | -0.09 | 26% | 22 Oct → | |
| overpass | 13–16 | -0.02 | 8% | 12 Sept → | |
| overpass | 16–7 | -0.07 | 9% | 11 Sept → | |
| mirage | 5–16 | 0.07 | 18% | 10 Sept → | |
| overpass | 15–15 | 0.05 | 9% | 9 Sept → | |
| mirage | 16–7 | 0.08 | 22% | 9 Sept → | |
| nuke | 11–16 | -0.06 | 8% | 7 Sept → | |
| inferno | 13–16 | -0.03 | 13% | 6 Sept → | |
| dust2 | 14–16 | 0.01 | 19% | 31 Aug → | |
| nuke | 16–0 | 0.10 | 17% | 31 Aug → | |
| vertigo | 4–16 | -0.03 | 11% | 31 Aug → | |
| overpass | 13–16 | 0.04 | 22% | 31 Aug → | |
| overpass | 12–16 | 0.02 | 18% | 31 Aug → | |
| mirage | 13–16 | 0.06 | 19% | 30 Aug → | |
| inferno | 15–15 | 0.04 | 17% | 27 Aug → |
Match data via Leetify.