kawai — CS2 Stats
FO76561199822451619[U:1:1862185891]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 7 Nov 2026 (7 days ago). Ranks are recorded once per day this page is viewed.
No change since then — still 477 tracked matches. Play, then come back: the next observation lands here.
Rating over time
Premier CS Rating
- At peak — 29,546
- 0 over 30 days · steady
- +4,547 over 90 days
- Next: Gold band at 30,000 — 454 to go
- Reached: Red band · Pink band · Purple band · Blue band
- Red band first seen 2026-09-01
- Pink band first seen 2026-09-01
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: 0pp win rate · −0.09 avg rating · −35.4pp headshot accuracy · +173ms reaction
Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.
Last 5 · 10 · 20 matches
Last 5
- 4–1 · 80% win rate
- Avg rating 0.01
- Avg headshot accuracy 17%
- Avg reaction 628ms
Last 10
- 9–1 · 90% win rate
- Avg rating 0.05
- Avg headshot accuracy 36%
- Avg reaction 430ms
Last 20
- 18–2 · 90% win rate
- Avg rating 0.09
- Avg headshot accuracy 54%
- Avg reaction 344ms
Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.
Player DNA
Primary style: Opening Duellist — Winning opening duels is what stands out in this profile (+4 against its own average). How often you WIN the first duel — CSDB cannot yet see how often you take it.
Sharp aimerStrong CT-side openerLimited utility dependence
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.
Your pro match
Plays most like donk 54% playstyle similarity
Most alike: aim profile, positioning profile.
Where you differ: higher opening-duel success; lower utility contribution.
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
Aim. Aim score of 100 — the mechanical foundation is a clear strength.
CT openings. 75% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
T openings. 61% T opening-duel success — entries that actually open the round.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
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 7.7/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 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.
Personal bests
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 mirage | S | 21 | 20–1 | 95% | 0.10 |
 dust2 | S | 21 | 17–4 | 81% | 0.12 |
 inferno | S | 11 | 8–3 | 73% | 0.06 |
| office | S | 10 | 9–1 | 90% | 0.09 |
 nuke | S | 9 | 8–1 | 89% | 0.09 |
 train | S | 7 | 7–0 | 100% | 0.10 |
 cache | S | 6 | 5–1 | 83% | 0.10 |
 ancient | S | 5 | 5–0 | 100% | 0.15 |
 anubis | — | 4 | 4–0 | 100% | 0.14 |
 overpass | — | 3 | 3–0 | 100% | 0.15 |
 vertigo | — | 2 | 2–0 | 100% | 0.08 |
| italy | — | 1 | 1–0 | 100% | 0.18 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (73% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 36 | 53% | 0.96 | 17.0 |
| Dust2 | 27 | 78% | 1.17 | 16.3 |
| Inferno | 3 | 67% | 1.19 | 22.7 |
| Nuke | 3 | 67% | 0.70 | 14.3 |
| Train | 1 | 0% | 0.45 | 9.0 |
| Ancient | 1 | 0% | 0.82 | 14.0 |
| Anubis | 1 | 0% | 0.53 | 8.0 |
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 0.1459 — below the 0.5 mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| office | 13–7 | -0.01 | 20% | 28 Oct → | |
| cache | 13–8 | -0.02 | 12% | 21 Oct → | |
| mirage | 13–4 | 0.01 | 15% | 20 Oct → | |
| mirage | 3–13 | 0.03 | 17% | 20 Oct → | |
| dust2 | 13–8 | 0.05 | 20% | 20 Oct → | |
| train | 13–3 | 0.08 | 20% | 7 Oct → | |
| train | 13–10 | 0.20 | 34% | 7 Oct → | |
| inferno | 9–4 | 0.01 | 33% | 7 Oct → | |
| train | 13–1 | 0.13 | 91% | 7 Oct → | |
| train | 9–5 | -0.03 | 100% | 7 Oct → | |
| train | 13–5 | 0.24 | 100% | 7 Oct → | |
| cache | 4–1 | 0.17 | 75% | 6 Oct → | |
| nuke | 13–1 | 0.01 | 78% | 6 Oct → | |
| nuke | 13–8 | 0.05 | 42% | 6 Oct → | |
| cache | 3–0 | 0.03 | 75% | 5 Oct → | |
| ancient | 13–3 | 0.24 | 72% | 5 Oct → | |
| anubis | 3–0 | 0.24 | 67% | 5 Oct → | |
| ancient | 12–2 | 0.18 | 47% | 5 Oct → | |
| cache | 3–13 | 0.11 | 59% | 4 Oct → | |
| ancient | 7–1 | 0.08 | 100% | 4 Oct → | |
| italy | 9–5 | 0.18 | 40% | 4 Oct → | |
| mirage | 13–9 | 0.23 | 55% | 4 Oct → | |
| nuke | 13–6 | 0.11 | 55% | 2 Oct → | |
| overpass | 4–0 | 0.11 | 100% | 2 Oct → | |
| overpass | 13–2 | 0.18 | 37% | 2 Oct → | |
| overpass | 13–1 | 0.14 | 70% | 1 Oct → | |
| dust2 | 13–0 | 0.15 | 69% | 1 Oct → | |
| office | 13–2 | 0.11 | 90% | 30 Sept → | |
| office | 13–1 | 0.11 | 44% | 30 Sept → | |
| inferno | 13–4 | 0.04 | 25% | 30 Sept → | |
| inferno | 10–0 | 0.05 | 56% | 30 Sept → | |
| mirage | 13–4 | -0.01 | 29% | 24 Sept → | |
| vertigo | 13–3 | 0.13 | 32% | 24 Sept → | |
| vertigo | 5–0 | 0.03 | 50% | 24 Sept → | |
| dust2 | 13–0 | 0.09 | 100% | 19 Sept → | |
| dust2 | 4–0 | 0.20 | 100% | 19 Sept → | |
| dust2 | 13–4 | 0.21 | 31% | 17 Sept → | |
| mirage | 13–5 | 0.22 | 88% | 17 Sept → | |
| mirage | 13–2 | 0.06 | 73% | 17 Sept → | |
| office | 13–3 | 0.18 | 55% | 17 Sept → | |
| inferno | 7–9 | -0.07 | 100% | 17 Sept → | |
| inferno | 8–8 | -0.08 | 78% | 17 Sept → | |
| inferno | 9–7 | 0.01 | 60% | 17 Sept → | |
| inferno | 9–0 | 0.22 | 71% | 10 Sept → | |
| inferno | 9–0 | 0.19 | 100% | 10 Sept → | |
| nuke | 3–0 | 0.20 | 100% | 10 Sept → | |
| nuke | 9–1 | 0.15 | 67% | 10 Sept → | |
| office | 13–10 | 0.21 | 37% | 8 Sept → | |
| office | 13–4 | 0.04 | 44% | 8 Sept → | |
| office | 13–0 | 0.15 | 15% | 3 Sept → | |
| office | 5–0 | 0.08 | 67% | 3 Sept → | |
| office | 13–9 | 0.02 | 18% | 3 Sept → | |
| office | 7–13 | 0.01 | 19% | 3 Sept → | |
| nuke | 9–1 | -0.00 | 46% | 29 Aug → | |
| cache | 13–2 | 0.21 | 39% | 27 Aug → | |
| cache | 13–3 | 0.08 | 46% | 27 Aug → | |
| train | 13–2 | 0.01 | 14% | 12 Aug → | |
| train | 13–6 | 0.09 | 20% | 12 Aug → | |
| mirage | 13–0 | 0.16 | 100% | 12 Aug → | |
| dust2 | 13–0 | 0.19 | 38% | 12 Aug → | |
| inferno | 13–8 | 0.20 | 89% | 12 Aug → | |
| dust2 | 0–1 | 0.00 | 0% | 11 Aug → | |
| nuke | 0–2 | 0.00 | 0% | 11 Aug → | |
| mirage | 13–3 | 0.10 | 93% | 11 Aug → | |
| mirage | 13–4 | 0.11 | 100% | 11 Aug → | |
| dust2 | 13–2 | 0.16 | 38% | 11 Aug → | |
| dust2 | 13–2 | 0.09 | 55% | 11 Aug → | |
| anubis | 13–1 | 0.09 | 50% | 11 Aug → | |
| ancient | 6–0 | 0.21 | 55% | 11 Aug → | |
| mirage | 2–0 | 0.04 | 100% | 11 Aug → | |
| dust2 | 13–1 | 0.20 | 60% | 11 Aug → | |
| dust2 | 7–3 | 0.27 | 22% | 11 Aug → | |
| mirage | 13–1 | 0.16 | 92% | 11 Aug → | |
| dust2 | 13–1 | 0.19 | 32% | 11 Aug → | |
| nuke | 13–3 | 0.26 | 26% | 11 Aug → | |
| dust2 | 0–4 | 0.08 | 31% | 10 Aug → | |
| mirage | 13–7 | 0.09 | 95% | 10 Aug → | |
| dust2 | 13–0 | 0.11 | 41% | 10 Aug → | |
| inferno | 13–0 | 0.01 | 57% | 10 Aug → | |
| inferno | 0–13 | 0.03 | 100% | 10 Aug → | |
| dust2 | 11–13 | 0.22 | 100% | 10 Aug → | |
| mirage | 13–2 | 0.11 | 92% | 10 Aug → | |
| mirage | 13–1 | 0.04 | 100% | 10 Aug → | |
| dust2 | 13–5 | 0.28 | 86% | 10 Aug → | |
| mirage | 13–1 | 0.05 | 36% | 10 Aug → | |
| dust2 | 2–13 | 0.01 | 32% | 10 Aug → | |
| dust2 | 13–11 | 0.02 | 100% | 10 Aug → | |
| mirage | 13–2 | 0.16 | 85% | 10 Aug → | |
| mirage | 6–0 | 0.10 | 50% | 10 Aug → | |
| mirage | 13–5 | 0.06 | 42% | 10 Aug → | |
| mirage | 13–0 | 0.07 | 100% | 9 Aug → | |
| anubis | 13–5 | 0.18 | 89% | 9 Aug → | |
| mirage | 13–4 | 0.18 | 74% | 9 Aug → | |
| ancient | 13–4 | 0.02 | 38% | 9 Aug → | |
| dust2 | 13–8 | 0.20 | 74% | 9 Aug → | |
| anubis | 13–7 | 0.04 | 17% | 9 Aug → | |
| mirage | 6–0 | 0.12 | 75% | 9 Aug → | |
| dust2 | 16–12 | -0.15 | 0% | 9 Aug → | |
| dust2 | 13–0 | 0.05 | 43% | 9 Aug → | |
| nuke | 13–0 | 0.02 | 7% | 9 Aug → |
Match data via Leetify.
Recent teammates
Milestones
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