Raw karambwan — CS2 Stats
SZ76561198036202121[U:1:75936393]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 8 Sep 2026 (9 days ago). Ranks are recorded once per day this page is viewed.
No change since then — still 256 tracked matches. Play, then come back: the next observation lands here.
CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 35 days played since 4 Jul 2022. Come back after the next session and the change shows above.
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Rating over time
Faceit ELO
- At peak — 1,968
- Next: Level 10 at 2,001 — 33 to go
- Reached: Level 9 · Level 8 · Level 7 · Level 6
- Level 9 first seen 2026-09-08
- Level 8 first seen 2026-09-08
CSDB’s own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
Compare periods
Last 7 days vs previous 7
No matches recorded between 9 Sep 2026 and 17 Sep 2026.
Measured 9 Sep 2026 → 17 Sep 2026; no observation near 14 days ago, so there is no previous window yet.
Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: −30pp win rate · −0.03 avg rating · +4.9pp headshot accuracy · +51ms reaction
Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).
Last 5 · 10 · 20 matches
Last 5
- 2–3 · 40% win rate
- Avg rating 0.01
- Avg headshot accuracy 22%
- Avg reaction 564ms
Last 10
- 3–6–1 · 30% win rate
- Avg rating 0.00
- Avg headshot accuracy 25%
- Avg reaction 562ms
Last 20
- 9–10–1 · 45% win rate
- Avg rating 0.02
- Avg headshot accuracy 23%
- Avg reaction 536ms
Newest first, from the last 44 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.
Player DNA
Primary style: Positional Player — Positioning stands above the rest of this profile (+2 against its own average).
Strong T-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 s1mple 88% playstyle similarity
Most alike: positioning profile, aim profile.
Where you differ: lower utility contribution; lower opening-duel success.
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
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 5.6/10 (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 44 tracked matches, oldest to newest. The delta compares the first third of the window with the last.
Personal bests
Across the last 44 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 mirage | S | 10 | 7–3 | 70% | 0.05 |
 inferno | S | 10 | 7–3 | 70% | 0.00 |
 vertigo | C | 7 | 3–4 | 43% | -0.02 |
 ancient | D | 5 | 1–4 | 20% | 0.01 |
 dust2 | — | 3 | 1–2 | 33% | 0.00 |
 nuke | — | 3 | 2–1 | 67% | 0.06 |
 overpass | — | 2 | 1–1 | 50% | -0.01 |
 anubis | — | 2 | 1–1 | 50% | -0.02 |
 train | — | 2 | 1–1 | 50% | -0.03 |
Across the last 44 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Ancient 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 resultsLWWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 68 | 50% | 1.13 | 16.7 |
| Inferno | 59 | 47% | 1.07 | 14.9 |
| Nuke | 40 | 62% | 1.33 | 17.5 |
| Anubis | 19 | 53% | 1.35 | 16.5 |
| Mirage | 18 | 56% | 1.19 | 17.4 |
| Vertigo | 18 | 67% | 1.24 | 17.3 |
| Train | 16 | 69% | 1.36 | 17.6 |
| Overpass | 7 | 57% | 1.02 | 15.6 |
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 0.4818 — below the 0.5 mark we flag
- Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 38.4251% — 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.
20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| ancient | 14–16 | -0.06 | 24% | 20 May → | |
| dust2 | 5–13 | 0.07 | 27% | 14 May → | |
| mirage | 13–5 | 0.06 | 20% | 12 May → | |
| mirage | 6–0 | 0.09 | 15% | 12 May → | |
| inferno | 5–13 | -0.11 | 22% | 15 Apr → | |
| overpass | 9–13 | 0.02 | 27% | 28 Mar → | |
| ancient | 5–13 | 0.07 | 32% | 24 Mar → | |
| anubis | 19–17 | 0.04 | 23% | 1 Mar → | |
| vertigo | 8–8 | -0.07 | 30% | 28 Feb → | |
| anubis | 6–13 | -0.09 | 33% | 22 Jan → | |
| inferno | 13–8 | -0.00 | 31% | 7 Dec → | |
| train | 13–1 | -0.01 | 18% | 2 Dec → | |
| mirage | 2–13 | -0.02 | 14% | 14 Nov → | |
| ancient | 11–13 | -0.02 | 23% | 11 Nov → | |
| ancient | 8–13 | -0.01 | 22% | 7 Nov → | |
| nuke | 13–7 | 0.17 | 18% | 7 Nov → | |
| inferno | 19–15 | 0.07 | 19% | 5 Nov → | |
| nuke | 1–13 | -0.04 | 24% | 21 Oct → | |
| ancient | 13–9 | 0.08 | 17% | 19 Oct → | |
| inferno | 13–1 | 0.11 | 21% | 15 Oct → | |
| train | 10–13 | -0.04 | 33% | 15 Oct → | |
| inferno | 13–9 | -0.04 | 21% | 11 Oct → | |
| inferno | 19–16 | -0.01 | 25% | 9 Oct → | |
| nuke | 9–6 | 0.05 | 24% | 8 Oct → | |
| inferno | 9–2 | 0.24 | 19% | 8 Oct → | |
| inferno | 1–9 | -0.17 | 33% | 24 Sept → | |
| inferno | 16–14 | 0.01 | 22% | 18 Sept → | |
| overpass | 13–10 | -0.05 | 10% | 1 Feb → | |
| vertigo | 13–5 | -0.01 | 22% | 1 Feb → | |
| mirage | 13–11 | -0.00 | 21% | 27 Jan → | |
| vertigo | 8–13 | -0.02 | 23% | 19 Jan → | |
| mirage | 11–13 | -0.04 | 14% | 19 Jan → | |
| vertigo | 9–13 | -0.02 | 20% | 14 Jan → | |
| vertigo | 13–11 | 0.03 | 25% | 13 Jan → | |
| vertigo | 3–13 | -0.09 | 5% | 13 Jan → | |
| vertigo | 16–13 | -0.01 | 36% | 12 Jan → | |
| mirage | 9–13 | 0.02 | 28% | 12 Jan → | |
| inferno | 4–13 | -0.10 | 22% | 6 Jan → | |
| mirage | 13–7 | 0.05 | 28% | 4 Jan → | |
| mirage | 13–6 | 0.12 | 25% | 4 Jan → | |
| mirage | 16–7 | 0.05 | 12% | 10 Sept → | |
| mirage | 16–12 | 0.20 | 31% | 10 Feb → | |
| dust2 | 16–8 | -0.07 | 13% | 9 Feb → | |
| dust2 | 14–16 | 0.02 | 23% | 4 Jul → |
Match data via Leetify.
