sWAN_ — CS2 Stats

JP76561198024687209[U:1:64421481]Steam profile ↗✓ No bans

3,213Tracked matches50%Win rate2020Tracked since

4,860Hours in CS14Hrs last 2 wks

CSDB Rating8.0 StrongPositional Player

Premier CS Rating25,713Top 10% of 212,695 CSDB-tracked playersRed band · top ~2.7% of ranked players (population est.)

CSDB Leaderboard#15463 of 259593 tracked

FaceitLevel 10 · 2,085 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 25,713 +1,702 1 Sept – 30 Oct · 10 days played

Faceit ELO: 2,085 +0 1 Sept – 23 Sept · 3 observations

25,713Peak Premier in tracked matches

2,085Highest Faceit ELO seen on CSDB

23Days played since 2026-08-12

Faceit ELO

At peak — 2,085
Next: 2,500 ELO at 2,500 — 415 to go
Reached: Level 10 · Level 9 · Level 8 · Level 7
Level 10 first seen 2026-09-01
Level 9 first seen 2026-09-01

Premier CS Rating

At peak — 25,713
+1,530 over 30 days · improving
Next: Gold band at 30,000 — 4,287 to go
Reached: Red band · Pink band · Purple band · Blue band
Pink band first seen 2026-09-01
Purple 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. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=30,986), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 10 median
Headshot rate	50.6%	50.9%
Shot accuracy	17.8%	13.7%
Kill/death ratio	1.41	1.09
Match win rate	64.0%	48.4%

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Performance scores

Aim84

Positioning80

Utility74

0–100 skill scores via Leetify.

Recent form

STEADY55–45Last 10055%Win rateLLWWWWLLLW

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · +3.8pp headshot accuracy · +51ms 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

3–2 · 60% win rate
Avg rating 0.07
Avg headshot accuracy 29%
Avg reaction 640ms

Last 10

5–5 · 50% win rate
Avg rating 0.04
Avg headshot accuracy 19%
Avg reaction 574ms

Last 20

10–10 · 50% win rate
Avg rating 0.03
Avg headshot accuracy 17%
Avg reaction 548ms

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: Positional Player — Positioning stands above the rest of this profile (+1.7 against its own average).

Aim8.4

Utility7.4

Positioning8.0

Opening Duels6.6

Clutch3.4

Strong positioning

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 Twistzz 84% playstyle similarity

Most alike: utility contribution, positioning 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

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

T openings. 65% T opening-duel success — entries that actually open the round.

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

Aim8.4

Positioning8.0

Utility7.4

Mechanics7.3

Opening Duels8.2

Win Impact5.0

Composite 8.0/10 (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

Match rating0.02+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.02

Reaction time541ms+1ms

first ⅓ avg 539ms → last ⅓ avg 541ms

Headshot accuracy16.2%−5.4%

first ⅓ avg 21.6% → last ⅓ avg 16.2%

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

0.12Best match rating · 13–10 · mirage, 18 Sept →

67%Best headshot accuracy · 6–2 · rush_001, 30 Oct →

383msFastest reaction time · 13–8 · cache, 21 Sept →

13–1Biggest win · ancient, 18 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak

L2Current streak

7–17In matches decided by ≤2 rounds

11Overtime games

Map breakdown

ancientBest map · 62% over 21anubisWeakest map · 43% over 23

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	25	15–10	60%	0.00
anubis	C	23	10–13	43%	-0.00
ancient	A	21	13–8	62%	0.02
cache	B	16	8–8	50%	0.01
mirage	A	9	5–4	56%	0.03
rush_001	A	5	3–2	60%	0.07
dust2	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (43% over 23). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

182,356Lifetime kills

1.41K/D · Top 10% of Level 10 players

10,346Matches

64.0%Match win rate · Top 5% of Level 10 players

50.6%Headshot %

17.8%Shot accuracy · Top 25% of Level 10 players

18,926MVPs

2,741Hours (in match)

5,907Bombs planted

1,551Bombs defused

Most-used weapons

AK-4769,615

M4A4 / M4A1-S38,922

Desert Eagle8,667

P2000 / USP-S8,658

AWP8,164

P2507,258

Glock-186,118

FAMAS2,915

Knife2,632

Galil AR2,531

Lifetime map wins

13,381inferno

4,282dust2

3,162nuke

1,796vertigo

1,190train

925cbble

410office

182dust

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

1,771Matches

52%Win rate

1.17Avg K/D

90.1ADR

45%Headshot %

Clutches & streaks

37%1v1 clutch win

24%1v2 clutch win

7Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	147	56%	1.20	18.1
Anubis	146	51%	1.14	18.1
Ancient	99	47%	1.09	16.9
Mirage	86	44%	1.22	18.2
Overpass	50	60%	1.15	17.0
Nuke	24	46%	1.13	17.5
Vertigo	20	45%	1.16	18.3
Cache	18	50%	1.14	17.1

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.

14.4%Headshot accuracy

40.7%Accuracy (enemy spotted)

42.5%Spray accuracy

82.7%Counter-strafing

9.5°Preaim

527msReaction time

65.3%T opening success

60.6%CT opening success

0.66Enemies flashed / flash

9.6%Flash assists

9.83HE damage / grenade

15.08Flashes / match

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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.3735% — below the 15% mark we flag
Aim Training →

Spend your practice time on Anubis

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

43% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
rush_001	4–8	0.09	38%	30 Oct →
rush_001	7–8	0.03	12%	30 Oct →
rush_001	6–2	0.06	14%	30 Oct →
rush_001	6–2	0.11	13%	30 Oct →
rush_001	6–2	0.06	67%	30 Oct →
inferno	13–5	0.10	18%	30 Oct →
inferno	5–13	-0.04	3%	30 Oct →
ancient	9–13	-0.02	6%	30 Oct →
anubis	11–13	-0.00	13%	30 Oct →
ancient	16–13	0.01	7%	28 Oct →
anubis	14–16	-0.06	11%	28 Oct →
ancient	13–7	0.03	10%	28 Oct →
cache	13–11	0.06	11%	28 Oct →
mirage	13–6	0.06	9%	23 Oct →
inferno	5–13	0.01	23%	23 Oct →
cache	13–9	-0.01	22%	23 Oct →
mirage	3–13	0.03	20%	21 Oct →
cache	3–13	0.01	13%	21 Oct →
inferno	5–13	0.07	20%	21 Oct →
ancient	13–10	0.08	14%	21 Oct →
ancient	13–10	-0.01	12%	21 Oct →
inferno	13–10	0.03	14%	21 Oct →
ancient	11–13	-0.01	16%	21 Oct →
anubis	4–13	-0.05	4%	19 Oct →
anubis	13–9	0.01	10%	19 Oct →
inferno	18–22	-0.00	19%	19 Oct →
anubis	13–10	-0.00	13%	19 Oct →
ancient	11–13	0.04	31%	19 Oct →
inferno	13–6	-0.00	21%	14 Oct →
inferno	13–9	-0.08	7%	14 Oct →
anubis	10–13	-0.03	15%	14 Oct →
mirage	5–13	-0.04	13%	14 Oct →
ancient	13–8	0.01	16%	14 Oct →
cache	11–13	-0.01	17%	14 Oct →
mirage	13–8	0.08	20%	12 Oct →
ancient	13–2	0.05	23%	12 Oct →
inferno	13–10	0.02	25%	12 Oct →
anubis	13–8	0.05	10%	12 Oct →
cache	8–13	-0.01	9%	12 Oct →
anubis	20–22	-0.01	17%	6 Oct →
cache	13–11	0.00	22%	6 Oct →
inferno	13–9	0.01	33%	6 Oct →
ancient	13–2	0.08	27%	5 Oct →
ancient	2–13	-0.00	15%	5 Oct →
cache	8–13	0.00	24%	5 Oct →
anubis	13–8	0.00	22%	5 Oct →
anubis	13–4	0.00	18%	5 Oct →
ancient	23–25	-0.02	14%	30 Sept →
anubis	11–13	0.01	13%	30 Sept →
inferno	3–13	-0.03	15%	28 Sept →
inferno	2–13	-0.07	8%	28 Sept →
ancient	13–10	-0.01	14%	28 Sept →
anubis	13–6	-0.03	14%	28 Sept →
mirage	13–10	0.00	10%	28 Sept →
anubis	11–13	0.02	18%	28 Sept →
ancient	9–13	-0.04	13%	28 Sept →
inferno	13–11	-0.00	13%	22 Sept →
mirage	11–13	-0.01	28%	22 Sept →
cache	13–3	0.05	16%	22 Sept →
anubis	10–13	-0.01	20%	21 Sept →
cache	13–8	0.02	15%	21 Sept →
inferno	13–6	-0.01	19%	21 Sept →
mirage	14–16	-0.02	16%	18 Sept →
cache	13–10	0.09	21%	18 Sept →
mirage	13–10	0.12	23%	18 Sept →
inferno	13–9	0.07	10%	18 Sept →
ancient	13–1	0.05	17%	18 Sept →
inferno	14–16	0.01	18%	16 Sept →
ancient	13–6	-0.02	13%	16 Sept →
anubis	8–13	-0.02	12%	16 Sept →
anubis	13–4	0.01	13%	16 Sept →
cache	13–9	-0.00	15%	14 Sept →
inferno	4–13	-0.03	24%	14 Sept →
anubis	13–11	-0.00	22%	14 Sept →
ancient	1–7	-0.07	43%	14 Sept →
inferno	19–16	-0.01	15%	14 Sept →
mirage	13–9	0.03	35%	13 Sept →
cache	13–9	0.02	16%	13 Sept →
cache	9–13	-0.06	18%	13 Sept →
inferno	13–10	-0.02	33%	13 Sept →
inferno	3–13	-0.08	31%	9 Sept →
inferno	13–9	0.04	23%	9 Sept →
anubis	17–19	-0.02	12%	7 Sept →
dust2	16–14	-0.01	24%	7 Sept →
anubis	13–11	0.06	16%	7 Sept →
ancient	13–5	0.08	15%	26 Aug →
ancient	13–7	0.07	14%	26 Aug →
inferno	13–11	0.03	18%	26 Aug →
cache	9–13	-0.01	26%	26 Aug →
anubis	6–13	0.00	27%	26 Aug →
cache	3–13	-0.07	11%	19 Aug →
ancient	8–13	-0.03	28%	19 Aug →
inferno	16–13	0.01	14%	19 Aug →
ancient	13–3	0.11	39%	19 Aug →
inferno	13–3	0.06	22%	17 Aug →
cache	11–13	0.04	26%	17 Aug →
anubis	11–13	-0.02	19%	17 Aug →
anubis	13–10	-0.02	15%	17 Aug →
inferno	9–13	-0.06	26%	12 Aug →
anubis	11–13	0.03	29%	12 Aug →