💫 Alex_lancien 💫 — CS2 Stats

FR76561198285476841[U:1:325211113]Steam profile ↗✓ No bans

2,045Tracked matches52%Win rate2020Tracked since

5,477Hours in CS5Hrs last 2 wks

CSDB Rating6.4 SolidPositional Player

CSDB Leaderboard#93238 of 261691 tracked

FaceitLevel 9Top 20.7% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

Rating over time

Premier CS Rating: 19,555 -2,056 4 May – 30 Jun · 2 days played

21,972Peak Premier in tracked matches

47Days played since 2026-04-27

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

How this compares with the same rank

Median values for Level 9 among CSDB-tracked players (n=15,553), 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 9 median	Level 10 median	vs Level 10
Headshot rate	59.0%	48.2%	50.9%	above
Shot accuracy	16.8%	13.2%	13.7%	above
Kill/death ratio	1.28	1.07	1.09	above
Match win rate	48.2%	46.9%	48.4%	meets

Across every metric we can compare, this profile already matches the typical Level 10 player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

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Performance scores

Aim75

Positioning62

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY46–48–6Last 10046%Win rateWTWLLWLWLW

Last 10 vs previous 10: 0pp win rate · −0.03 avg rating · −0.3pp headshot accuracy · +88ms 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

2–2–1 · 40% win rate
Avg rating -0.02
Avg headshot accuracy 20%
Avg reaction 669ms

Last 10

5–4–1 · 50% win rate
Avg rating -0.01
Avg headshot accuracy 23%
Avg reaction 616ms

Last 20

10–9–1 · 50% win rate
Avg rating 0.01
Avg headshot accuracy 23%
Avg reaction 572ms

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 (+1.4 against its own average).

Aim7.5

Utility5.6

Positioning6.2

Opening Duels3.7

Clutch3.8

Strong CT-side opener

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 91% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: 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

CT openings. 68% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 68% on CT to 34% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 568ms 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

Aim7.5

Positioning6.2

Utility5.6

Mechanics6.9

Opening Duels5.2

Win Impact5.6

Composite 6.4/10 (Solid), 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

Match rating0.01−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time562ms−63ms

first ⅓ avg 625ms → last ⅓ avg 562ms

Headshot accuracy22.3%+0.7%

first ⅓ avg 21.6% → last ⅓ avg 22.3%

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

0.14Best match rating · 13–1 · inferno, 24 Oct →

46%Best headshot accuracy · 13–1 · dust2, 1 Aug →

391msFastest reaction time · 13–2 · dust2, 23 Oct →

13–1Biggest win · inferno, 13 Nov →

Across the last 100 tracked matches.

Highlights

6Longest win streak

5–7In matches decided by ≤2 rounds

1Overtime games

Map breakdown

cacheBest map · 50% over 16anubisWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	48	22–26	46%	0.01
inferno	B	29	14–15	48%	0.02
cache	B	16	8–8	50%	0.01
anubis	D	6	2–4	33%	0.01
ancient	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

221,042Lifetime kills

1.28K/D · Top 25% of Level 9 players

7,031Matches

48.2%Match win rate · Top 50% of Level 9 players

59.0%Headshot % · Top 25% of Level 9 players

16.8%Shot accuracy · Top 25% of Level 9 players

16,993MVPs

5,506Hours (in match)

9,542Bombs planted

1,801Bombs defused

Most-used weapons

AK-47105,715

M4A4 / M4A1-S45,557

P2000 / USP-S12,073

Glock-187,084

AWP6,415

Desert Eagle4,863

FAMAS3,725

Galil AR3,357

SG 5533,202

P903,191

Lifetime map wins

37,763dust2

19,753inferno

2,200vertigo

1,050nuke

761cbble

375train

297safehouse

186lake

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

Faceit stats

Combat

470Matches

52%Win rate

1.09Avg K/D

86.2ADR

43%Headshot %

Clutches & streaks

39%1v1 clutch win

33%1v2 clutch win

10Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	32	62%	1.51	17.9
Inferno	29	72%	1.26	17.5
Anubis	22	50%	1.17	16.4
Mirage	21	43%	1.08	16.3
Ancient	15	33%	1.12	16.1
Nuke	9	56%	1.17	16.9
Vertigo	6	33%	0.88	18.0
Cache	5	40%	1.35	20.0

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.

22.5%Headshot accuracy

33.9%Accuracy (enemy spotted)

33.3%Spray accuracy

81.0%Counter-strafing

9.2°Preaim

568msReaction time

34.3%T opening success

67.5%CT opening success

0.41Enemies flashed / flash

4.7%Flash assists

12.76HE damage / grenade

11.81Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4065 — below the 0.5 mark we flag
Grenade Lineups →
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 34.2561% — below the 40% mark we flag

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.

33% win rate across 6 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
inferno	13–1	0.02	11%	13 Nov →
dust2	12–12	0.01	14%	13 Nov →
dust2	13–6	-0.03	20%	10 Nov →
inferno	2–13	-0.05	33%	10 Nov →
dust2	9–13	-0.04	21%	10 Nov →
dust2	13–8	0.00	31%	4 Nov →
dust2	2–13	-0.04	26%	4 Nov →
inferno	13–8	0.03	23%	31 Oct →
dust2	7–13	-0.05	20%	31 Oct →
inferno	13–11	0.06	30%	30 Oct →
dust2	8–13	-0.01	28%	30 Oct →
dust2	6–13	0.05	17%	25 Oct →
inferno	6–13	-0.02	22%	25 Oct →
inferno	13–3	0.06	24%	24 Oct →
dust2	13–4	0.11	16%	24 Oct →
inferno	13–1	0.14	34%	24 Oct →
dust2	3–13	-0.03	26%	24 Oct →
anubis	11–13	-0.02	22%	23 Oct →
dust2	13–11	-0.02	21%	23 Oct →
inferno	13–4	-0.04	21%	23 Oct →
dust2	13–2	0.06	22%	23 Oct →
dust2	8–13	-0.01	19%	19 Oct →
inferno	9–13	0.03	22%	19 Oct →
cache	5–13	-0.03	15%	15 Oct →
inferno	13–6	0.07	17%	13 Oct →
dust2	6–13	0.01	33%	10 Oct →
inferno	13–4	0.04	35%	10 Oct →
dust2	9–13	-0.04	15%	10 Oct →
cache	13–6	0.04	26%	9 Oct →
inferno	13–11	0.07	19%	8 Oct →
dust2	5–13	-0.02	15%	7 Oct →
ancient	11–13	0.01	10%	29 Sept →
dust2	13–10	-0.00	28%	29 Sept →
anubis	13–9	-0.02	16%	19 Sept →
dust2	12–12	-0.00	17%	18 Sept →
dust2	13–8	0.04	19%	18 Sept →
inferno	6–13	0.02	21%	4 Sept →
dust2	11–13	0.04	15%	4 Sept →
inferno	13–5	0.07	23%	2 Sept →
dust2	13–11	0.05	28%	2 Sept →
dust2	13–6	0.13	30%	2 Sept →
dust2	13–8	0.01	18%	1 Sept →
dust2	3–13	-0.06	15%	1 Sept →
dust2	13–9	-0.02	19%	1 Sept →
anubis	13–9	0.07	18%	24 Aug →
cache	13–8	-0.02	20%	6 Aug →
dust2	10–13	-0.04	33%	6 Aug →
dust2	0–5	-0.11	33%	4 Aug →
cache	13–9	-0.05	28%	4 Aug →
dust2	12–12	0.01	17%	4 Aug →
cache	11–13	-0.01	24%	1 Aug →
dust2	13–1	0.12	46%	1 Aug →
dust2	13–5	-0.02	23%	28 Jul →
cache	2–13	-0.03	11%	28 Jul →
inferno	3–13	0.01	21%	22 Jul →
dust2	13–2	0.09	16%	22 Jul →
inferno	11–13	0.00	25%	21 Jul →
dust2	13–7	0.12	25%	21 Jul →
inferno	8–13	-0.00	9%	21 Jul →
dust2	13–8	0.00	23%	19 Jul →
dust2	10–13	-0.02	30%	19 Jul →
inferno	5–13	-0.06	9%	17 Jul →
inferno	5–13	0.01	20%	17 Jul →
dust2	12–12	-0.04	21%	17 Jul →
cache	10–13	0.09	26%	15 Jul →
dust2	5–13	0.05	16%	15 Jul →
inferno	13–3	0.06	27%	15 Jul →
dust2	13–10	0.11	14%	15 Jul →
inferno	8–13	-0.04	27%	14 Jul →
dust2	13–11	0.02	19%	14 Jul →
inferno	4–13	0.00	18%	9 Jul →
cache	6–13	-0.04	24%	7 Jul →
dust2	5–13	-0.06	28%	7 Jul →
inferno	4–13	-0.05	10%	2 Jul →
dust2	10–13	0.09	36%	30 Jun →
inferno	13–10	-0.00	15%	30 Jun →
inferno	11–13	0.01	16%	22 Jun →
cache	13–5	0.01	17%	22 Jun →
dust2	9–13	0.00	23%	19 Jun →
cache	13–7	0.03	34%	19 Jun →
inferno	13–10	-0.03	22%	17 May →
dust2	13–9	-0.02	22%	17 May →
cache	13–2	0.07	15%	17 May →
dust2	13–9	0.02	19%	15 May →
inferno	13–6	0.02	16%	15 May →
cache	7–13	0.01	21%	15 May →
dust2	5–13	0.02	24%	15 May →
anubis	7–13	0.02	29%	12 May →
dust2	9–13	0.03	24%	12 May →
dust2	13–9	-0.00	22%	5 May →
cache	10–13	-0.03	14%	4 May →
anubis	9–13	-0.01	11%	4 May →
dust2	13–4	0.03	16%	4 May →
inferno	11–13	0.06	24%	4 May →
cache	13–6	0.06	24%	4 May →
cache	13–7	0.07	25%	3 May →
cache	8–13	-0.07	20%	29 Apr →
inferno	12–12	-0.00	29%	28 Apr →
dust2	12–12	0.05	37%	28 Apr →
anubis	15–19	0.02	17%	27 Apr →