西格玛·沃尔夫·巨兽 — CS2 Stats

76561198413397764[U:1:453132036]

2,905Tracked matches44%Win rate2020Tracked since

3,217Hours in CS29Hrs last 2 wks

CSDB Rating4.0 Developing

Premier CS Rating8,483Light Blue band · top ~62.1% of ranked players (population est.)

CSDB Leaderboard#11635 of 15574 tracked

FaceitLevel 6 · 749 ELOTop 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim55

Positioning41

Utility29

0–100 skill scores via Leetify.

Recent form

STEADY40–53–7Last 10040%Win rateWLLWLTLWWT

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

Aim5.5

Aggression3.7

Utility2.9

Positioning4.1

Opening Duels1.4

Clutch4.0

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 78% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

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

Reaction time. 713ms 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

Aim5.5

Positioning4.1

Utility2.9

Mechanics7.4

Opening Duels1.4

Win Impact3.1

Composite 4.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.04+0.00

first ⅓ avg -0.04 → last ⅓ avg -0.04

Reaction time712ms−73ms

first ⅓ avg 784ms → last ⅓ avg 712ms

Headshot accuracy27.8%+2.7%

first ⅓ avg 25.1% → last ⅓ avg 27.8%

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

0.11Best rating — inferno 13–0

13–0Biggest win — inferno

3Longest win streak

3–5In matches decided by ≤2 rounds

9Overtime games

Map breakdown

cacheBest map · 69% over 13dust2Weakest map · 11% over 9

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	21	9–12	43%	-0.03
nuke	D	14	3–11	21%	-0.04
anubis	B	13	7–6	54%	-0.04
cache	S	13	9–4	69%	-0.03
inferno	B	11	5–6	45%	-0.01
ancient	C	11	4–7	36%	-0.02
dust2	D	9	1–8	11%	-0.04
train	—	2	1–1	50%	-0.06
office	—	2	0–2	0%	-0.06
vertigo	—	1	0–1	0%	-0.05
fachwerk	—	1	0–1	0%	-0.09
boulder	—	1	1–0	100%	0.06
italy	—	1	0–1	0%	-0.11

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (11% over 9). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

49,396Lifetime kills

0.75K/D

3,330Matches

42.4%Match win rate

56.8%Headshot % · Top 25% of tracked players

4.0%Shot accuracy

6,365MVPs

1,377Hours (in match)

1,350Bombs planted

390Bombs defused

Most-used weapons

AK-4716,914

M4A4 / M4A1-S9,955

Desert Eagle3,999

AWP3,193

P2000 / USP-S2,770

Glock-182,483

Galil AR1,800

MP91,075

FAMAS1,008

MAC-10929

Lifetime map wins

4,746inferno

4,257nuke

2,723dust2

1,967vertigo

1,764train

1,421office

135italy

24cbble

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

Faceit stats

Combat

419Matches

49%Win rate

0.84Avg K/D

72.3ADR

52%Headshot %

Clutches & streaks

40%1v1 clutch win

15%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	61	44%	0.76	13.1
Anubis	32	56%	0.81	13.6
Inferno	30	53%	0.79	13.1
Dust2	29	34%	0.71	12.6
Nuke	28	54%	0.92	14.0
Ancient	25	60%	0.94	14.2
Train	12	67%	0.85	14.7
Overpass	12	33%	0.76	15.1

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.

27.9%Headshot accuracy

26.0%Accuracy (enemy spotted)

25.1%Spray accuracy

83.3%Counter-strafing

8.7°Preaim

713msReaction time

33.9%T opening success

37.6%CT opening success

0.38Enemies flashed / flash

5.7%Flash assists

7.47HE damage / grenade

5.66Flashes / 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 Settings
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 713.3328ms — above the 700ms mark we flag
Aim Training →
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 0.379 — 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 33.8564% — below the 40% mark we flag

Spend your practice time on Dust 2

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

11% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–7	-0.07	33%	27 Aug →
inferno	11–13	-0.06	34%	27 Aug →
nuke	3–13	-0.03	20%	27 Aug →
mirage	13–7	-0.05	27%	26 Aug →
mirage	10–13	-0.01	31%	25 Aug →
dust2	15–15	-0.02	23%	25 Aug →
mirage	5–13	-0.10	6%	24 Aug →
dust2	13–9	-0.04	43%	24 Aug →
mirage	13–4	-0.03	11%	24 Aug →
inferno	12–12	-0.08	56%	24 Aug →
nuke	9–13	-0.06	19%	23 Aug →
anubis	13–8	0.02	46%	23 Aug →
dust2	6–13	-0.01	30%	23 Aug →
mirage	13–8	0.03	21%	23 Aug →
mirage	7–13	-0.03	29%	21 Aug →
cache	13–5	-0.06	44%	21 Aug →
nuke	5–13	-0.08	28%	21 Aug →
anubis	13–7	-0.06	29%	20 Aug →
ancient	2–13	-0.06	33%	20 Aug →
nuke	3–13	-0.11	17%	20 Aug →
cache	10–13	-0.08	25%	20 Aug →
ancient	10–13	-0.01	27%	20 Aug →
mirage	13–11	0.06	27%	20 Aug →
anubis	13–7	-0.09	18%	20 Aug →
anubis	15–15	-0.06	23%	20 Aug →
inferno	13–10	-0.04	30%	20 Aug →
cache	8–13	-0.01	30%	19 Aug →
dust2	9–13	-0.04	23%	19 Aug →
nuke	13–3	0.07	29%	19 Aug →
nuke	9–13	-0.00	18%	17 Aug →
ancient	13–10	0.04	24%	17 Aug →
mirage	4–13	-0.07	39%	17 Aug →
cache	13–1	-0.03	24%	17 Aug →
ancient	13–4	0.03	15%	17 Aug →
dust2	14–16	-0.01	33%	16 Aug →
inferno	8–13	-0.03	40%	16 Aug →
cache	13–16	0.01	27%	16 Aug →
inferno	13–0	0.11	23%	16 Aug →
mirage	14–16	-0.01	27%	16 Aug →
mirage	10–13	0.00	33%	12 Aug →
anubis	13–5	-0.02	28%	12 Aug →
nuke	13–9	0.07	28%	12 Aug →
anubis	10–13	-0.08	32%	8 Aug →
cache	13–6	-0.01	25%	8 Aug →
anubis	13–7	0.01	24%	7 Aug →
mirage	9–13	-0.10	20%	7 Aug →
train	13–6	-0.08	25%	6 Aug →
vertigo	12–12	-0.05	36%	5 Aug →
mirage	16–14	0.03	30%	4 Aug →
anubis	13–9	-0.02	13%	4 Aug →
mirage	9–13	-0.05	30%	2 Aug →
ancient	13–10	-0.07	13%	2 Aug →
nuke	15–15	-0.10	19%	2 Aug →
inferno	14–16	-0.05	38%	31 Jul →
nuke	3–13	-0.08	50%	31 Jul →
cache	13–7	-0.04	29%	31 Jul →
anubis	8–13	0.03	28%	30 Jul →
dust2	6–13	-0.05	29%	30 Jul →
anubis	11–13	-0.11	16%	30 Jul →
mirage	5–13	0.03	25%	30 Jul →
dust2	4–13	-0.07	39%	30 Jul →
mirage	7–13	0.00	31%	28 Jul →
mirage	13–2	-0.02	29%	28 Jul →
office	12–12	-0.05	38%	27 Jul →
anubis	0–13	-0.08	35%	26 Jul →
inferno	13–10	0.03	32%	23 Jul →
ancient	8–13	-0.07	20%	22 Jul →
mirage	13–7	0.03	27%	21 Jul →
cache	7–1	-0.08	33%	21 Jul →
inferno	8–13	-0.05	28%	18 Jul →
ancient	10–13	0.01	33%	18 Jul →
cache	8–13	-0.08	16%	18 Jul →
nuke	10–13	-0.10	25%	18 Jul →
nuke	10–13	-0.01	30%	16 Jul →
inferno	13–2	0.10	50%	16 Jul →
anubis	5–13	-0.06	24%	14 Jul →
ancient	8–13	-0.00	26%	14 Jul →
inferno	13–5	-0.02	13%	14 Jul →
nuke	10–13	-0.05	38%	14 Jul →
ancient	5–13	-0.05	22%	13 Jul →
cache	13–4	-0.01	26%	13 Jul →
mirage	1–13	-0.13	19%	13 Jul →
mirage	13–10	-0.07	22%	13 Jul →
anubis	13–7	-0.05	24%	13 Jul →
ancient	13–9	-0.02	25%	12 Jul →
dust2	7–13	-0.05	23%	12 Jul →
inferno	8–13	-0.01	33%	12 Jul →
cache	13–9	0.00	24%	12 Jul →
ancient	15–15	0.00	24%	10 Jul →
cache	13–1	-0.02	6%	10 Jul →
fachwerk	7–13	-0.09	17%	10 Jul →
boulder	13–2	0.06	15%	10 Jul →
cache	13–11	-0.03	30%	22 Jun →
train	10–13	-0.05	24%	22 Jun →
office	9–13	-0.07	39%	20 Jun →
italy	7–13	-0.11	0%	18 Jun →
mirage	13–4	-0.06	18%	14 Jun →
dust2	8–13	-0.03	26%	8 Jun →
mirage	9–13	-0.05	25%	4 Jun →
nuke	4–13	-0.07	43%	4 Jun →