snaxx — CS2 Stats

76561198023456348[U:1:63190620]Steam profile ↗

564Tracked matches31%Win rate2020Tracked since

CSDB Rating2.6 LearningClutch Specialist

WingmanGold Nova II

Ladder ranks via Leetify

Performance scores

Aim25

Positioning29

Utility39

0–100 skill scores via Leetify.

Recent form

COLD36–57–7Last 10036%Win rateLLLLLWLLWL

Last 10 vs previous 10: -30pp win rate · +0.01 avg rating

Player DNA

Primary style: Clutch Specialist — Late-round 1vX conversion well above par.

Aim2.5

Aggression1.8

Utility3.9

Positioning2.9

Opening Duels0.0

Clutch10.0

Strong CT-side openerLimited utility dependenceReliable in 1v1s

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 65% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; 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

T-side openings. Opening success drops from 37% on CT to 13% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 683ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim2.5

Positioning2.9

Utility3.9

Mechanics4.1

Opening Duels0.8

Win Impact0.0

Composite 2.6/10 (Learning), 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 rating-0.05−0.00

first ⅓ avg -0.04 → last ⅓ avg -0.05

Reaction time675ms−8ms

first ⅓ avg 683ms → last ⅓ avg 675ms

Headshot accuracy15.6%−2.9%

first ⅓ avg 18.5% → last ⅓ avg 15.6%

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

0.06Best rating — inferno 13–3

13–2Biggest win — mirage

4Longest win streak

L5Current streak

6–8In matches decided by ≤2 rounds

5Overtime games

Map breakdown

infernoBest map · 50% over 8mirageWeakest map · 25% over 16

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	22	8–14	36%	-0.06
cache	D	17	5–12	29%	-0.04
mirage	D	16	4–12	25%	-0.05
ancient	B	11	5–6	45%	-0.05
inferno	B	8	4–4	50%	-0.04
nuke	C	8	3–5	38%	-0.06
anubis	D	6	2–4	33%	-0.04
office	—	4	3–1	75%	-0.09
vertigo	—	3	0–3	0%	-0.04
overpass	—	2	1–1	50%	-0.04
fachwerk	—	1	0–1	0%	-0.01
stronghold	—	1	0–1	0%	-0.08
train	—	1	1–0	100%	-0.09

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (25% over 16). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

114Matches

45%Win rate

0.73Avg K/D

45.6ADR

45%Headshot %

Clutches & streaks

71%1v1 clutch win

0%1v2 clutch win

4Longest win streak

Recent Faceit resultsLWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	4	50%	1.34	9.5
Ancient	3	67%	0.75	11.7
Dust2	3	33%	0.32	5.0
Mirage	2	0%	0.42	8.5
Cache	1	0%	0.67	8.0
Inferno	1	100%	0.80	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.

15.8%Headshot accuracy

25.6%Accuracy (enemy spotted)

31.0%Spray accuracy

68.6%Counter-strafing

11.6°Preaim

683msReaction time

12.8%T opening success

36.8%CT opening success

0.63Enemies flashed / flash

3.9%Flash assists

6.17HE damage / grenade

4.72Flashes / 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.

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 12.7885% — below the 40% mark we flag

Spend your practice time on Mirage

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

25% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	11–13	-0.03	21%	26 Jul →
dust2	5–13	-0.02	21%	26 Jul →
mirage	7–13	-0.09	11%	13 Jul →
dust2	10–13	-0.08	17%	12 Jul →
fachwerk	7–13	-0.01	25%	9 Jul →
office	13–5	-0.09	20%	9 Jul →
dust2	12–16	-0.05	15%	9 Jul →
dust2	10–13	-0.00	19%	9 Jul →
mirage	13–2	-0.01	22%	9 Jul →
dust2	7–13	-0.06	29%	9 Jul →
mirage	13–6	-0.06	7%	9 Jul →
dust2	11–13	-0.08	11%	9 Jul →
cache	11–13	-0.09	13%	8 Jul →
stronghold	11–13	-0.08	23%	8 Jul →
office	13–5	-0.07	25%	8 Jul →
ancient	13–10	-0.03	6%	8 Jul →
mirage	9–13	-0.07	21%	7 Jul →
mirage	13–5	-0.01	5%	6 Jul →
inferno	13–9	-0.06	10%	6 Jul →
ancient	2–13	-0.00	7%	6 Jul →
ancient	5–13	-0.05	8%	6 Jul →
mirage	13–16	-0.07	8%	6 Jul →
mirage	5–13	-0.04	21%	6 Jul →
ancient	13–8	0.02	14%	5 Jul →
overpass	16–14	-0.03	6%	5 Jul →
anubis	10–13	-0.05	15%	5 Jul →
cache	9–13	-0.05	25%	5 Jul →
dust2	8–13	-0.04	18%	3 Jul →
mirage	3–13	-0.08	9%	2 Jul →
dust2	12–12	-0.03	26%	1 Jul →
ancient	13–3	-0.08	10%	1 Jul →
anubis	13–8	0.01	11%	30 Jun →
dust2	5–13	-0.08	17%	30 Jun →
dust2	13–8	-0.10	22%	30 Jun →
ancient	16–12	-0.04	7%	30 Jun →
vertigo	7–13	-0.08	7%	30 Jun →
nuke	11–13	-0.06	20%	30 Jun →
overpass	8–13	-0.05	27%	30 Jun →
inferno	13–3	0.06	8%	30 Jun →
dust2	13–5	-0.01	24%	29 Jun →
cache	7–13	-0.10	17%	28 Jun →
inferno	10–13	-0.08	25%	28 Jun →
anubis	4–13	-0.01	21%	28 Jun →
mirage	5–13	-0.05	7%	28 Jun →
ancient	13–11	-0.05	10%	28 Jun →
dust2	13–4	-0.01	17%	28 Jun →
mirage	10–13	-0.01	13%	26 Jun →
ancient	8–13	-0.09	20%	26 Jun →
vertigo	12–12	-0.06	4%	26 Jun →
mirage	6–13	-0.03	21%	25 Jun →
dust2	10–13	-0.06	14%	25 Jun →
cache	13–3	0.03	14%	22 Jun →
dust2	6–13	-0.07	17%	20 Jun →
cache	5–13	-0.06	19%	20 Jun →
cache	12–12	-0.06	22%	19 Jun →
train	13–11	-0.09	9%	17 Jun →
nuke	11–13	-0.05	12%	17 Jun →
mirage	9–13	-0.01	17%	16 Jun →
nuke	3–13	-0.08	11%	16 Jun →
inferno	13–11	-0.07	18%	16 Jun →
mirage	13–3	0.02	15%	16 Jun →
nuke	13–8	-0.09	8%	16 Jun →
dust2	13–9	-0.12	8%	16 Jun →
dust2	9–13	-0.12	8%	15 Jun →
inferno	4–13	-0.09	0%	13 Jun →
dust2	13–11	-0.10	19%	12 Jun →
nuke	13–10	-0.02	10%	12 Jun →
inferno	13–5	0.01	27%	12 Jun →
ancient	6–13	-0.05	13%	12 Jun →
dust2	13–6	0.00	13%	12 Jun →
mirage	2–13	-0.10	11%	11 Jun →
dust2	16–14	-0.01	17%	11 Jun →
dust2	13–8	-0.05	17%	10 Jun →
office	13–7	-0.14	25%	10 Jun →
cache	13–2	-0.06	8%	10 Jun →
nuke	6–13	-0.03	31%	10 Jun →
nuke	4–13	-0.13	24%	10 Jun →
cache	13–9	0.04	17%	9 Jun →
cache	11–13	-0.03	21%	9 Jun →
cache	8–13	-0.06	17%	9 Jun →
anubis	6–13	-0.08	10%	1 Jun →
mirage	11–13	-0.05	23%	1 Jun →
cache	5–13	-0.08	11%	8 May →
cache	6–13	0.03	27%	8 May →
cache	9–13	-0.03	18%	7 May →
cache	12–12	-0.04	22%	4 May →
cache	8–13	-0.03	19%	4 May →
cache	13–4	0.01	17%	4 May →
cache	13–7	-0.02	15%	30 Apr →
anubis	12–12	-0.08	16%	24 Apr →
inferno	12–12	-0.04	28%	21 Apr →
ancient	12–12	-0.06	12%	21 Apr →
vertigo	8–13	0.01	9%	21 Apr →
office	4–13	-0.04	13%	21 Apr →
dust2	8–13	-0.09	40%	18 Apr →
inferno	10–13	-0.03	21%	18 Apr →
nuke	13–9	-0.01	17%	17 Apr →
ancient	3–13	-0.06	24%	17 Apr →
anubis	13–9	-0.05	18%	17 Apr →
mirage	8–13	-0.07	15%	17 Apr →