Garry T. Snail Trail. — CS2 Stats

76561199752102707[U:1:1791836979]Steam profile ↗✓ No bans

583Tracked matches61%Win rate2025Tracked since

CSDB Rating5.3 DevelopingPassive Rifler

Premier CS Rating11,548Blue band · top ~46.7% of ranked players (population est.)

CSDB Leaderboard#23686 of 33691 tracked

WingmanGold Nova I

Ladder ranks via Leetify

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Performance scores

Aim66

Positioning39

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY52–43–5Last 10052%Win rateWLWWWTWLLW

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

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim6.6

Aggression2.9

Utility4.9

Positioning3.9

Opening Duels0.3

Clutch4.0

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.

Your pro match

Plays most like NiKo 80% playstyle similarity

Most alike: utility contribution, opening-duel success.

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 42% on CT to 20% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 577ms 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

Aim6.6

Positioning3.9

Utility4.9

Mechanics7.2

Opening Duels1.5

Win Impact8.6

Composite 5.3/10 (Developing), 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

Match rating-0.02−0.00

first ⅓ avg -0.02 → last ⅓ avg -0.02

Reaction time575ms−66ms

first ⅓ avg 641ms → last ⅓ avg 575ms

Headshot accuracy12.2%+0.4%

first ⅓ avg 11.8% → last ⅓ avg 12.2%

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.

Highlights

0.10Best rating — cache 13–3

13–0Biggest win — ancient

5Longest win streak

5–6In matches decided by ≤2 rounds

4Overtime games

Map breakdown

ancientBest map · 70% over 10infernoWeakest map · 39% over 18

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	25	13–12	52%	-0.01
nuke	A	23	14–9	61%	-0.01
inferno	C	18	7–11	39%	-0.03
ancient	S	10	7–3	70%	0.00
anubis	B	6	3–3	50%	-0.00
overpass	S	6	4–2	67%	-0.02
dust2	C	5	2–3	40%	-0.03
mirage	—	3	1–2	33%	-0.02
vertigo	—	2	1–1	50%	-0.02
office	—	2	0–2	0%	-0.08

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (39% over 18). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

17Matches

35%Win rate

0.59Avg K/D

50.8ADR

35%Headshot %

Clutches & streaks

40%1v1 clutch win

12%1v2 clutch win

2Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	6	33%	0.50	6.8
Dust2	5	40%	0.50	6.8
Nuke	4	50%	0.80	11.3
Overpass	1	0%	0.77	17.0
Inferno	1	0%	0.56	9.0

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.

12.1%Headshot accuracy

36.4%Accuracy (enemy spotted)

37.3%Spray accuracy

82.5%Counter-strafing

10.5°Preaim

577msReaction time

20.3%T opening success

42.3%CT opening success

0.54Enemies flashed / flash

5.9%Flash assists

12.07HE damage / grenade

5.72Flashes / 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.

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 12.0915% — below the 15% mark we flag
Aim Training →
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 20.2913% — below the 40% mark we flag

Spend your practice time on Inferno

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

39% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–1	0.05	16%	29 Aug →
nuke	9–13	-0.01	13%	29 Aug →
nuke	13–11	-0.05	9%	28 Aug →
nuke	12–3	-0.06	7%	28 Aug →
anubis	13–6	-0.03	18%	24 Aug →
nuke	12–12	-0.06	5%	16 Aug →
vertigo	13–8	-0.01	17%	15 Aug →
anubis	11–13	0.03	14%	15 Aug →
inferno	11–13	-0.02	12%	15 Aug →
cache	13–3	0.10	3%	15 Aug →
vertigo	6–13	-0.04	14%	15 Aug →
inferno	0–13	-0.06	13%	15 Aug →
nuke	13–9	-0.05	27%	15 Aug →
inferno	0–8	-0.08	6%	14 Aug →
nuke	13–8	0.10	11%	14 Aug →
cache	13–7	0.07	13%	14 Aug →
overpass	13–5	-0.02	7%	14 Aug →
ancient	13–5	-0.04	13%	12 Aug →
overpass	13–6	-0.02	13%	12 Aug →
nuke	8–13	-0.06	11%	10 Aug →
nuke	6–4	-0.05	8%	9 Aug →
nuke	6–13	-0.07	0%	9 Aug →
cache	16–12	0.00	7%	9 Aug →
cache	15–15	-0.00	17%	8 Aug →
inferno	5–13	-0.05	7%	8 Aug →
ancient	9–13	-0.05	18%	8 Aug →
nuke	13–3	0.02	12%	7 Aug →
inferno	2–9	-0.09	8%	6 Aug →
inferno	5–0	-0.05	20%	6 Aug →
cache	13–7	0.02	17%	6 Aug →
cache	11–13	-0.06	10%	4 Aug →
nuke	4–13	0.02	16%	4 Aug →
cache	5–13	-0.07	20%	29 Jul →
ancient	4–13	-0.05	4%	28 Jul →
overpass	6–13	-0.02	10%	28 Jul →
nuke	13–7	-0.02	8%	28 Jul →
overpass	13–9	0.07	13%	27 Jul →
ancient	13–0	0.10	20%	27 Jul →
ancient	16–13	0.00	12%	26 Jul →
inferno	7–11	-0.02	9%	26 Jul →
cache	13–4	-0.01	13%	25 Jul →
cache	13–11	-0.03	8%	25 Jul →
nuke	13–7	0.01	12%	25 Jul →
anubis	13–4	0.04	17%	25 Jul →
cache	9–13	-0.01	15%	25 Jul →
nuke	13–6	-0.02	12%	25 Jul →
inferno	13–6	0.04	17%	24 Jul →
office	7–13	-0.06	12%	24 Jul →
cache	9–13	-0.07	16%	24 Jul →
nuke	13–1	0.09	13%	24 Jul →
anubis	9–13	-0.01	14%	24 Jul →
inferno	12–12	-0.09	9%	24 Jul →
cache	13–6	-0.01	17%	21 Jul →
nuke	13–5	0.04	18%	19 Jul →
mirage	3–13	-0.04	2%	19 Jul →
cache	13–7	-0.03	11%	19 Jul →
inferno	13–7	-0.02	9%	18 Jul →
inferno	13–8	-0.05	10%	18 Jul →
nuke	13–10	0.04	8%	18 Jul →
ancient	13–4	0.05	12%	18 Jul →
office	1–9	-0.10	10%	17 Jul →
inferno	13–2	0.08	14%	17 Jul →
nuke	12–12	-0.06	9%	17 Jul →
dust2	10–13	-0.09	17%	17 Jul →
nuke	13–7	0.02	16%	17 Jul →
dust2	13–11	-0.02	15%	16 Jul →
anubis	10–13	-0.07	0%	16 Jul →
overpass	5–13	-0.09	4%	16 Jul →
ancient	13–3	-0.04	11%	16 Jul →
nuke	13–10	-0.00	15%	16 Jul →
cache	0–13	-0.06	8%	16 Jul →
cache	11–13	-0.05	7%	16 Jul →
nuke	12–12	-0.04	10%	16 Jul →
inferno	11–13	-0.01	13%	16 Jul →
inferno	13–8	0.03	8%	14 Jul →
cache	5–13	-0.02	16%	14 Jul →
cache	13–11	0.03	12%	13 Jul →
inferno	8–13	-0.03	9%	13 Jul →
dust2	16–12	0.00	21%	13 Jul →
mirage	1–8	-0.05	10%	13 Jul →
anubis	13–4	0.01	13%	13 Jul →
cache	6–13	0.03	11%	12 Jul →
mirage	13–6	0.04	21%	12 Jul →
ancient	3–13	0.09	14%	12 Jul →
ancient	13–9	-0.06	9%	11 Jul →
cache	13–9	0.03	17%	11 Jul →
nuke	10–13	-0.03	15%	10 Jul →
inferno	13–4	-0.01	6%	10 Jul →
ancient	13–6	0.01	20%	10 Jul →
overpass	13–9	-0.03	19%	9 Jul →
inferno	8–13	-0.06	12%	9 Jul →
cache	6–13	-0.08	11%	9 Jul →
cache	3–13	0.01	8%	8 Jul →
cache	0–3	-0.02	0%	8 Jul →
inferno	10–13	-0.05	13%	8 Jul →
dust2	3–13	-0.01	9%	8 Jul →
dust2	1–3	-0.02	11%	8 Jul →
nuke	4–13	-0.02	8%	8 Jul →
cache	13–8	-0.01	19%	7 Jul →
cache	13–8	-0.04	10%	7 Jul →