girthyBABOON39 — CS2 Stats

76561198936016138[U:1:975750410]✓ No bans

606Tracked matches53%Win rate2024Tracked since

CSDB Rating3.5 Learning

Premier CS Rating7,756Light Blue band · top ~65.6% of ranked players (population est.)

WingmanSilver IV

Ladder ranks via Leetify

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Performance scores

Aim31

Positioning26

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY44–55–1Last 10044%Win rateLWLWLLWWLW

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

Player DNA

Aim3.1

Aggression0.9

Utility5.6

Positioning2.6

Opening Duels0.0

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 67% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower opening-fight frequency; 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. 717ms 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

Aim3.1

Positioning2.6

Utility5.6

Mechanics6.6

Opening Duels0.0

Win Impact6.1

Composite 3.5/10 (Learning), 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-0.04−0.02

first ⅓ avg -0.02 → last ⅓ avg -0.04

Reaction time727ms+14ms

first ⅓ avg 713ms → last ⅓ avg 727ms

Headshot accuracy12.8%−5.0%

first ⅓ avg 17.8% → last ⅓ avg 12.8%

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

0.07Best rating — ancient 11–13

13–1Biggest win — mirage

5Longest win streak

10–8In matches decided by ≤2 rounds

5Overtime games

Map breakdown

ancientBest map · 57% over 14infernoWeakest map · 25% over 12

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	31	16–15	52%	-0.04
dust2	C	30	12–18	40%	-0.04
ancient	A	14	8–6	57%	-0.02
inferno	D	12	3–9	25%	-0.02
anubis	D	7	2–5	29%	-0.05
nuke	—	3	1–2	33%	-0.06
overpass	—	2	2–0	100%	0.03
cache	—	1	0–1	0%	-0.12

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

44Matches

34%Win rate

0.64Avg K/D

62.7ADR

42%Headshot %

Clutches & streaks

40%1v1 clutch win

14%1v2 clutch win

2Longest win streak

Recent Faceit resultsWLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	14	43%	0.67	11.4
Ancient	9	33%	0.72	10.1
Nuke	6	33%	0.47	5.8
Inferno	5	20%	0.55	9.8
Anubis	4	50%	0.84	10.5
Dust2	3	33%	0.66	7.3
Overpass	1	0%	0.14	2.0
Vertigo	1	0%	0.86	12.0

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.

13.0%Headshot accuracy

32.4%Accuracy (enemy spotted)

32.1%Spray accuracy

79.5%Counter-strafing

13.9°Preaim

717msReaction time

23.7%T opening success

21.5%CT opening success

0.54Enemies flashed / flash

5.2%Flash assists

5.85HE damage / grenade

14.04Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.88° — above the 12° mark we flag
Aim Training →
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 13.0383% — below the 15% mark we flag
Aim Training →
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 716.9605ms — above the 700ms mark we flag
Aim Training →

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.

25% win rate across 12 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
nuke	9–13	-0.06	16%	26 Aug →
dust2	13–6	-0.03	12%	26 Aug →
mirage	10–13	-0.12	8%	25 Aug →
ancient	13–9	-0.03	4%	25 Aug →
dust2	2–13	-0.12	12%	24 Aug →
anubis	8–13	-0.06	11%	24 Aug →
mirage	13–2	0.03	24%	24 Aug →
anubis	13–3	-0.02	30%	23 Aug →
dust2	10–13	-0.09	24%	23 Aug →
mirage	13–8	-0.00	8%	16 Aug →
dust2	8–13	-0.07	10%	16 Aug →
mirage	11–13	-0.08	18%	31 Jul →
dust2	13–5	-0.06	7%	31 Jul →
inferno	4–13	-0.11	11%	30 Jul →
mirage	13–7	-0.04	13%	29 Jul →
dust2	13–7	-0.00	21%	29 Jul →
mirage	13–2	-0.05	5%	29 Jul →
mirage	1–13	-0.08	3%	28 Jul →
dust2	13–11	0.04	16%	28 Jul →
mirage	13–3	0.01	24%	17 Jul →
mirage	9–13	-0.04	11%	9 Jul →
cache	7–13	-0.12	14%	7 Jul →
anubis	9–13	-0.05	14%	6 Jul →
ancient	13–6	0.03	10%	6 Jul →
anubis	6–13	-0.07	7%	5 Jul →
mirage	1–13	-0.06	18%	5 Jul →
ancient	13–7	0.01	9%	3 Jul →
mirage	13–9	-0.02	12%	1 Jul →
mirage	13–5	-0.00	16%	29 Jun →
dust2	13–10	0.03	8%	29 Jun →
dust2	16–14	-0.02	13%	28 Jun →
ancient	4–13	-0.08	10%	28 Jun →
anubis	4–13	-0.09	6%	28 Jun →
mirage	5–13	-0.02	15%	28 Jun →
mirage	13–10	-0.06	22%	24 Jun →
mirage	13–3	-0.01	11%	23 Jun →
ancient	3–13	-0.11	5%	23 Jun →
inferno	8–13	0.01	16%	23 Jun →
mirage	13–1	0.01	8%	22 Jun →
dust2	13–11	0.02	18%	22 Jun →
inferno	13–4	0.01	11%	22 Jun →
dust2	3–13	-0.07	21%	22 Jun →
dust2	8–13	-0.10	11%	21 Jun →
nuke	5–1	-0.11	0%	21 Jun →
inferno	7–13	-0.03	12%	13 Jun →
dust2	13–16	-0.06	11%	11 Jun →
dust2	10–13	-0.08	8%	10 Jun →
dust2	15–15	-0.05	11%	7 Jun →
dust2	1–10	-0.06	26%	6 Jun →
ancient	13–11	-0.07	7%	6 Jun →
ancient	9–13	-0.02	12%	6 Jun →
ancient	13–2	-0.01	7%	6 Jun →
dust2	4–13	-0.09	12%	6 Jun →
mirage	5–13	-0.05	10%	5 Jun →
inferno	13–2	0.00	16%	5 Jun →
inferno	6–12	-0.02	7%	4 Jun →
mirage	6–13	-0.03	9%	4 Jun →
mirage	5–13	-0.03	8%	3 Jun →
dust2	11–13	-0.01	10%	2 Jun →
dust2	10–13	-0.02	11%	2 Jun →
dust2	4–13	-0.07	17%	1 Jun →
mirage	11–13	-0.02	11%	1 Jun →
inferno	8–13	-0.04	16%	30 May →
mirage	8–13	-0.10	13%	30 May →
anubis	10–13	-0.03	10%	28 May →
dust2	5–13	-0.09	15%	25 May →
mirage	13–10	-0.06	16%	21 May →
dust2	11–13	-0.03	17%	20 May →
anubis	13–11	-0.02	15%	18 May →
mirage	11–13	-0.01	18%	18 May →
mirage	13–3	-0.01	3%	17 May →
mirage	13–9	-0.01	14%	27 Apr →
ancient	13–6	0.05	20%	18 Apr →
mirage	13–7	-0.08	8%	11 Apr →
dust2	16–14	-0.02	16%	31 Jan →
nuke	8–13	-0.02	13%	31 Jan →
ancient	13–16	-0.07	8%	2 Nov →
ancient	4–13	0.01	13%	31 Oct →
dust2	13–3	-0.03	19%	27 Oct →
ancient	7–6	-0.05	8%	27 Oct →
overpass	13–11	0.04	17%	19 Oct →
dust2	13–2	-0.06	15%	3 Oct →
mirage	6–13	-0.05	14%	2 Oct →
dust2	13–11	-0.00	17%	29 Sept →
dust2	11–13	-0.02	16%	28 Sept →
inferno	9–13	0.01	24%	27 Sept →
dust2	7–13	-0.04	19%	17 Sept →
inferno	11–13	0.01	15%	16 Sept →
mirage	10–13	-0.06	6%	16 Sept →
ancient	13–9	-0.01	28%	13 Sept →
mirage	7–13	-0.05	22%	13 Sept →
ancient	11–13	0.07	18%	10 Sept →
inferno	13–10	-0.02	17%	8 Sept →
dust2	13–11	-0.01	11%	6 Sept →
inferno	8–13	-0.01	11%	3 Sept →
mirage	13–7	-0.08	15%	1 Sept →
dust2	4–13	-0.11	31%	31 Aug →
inferno	7–13	-0.01	12%	28 Aug →
overpass	5–0	0.02	100%	28 Aug →
mirage	13–10	-0.02	6%	27 Aug →