yourwombat — CS2 Stats

76561198034537139[U:1:74271411]

1,866Tracked matches54%Win rate2020Tracked since

CSDB Rating7.3 StrongAggressive Rifler

FaceitLevel 10 · 2,728 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim93

Positioning63

Utility72

0–100 skill scores via Leetify.

Recent form

STEADY60–38–2Last 10060%Win rateLLWLLWWLWL

Last 10 vs previous 10: -30pp win rate · -0.03 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim9.3

Aggression7.7

Utility7.2

Positioning6.3

Opening Duels3.3

Clutch4.0

Sharp aimerStrong CT-side openerEffective flashes

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 b1t 96% playstyle similarity

Most alike: opening-duel success, 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

Aim. Aim score of 93 — the mechanical foundation is a clear strength.

Areas to improve

T-side openings. Opening success drops from 56% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim9.3

Positioning6.3

Utility7.2

Mechanics6.9

Opening Duels3.3

Win Impact6.2

Composite 7.3/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.03

first ⅓ avg 0.03 → last ⅓ avg 0.01

Reaction time469ms−84ms

first ⅓ avg 554ms → last ⅓ avg 469ms

Headshot accuracy20.8%−0.9%

first ⅓ avg 21.7% → last ⅓ avg 20.8%

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

0.17Best rating — cache 13–10

13–1Biggest win — ancient

7Longest win streak

L2Current streak

9–5In matches decided by ≤2 rounds

5Overtime games

Map breakdown

overpassBest map · 71% over 7infernoWeakest map · 44% over 9

Map	Grade	Played	Record	Win rate	Avg rating
mirage	A	25	16–9	64%	0.03
dust2	S	18	12–6	67%	0.03
anubis	A	13	8–5	62%	0.04
nuke	B	13	7–6	54%	0.01
inferno	C	9	4–5	44%	0.01
overpass	S	7	5–2	71%	0.00
train	B	6	3–3	50%	0.03
cache	A	5	3–2	60%	0.09
ancient	—	3	1–2	33%	-0.02
office	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (44% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,093Matches

60%Win rate

1.31Avg K/D

80.2ADR

44%Headshot %

Clutches & streaks

40%1v1 clutch win

26%1v2 clutch win

22Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	150	54%	1.38	16.9
Dust2	98	63%	1.18	17.3
Anubis	85	58%	1.22	17.1
Inferno	80	64%	1.26	15.1
Nuke	56	55%	1.15	15.4
Overpass	27	63%	1.23	15.8
Vertigo	26	69%	1.35	17.3
Ancient	21	57%	1.09	16.2

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.

21.0%Headshot accuracy

39.5%Accuracy (enemy spotted)

44.8%Spray accuracy

81.0%Counter-strafing

7.9°Preaim

467msReaction time

29.9%T opening success

56.3%CT opening success

0.71Enemies flashed / flash

14.0%Flash assists

8.56HE damage / grenade

14.31Flashes / 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 29.9046% — 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.

44% win rate across 9 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
inferno	2–13	-0.09	7%	26 Aug →
anubis	4–13	0.01	21%	26 Aug →
dust2	13–9	0.02	23%	12 Jul →
dust2	10–13	-0.02	18%	7 Jul →
mirage	9–13	0.04	15%	7 Jul →
mirage	13–9	0.03	26%	5 Jul →
anubis	13–11	0.04	27%	1 Jul →
inferno	5–13	-0.06	18%	16 Jun →
anubis	16–13	0.02	9%	16 Jun →
overpass	4–13	-0.05	33%	16 Jun →
dust2	13–7	0.07	39%	16 Jun →
mirage	13–10	0.06	33%	16 Jun →
nuke	4–13	-0.08	8%	15 Jun →
inferno	7–13	0.03	29%	12 Jun →
mirage	13–8	0.03	19%	12 Jun →
overpass	13–6	-0.00	17%	12 Jun →
overpass	13–11	0.06	17%	10 Jun →
dust2	13–6	0.01	18%	9 Jun →
inferno	13–7	0.05	28%	9 Jun →
anubis	10–13	-0.01	19%	8 Jun →
mirage	2–13	-0.08	7%	8 Jun →
mirage	9–13	-0.01	25%	7 Jun →
mirage	13–6	-0.01	23%	1 Jun →
mirage	14–16	0.02	21%	26 May →
cache	13–3	0.02	19%	26 May →
cache	12–12	0.08	16%	26 May →
cache	12–12	0.06	18%	25 May →
overpass	13–7	-0.02	17%	18 May →
nuke	13–8	-0.00	26%	30 Apr →
dust2	10–13	0.02	30%	30 Apr →
inferno	6–13	-0.03	22%	30 Apr →
mirage	3–13	0.01	16%	29 Apr →
nuke	5–13	-0.05	23%	29 Apr →
cache	13–6	0.12	14%	29 Apr →
cache	13–10	0.17	33%	29 Apr →
anubis	13–4	0.13	20%	28 Apr →
mirage	13–3	0.09	11%	27 Apr →
dust2	13–11	0.03	17%	21 Apr →
ancient	7–13	-0.05	25%	21 Apr →
nuke	13–10	0.02	24%	20 Apr →
mirage	11–13	0.04	46%	19 Apr →
nuke	13–7	0.05	11%	18 Apr →
anubis	13–6	0.08	22%	18 Apr →
dust2	5–13	0.06	15%	17 Apr →
dust2	13–4	0.08	31%	8 Apr →
nuke	9–13	0.04	19%	24 Mar →
inferno	11–13	-0.04	17%	24 Mar →
mirage	13–7	-0.03	10%	24 Mar →
dust2	5–13	0.03	18%	24 Mar →
nuke	13–9	-0.02	18%	23 Mar →
mirage	13–9	0.07	24%	23 Mar →
mirage	13–7	0.04	11%	22 Mar →
nuke	13–4	0.09	23%	22 Mar →
mirage	13–4	0.04	8%	22 Mar →
dust2	17–19	0.03	23%	21 Mar →
anubis	2–13	-0.02	22%	21 Mar →
overpass	13–5	-0.01	17%	3 Mar →
mirage	13–6	0.09	12%	24 Feb →
nuke	13–6	0.03	55%	23 Feb →
anubis	9–13	0.04	18%	23 Feb →
mirage	13–10	0.05	23%	17 Feb →
nuke	13–2	0.12	26%	17 Feb →
mirage	13–9	0.03	19%	3 Feb →
mirage	13–11	0.01	18%	27 Nov →
train	10–13	0.01	26%	25 Nov →
overpass	13–10	-0.01	11%	15 Oct →
mirage	7–13	-0.02	5%	15 Oct →
train	13–6	-0.01	18%	14 Oct →
mirage	13–6	0.10	29%	14 Oct →
nuke	10–13	-0.00	16%	7 Oct →
mirage	3–13	0.01	15%	6 Oct →
nuke	9–13	0.01	20%	6 Oct →
mirage	8–13	-0.03	29%	11 Sept →
overpass	14–16	0.02	16%	25 Jul →
inferno	13–11	-0.00	31%	1 Apr →
mirage	9–2	0.15	19%	1 Apr →
inferno	13–7	0.06	18%	25 Feb →
ancient	10–13	-0.03	20%	24 Feb →
dust2	13–8	0.04	16%	19 Feb →
train	13–9	-0.00	23%	18 Feb →
dust2	13–11	-0.03	26%	17 Feb →
mirage	13–8	0.04	22%	13 Feb →
dust2	13–4	0.08	28%	6 Feb →
anubis	13–4	0.08	23%	3 Feb →
dust2	13–9	0.09	23%	2 Feb →
train	5–13	0.02	15%	20 Jan →
nuke	3–13	-0.05	29%	13 Jan →
inferno	13–2	0.12	25%	4 Jan →
anubis	13–11	0.00	25%	2 Jan →
dust2	19–17	-0.01	18%	2 Jan →
dust2	13–5	-0.00	19%	17 Dec →
ancient	13–1	0.03	17%	5 Dec →
anubis	13–5	0.06	21%	3 Dec →
train	10–13	0.11	27%	14 Nov →
train	13–11	0.02	21%	14 Nov →
dust2	5–13	-0.06	12%	30 Oct →
anubis	13–7	0.05	21%	18 Oct →
anubis	10–13	-0.01	12%	17 Oct →
office	13–6	-0.01	45%	11 Oct →
dust2	13–3	0.11	18%	9 Oct →