Anks69 — CS2 Stats

76561199029774609[U:1:1069508881]

1,386Tracked matches50%Win rate2021Tracked since

CSDB Rating5.4 DevelopingHybrid Rifler

Premier CS Rating14,999Blue band · top ~28.4% of ranked players (population est.)

CSDB Leaderboard#26619 of 43526 tracked

FaceitLevel 8 · 1,482 ELOTop 31.2% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim69

Positioning56

Utility52

0–100 skill scores via Leetify.

Recent form

STEADY51–47–2Last 10051%Win rateWWLWWWLLWL

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

Player DNA

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

Aim6.9

Aggression8.1

Utility5.2

Positioning5.6

Opening Duels4.3

Clutch3.6

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 ropz 90% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: 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

Strengths

CT openings. 69% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 69% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 618ms 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

Aim6.9

Positioning5.6

Utility5.2

Mechanics5.1

Opening Duels4.9

Win Impact5.0

Composite 5.4/10 (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 rating0.02−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.02

Reaction time637ms−44ms

first ⅓ avg 681ms → last ⅓ avg 637ms

Headshot accuracy21.8%+2.9%

first ⅓ avg 18.9% → last ⅓ avg 21.8%

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

0.22Best rating — overpass 9–1

13–1Biggest win — cache

8Longest win streak

W2Current streak

3–14In matches decided by ≤2 rounds

4Overtime games

Map breakdown

overpassBest map · 83% over 6infernoWeakest map · 38% over 26

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	26	10–16	38%	0.00
dust2	A	15	9–6	60%	0.01
mirage	B	13	6–7	46%	-0.00
nuke	S	12	9–3	75%	0.03
anubis	C	10	4–6	40%	0.01
ancient	B	8	4–4	50%	-0.01
cache	S	6	4–2	67%	0.03
overpass	S	6	5–1	83%	0.09
vertigo	—	2	0–2	0%	-0.04
office	—	1	0–1	0%	-0.11
fachwerk	—	1	0–1	0%	0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 26). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

795Matches

51%Win rate

1.02Avg K/D

77.8ADR

42%Headshot %

Clutches & streaks

38%1v1 clutch win

21%1v2 clutch win

6Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	115	52%	1.07	15.7
Inferno	65	57%	1.19	15.6
Dust2	60	45%	1.14	15.4
Anubis	60	55%	1.09	16.4
Ancient	50	48%	0.97	15.1
Overpass	26	50%	1.21	17.6
Nuke	25	52%	1.18	16.2
Train	18	50%	0.86	12.5

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.

21.6%Headshot accuracy

37.7%Accuracy (enemy spotted)

39.0%Spray accuracy

73.0%Counter-strafing

11.1°Preaim

618msReaction time

25.2%T opening success

69.2%CT opening success

0.60Enemies flashed / flash

5.9%Flash assists

10.16HE damage / grenade

11.41Flashes / 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 25.1714% — 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.

38% win rate across 26 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	13–7	0.09	13%	29 Aug →
nuke	13–10	0.03	16%	23 Aug →
inferno	4–13	-0.04	21%	23 Aug →
nuke	13–10	0.01	26%	19 Aug →
inferno	13–3	0.06	27%	17 Aug →
mirage	13–4	0.12	22%	17 Aug →
dust2	10–13	-0.01	19%	14 Aug →
inferno	4–9	-0.00	21%	11 Aug →
cache	8–3	0.05	23%	9 Aug →
cache	9–13	-0.02	20%	2 Aug →
ancient	13–6	0.08	22%	2 Aug →
inferno	7–13	-0.04	22%	2 Aug →
dust2	7–13	-0.02	14%	2 Aug →
mirage	7–13	0.00	19%	2 Aug →
inferno	9–13	-0.01	31%	25 Jul →
cache	13–6	0.12	33%	25 Jul →
inferno	13–2	0.08	21%	25 Jul →
anubis	13–9	0.03	22%	22 Jul →
nuke	13–4	-0.05	16%	22 Jul →
mirage	4–13	-0.01	29%	21 Jul →
inferno	11–13	0.04	23%	20 Jul →
nuke	13–5	-0.05	21%	20 Jul →
nuke	8–10	0.08	29%	20 Jul →
mirage	1–13	-0.01	22%	20 Jul →
inferno	6–13	-0.04	21%	20 Jul →
dust2	13–5	0.04	16%	20 Jul →
inferno	9–13	0.04	27%	18 Jul →
inferno	5–13	0.04	22%	18 Jul →
office	12–12	-0.11	7%	17 Jul →
fachwerk	12–12	0.05	36%	17 Jul →
mirage	13–9	0.00	10%	13 Jul →
nuke	6–13	-0.03	19%	13 Jul →
vertigo	8–13	-0.02	30%	13 Jul →
dust2	13–4	-0.03	11%	13 Jul →
vertigo	0–13	-0.06	14%	7 Jul →
mirage	7–13	-0.07	18%	5 Jul →
dust2	13–9	-0.04	29%	5 Jul →
ancient	4–13	-0.07	22%	4 Jul →
inferno	13–10	-0.03	13%	3 Jul →
dust2	13–8	0.04	16%	1 Jul →
overpass	13–3	0.10	15%	30 Jun →
inferno	13–3	0.03	26%	30 Jun →
dust2	13–3	0.02	20%	28 Jun →
mirage	13–7	0.08	16%	27 Jun →
inferno	13–2	0.11	21%	25 Jun →
mirage	13–9	0.02	29%	21 Jun →
dust2	4–13	0.01	20%	21 Jun →
cache	11–13	-0.04	36%	14 Jun →
mirage	7–13	-0.06	25%	13 Jun →
dust2	11–13	-0.09	29%	13 Jun →
anubis	11–13	0.01	19%	8 Jun →
inferno	12–16	0.02	12%	8 Jun →
inferno	0–13	-0.07	100%	8 Jun →
inferno	9–7	-0.10	18%	8 Jun →
dust2	16–14	-0.07	12%	7 Jun →
ancient	1–13	-0.10	0%	7 Jun →
anubis	13–4	0.06	16%	7 Jun →
overpass	9–1	0.22	16%	7 Jun →
inferno	9–5	-0.04	30%	7 Jun →
inferno	7–13	-0.05	10%	31 May →
ancient	13–5	0.05	24%	31 May →
mirage	4–13	-0.05	23%	30 May →
inferno	13–9	-0.04	20%	30 May →
anubis	13–6	0.02	26%	30 May →
nuke	13–7	0.02	16%	27 May →
dust2	13–6	0.05	27%	27 May →
inferno	10–13	-0.01	11%	25 May →
nuke	13–3	0.04	17%	24 May →
anubis	3–13	-0.08	17%	20 May →
ancient	4–13	0.04	17%	19 May →
nuke	13–9	0.07	21%	18 May →
anubis	5–13	0.05	31%	18 May →
mirage	13–6	-0.01	16%	17 May →
cache	13–6	0.02	21%	16 May →
overpass	16–12	0.05	14%	16 May →
anubis	11–13	0.05	14%	15 May →
inferno	4–13	-0.00	18%	15 May →
dust2	11–13	0.02	18%	13 May →
anubis	13–10	-0.01	14%	13 May →
inferno	9–5	0.12	24%	10 May →
anubis	11–13	-0.00	14%	2 May →
inferno	9–3	0.05	21%	2 May →
cache	13–1	0.05	17%	1 May →
inferno	7–13	-0.05	29%	26 Apr →
ancient	13–9	-0.03	17%	26 Apr →
inferno	11–13	0.00	22%	25 Apr →
ancient	13–6	-0.01	17%	17 Apr →
dust2	13–3	0.16	26%	17 Apr →
dust2	11–13	0.01	35%	12 Apr →
overpass	13–9	0.06	17%	10 Apr →
overpass	9–13	-0.02	7%	10 Apr →
nuke	9–6	0.13	31%	8 Apr →
mirage	13–7	-0.02	21%	6 Apr →
overpass	13–4	0.10	15%	6 Apr →
inferno	11–13	-0.05	11%	5 Apr →
mirage	5–13	-0.04	9%	5 Apr →
anubis	14–16	0.01	18%	5 Apr →
dust2	13–11	0.08	14%	3 Apr →
ancient	11–13	-0.01	18%	20 Mar →
nuke	11–13	0.05	19%	20 Mar →