Taxooh — CS2 Stats

76561198158266790[U:1:198001062]Steam profile ↗✓ No bans

3,154Tracked matches30%Win rate2020Tracked since

CSDB Rating6.3 SolidAggressive Rifler

FaceitLevel 10 · 2,695 ELOTop 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

Share this profile

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim85

Positioning59

Utility59

0–100 skill scores via Leetify.

Recent form

STEADY45–54–1Last 10045%Win rateLLLWWLWWLL

Last 10 vs previous 10: +20pp win rate · +0.03 avg rating

Player DNA

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

Aim8.5

Aggression8.7

Utility5.9

Positioning5.9

Opening Duels4.5

Clutch3.2

Sharp aimerStrong 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 donk 93% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

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 57% on CT to 39% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 582ms 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

Aim8.5

Positioning5.9

Utility5.9

Mechanics7.7

Opening Duels4.5

Win Impact0.0

Composite 6.3/10 (Solid), 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 rating-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time587ms−83ms

first ⅓ avg 670ms → last ⅓ avg 587ms

Headshot accuracy22.1%+1.4%

first ⅓ avg 20.8% → last ⅓ avg 22.1%

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 — overpass 13–5

13–3Biggest win — ancient

8Longest win streak

L3Current streak

6–14In matches decided by ≤2 rounds

14Overtime games

Map breakdown

ancientBest map · 56% over 16nukeWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	29	13–16	45%	-0.01
inferno	C	28	12–16	43%	-0.01
ancient	A	16	9–7	56%	0.02
dust2	D	11	3–8	27%	-0.01
nuke	D	5	1–4	20%	-0.05
overpass	—	4	2–2	50%	0.03
cache	—	3	2–1	67%	0.01
train	—	2	2–0	100%	-0.01
vertigo	—	1	1–0	100%	0.04
anubis	—	1	0–1	0%	-0.02

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,161Matches

51%Win rate

1.08Avg K/D

77.1ADR

46%Headshot %

Clutches & streaks

36%1v1 clutch win

19%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	645	53%	1.03	15.1
Inferno	303	55%	1.03	15.7
Ancient	299	50%	0.96	15.1
Dust2	180	48%	0.97	14.8
Anubis	151	50%	0.98	14.7
Vertigo	147	57%	1.15	16.2
Nuke	132	51%	1.00	14.6
Train	51	59%	0.91	15.0

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.

22.1%Headshot accuracy

36.3%Accuracy (enemy spotted)

38.4%Spray accuracy

84.7%Counter-strafing

7.7°Preaim

582msReaction time

38.7%T opening success

56.9%CT opening success

0.57Enemies flashed / flash

9.1%Flash assists

10.32HE damage / grenade

6.95Flashes / 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 38.74% — below the 40% mark we flag

Spend your practice time on Nuke

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	7–13	-0.01	38%	27 Aug →
inferno	8–13	-0.06	28%	20 Aug →
dust2	14–16	0.03	20%	18 Aug →
vertigo	13–8	0.04	27%	9 Aug →
cache	13–5	0.03	30%	8 Aug →
ancient	10–13	0.02	19%	8 Aug →
inferno	13–5	-0.01	31%	5 Aug →
inferno	13–4	-0.01	11%	24 Jul →
mirage	11–13	-0.01	31%	11 Jul →
mirage	9–13	-0.01	21%	4 Jul →
inferno	10–13	-0.02	13%	3 Jul →
dust2	5–13	-0.07	18%	25 Jun →
inferno	19–22	0.02	17%	20 Jun →
dust2	13–10	0.01	20%	18 Jun →
inferno	8–13	0.01	21%	16 Jun →
mirage	11–13	-0.02	21%	11 Jun →
dust2	5–13	0.03	25%	6 Jun →
nuke	2–13	-0.13	14%	12 May →
ancient	8–13	-0.07	21%	12 May →
inferno	13–8	0.01	33%	9 May →
inferno	10–13	-0.01	13%	2 May →
dust2	7–13	-0.02	47%	2 May →
cache	13–7	0.03	21%	28 Apr →
inferno	13–6	-0.02	25%	4 Apr →
nuke	9–13	-0.05	17%	4 Apr →
mirage	6–13	-0.03	11%	28 Mar →
ancient	13–11	-0.01	16%	28 Mar →
mirage	11–13	-0.01	19%	20 Mar →
anubis	11–13	-0.02	25%	19 Mar →
ancient	14–16	0.01	17%	18 Mar →
mirage	2–13	-0.02	13%	18 Mar →
mirage	13–5	-0.02	21%	17 Mar →
mirage	5–13	-0.05	26%	16 Mar →
mirage	13–10	0.03	15%	16 Mar →
inferno	13–10	0.03	17%	4 Mar →
inferno	12–16	-0.07	8%	16 Feb →
inferno	9–13	0.01	14%	31 Jan →
mirage	13–5	-0.01	24%	6 Jan →
ancient	16–13	0.03	23%	6 Jan →
dust2	4–13	-0.03	21%	3 Jan →
ancient	25–22	-0.02	19%	2 Jan →
mirage	13–5	-0.00	13%	28 Dec →
train	13–10	0.02	16%	27 Dec →
inferno	13–9	-0.03	20%	25 Dec →
dust2	8–13	-0.04	30%	23 Dec →
mirage	11–13	0.01	20%	16 Dec →
dust2	9–13	-0.02	24%	6 Dec →
mirage	8–13	0.01	24%	4 Dec →
inferno	13–8	0.04	17%	21 Nov →
mirage	19–15	0.05	18%	15 Nov →
inferno	6–13	-0.02	26%	12 Oct →
inferno	13–10	0.04	15%	11 Oct →
dust2	14–16	-0.03	18%	5 Oct →
inferno	5–13	-0.04	29%	5 Oct →
inferno	13–16	-0.05	12%	3 Oct →
dust2	13–11	0.04	22%	3 Oct →
ancient	6–13	-0.01	26%	3 Oct →
inferno	3–13	-0.04	10%	2 Oct →
inferno	13–9	-0.01	14%	2 Oct →
mirage	13–7	-0.02	17%	2 Oct →
mirage	7–13	-0.00	33%	1 Oct →
overpass	10–13	0.04	26%	1 Oct →
inferno	5–13	-0.04	21%	1 Oct →
ancient	11–13	0.02	22%	30 Sept →
inferno	10–13	-0.03	10%	30 Sept →
mirage	13–8	-0.00	26%	30 Sept →
nuke	15–15	-0.01	30%	29 Sept →
overpass	13–5	0.17	22%	28 Sept →
ancient	5–13	0.04	18%	28 Sept →
train	13–7	-0.04	12%	27 Sept →
ancient	13–11	-0.02	29%	27 Sept →
nuke	3–13	-0.07	33%	27 Sept →
ancient	13–6	0.03	23%	26 Sept →
ancient	11–13	0.03	23%	26 Sept →
mirage	8–13	-0.02	9%	26 Sept →
mirage	11–13	-0.04	13%	25 Sept →
mirage	13–9	-0.04	10%	24 Sept →
mirage	9–13	-0.10	29%	23 Sept →
mirage	13–8	-0.02	24%	22 Sept →
mirage	11–13	0.05	29%	22 Sept →
nuke	13–8	0.04	21%	22 Sept →
overpass	13–11	-0.02	19%	19 Sept →
inferno	5–13	-0.06	4%	18 Sept →
inferno	16–12	-0.04	17%	18 Sept →
mirage	14–16	-0.01	12%	18 Sept →
ancient	16–14	0.05	18%	17 Sept →
inferno	8–13	-0.03	17%	17 Sept →
ancient	13–9	0.07	19%	15 Sept →
mirage	13–8	-0.03	10%	15 Sept →
mirage	13–5	0.05	26%	15 Sept →
mirage	16–12	0.07	22%	14 Sept →
inferno	13–9	0.01	33%	14 Sept →
inferno	13–10	0.05	28%	13 Sept →
dust2	13–6	0.05	37%	13 Sept →
ancient	13–6	0.05	22%	16 Aug →
overpass	10–13	-0.06	13%	16 Aug →
inferno	11–13	-0.03	19%	7 Aug →
mirage	13–11	0.03	22%	7 Aug →
ancient	13–3	0.10	29%	7 Aug →
mirage	9–13	-0.06	23%	7 Aug →