ℕ𝕚𝕘𝕥𝕙𝕞𝕒𝕣 — CS2 Stats

TR76561198706331847[U:1:746066119]Steam profile ↗✓ No bans

196Tracked matches0%Win rate2026Tracked since

CSDB Rating1.6 LearningAll-Rounder

Premier CS Rating4,457Grey band · top ~81.1% of ranked players (population est.)

CSDB Leaderboard#202449 of 257778 tracked

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 26 Oct 2026 (yesterday). Ranks are recorded once per day this page is viewed.

−2088Premier CS Rating · 6,545 → 4,457

Rating over time

Premier CS Rating: 4,457 -7,252 28 Sept – 27 Oct · 13 days played

18,972Peak Premier in tracked matches

13Days played since 2026-09-28

Premier CS Rating

14,139 below peak (18,596)
-7,252 over 30 days · declining
Next: Light Blue band at 5,000 — 543 to go
Reached: Purple band · Blue band · Light Blue band
Purple band first seen 2026-10-15
Blue band first seen 2026-10-15

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

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Performance scores

Aim5

Positioning9

Utility1

0–100 skill scores via Leetify.

Recent form

COLD55–45Last 10055%Win rateLLLLLLLLLL

Last 10 vs previous 10: 0pp win rate · −0.00 avg rating · +5.2pp headshot accuracy · +147ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

0–5 · 0% win rate
Avg rating -0.07
Avg headshot accuracy 13%
Avg reaction 945ms

Last 10

0–10 · 0% win rate
Avg rating -0.07
Avg headshot accuracy 16%
Avg reaction 891ms

Last 20

0–20 · 0% win rate
Avg rating -0.07
Avg headshot accuracy 14%
Avg reaction 817ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim0.5

Utility0.1

Positioning0.9

Opening Duels0.0

Excellent counter-strafingLimited utility dependence

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like donk 75% 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

Strengths

Counter-strafing. 92% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Reaction time. 856ms 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

Aim0.5

Positioning0.9

Utility0.1

Mechanics9.2

Opening Duels0.0

Win Impact0.0

Composite 1.6/10 (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-0.07−0.17

first ⅓ avg 0.09 → last ⅓ avg -0.07

Reaction time806ms+334ms

first ⅓ avg 472ms → last ⅓ avg 806ms

Headshot accuracy12.9%−14.4%

first ⅓ avg 27.3% → last ⅓ avg 12.9%

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.

Personal bests

0.27Best match rating · 13–2 · nuke, 29 Sept →

64%Best headshot accuracy · 13–7 · train, 2 Oct →

281msFastest reaction time · 13–3 · anubis, 4 Oct →

13–1Biggest win · dust2, 5 Oct →

Across the last 100 tracked matches.

Highlights

17Longest win streak

L33Current streak

1–5In matches decided by ≤2 rounds

Map breakdown

vertigoBest map · 100% over 5anubisWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	20	8–12	40%	0.01
mirage	C	18	8–10	44%	0.01
nuke	S	17	12–5	71%	0.05
inferno	C	10	4–6	40%	0.01
cache	S	10	7–3	70%	0.07
anubis	D	9	3–6	33%	0.01
ancient	C	5	2–3	40%	0.04
vertigo	S	5	5–0	100%	0.09
train	—	3	3–0	100%	0.04
office	—	2	2–0	100%	0.11
overpass	—	1	1–0	100%	-0.00

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

13.2%Headshot accuracy

14.6%Accuracy (enemy spotted)

19.2%Spray accuracy

91.5%Counter-strafing

14.2°Preaim

856msReaction time

3.3%T opening success

0.0%CT opening success

0.00Enemies flashed / flash

0.0%Flash assists

0.00HE damage / grenade

0.03Flashes / 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 14.2479° — 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 13.1745% — 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 855.7143ms — above the 700ms mark we flag
Aim Training →

Spend your practice time on Anubis

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

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	0–13	-0.05	0%	27 Oct →
mirage	0–13	-0.06	19%	26 Oct →
mirage	0–13	-0.11	15%	26 Oct →
anubis	0–13	-0.08	0%	26 Oct →
dust2	0–13	-0.06	33%	26 Oct →
mirage	0–13	-0.07	22%	26 Oct →
inferno	0–13	-0.09	0%	26 Oct →
anubis	0–13	-0.09	33%	26 Oct →
dust2	0–13	-0.04	40%	26 Oct →
anubis	0–13	-0.07	0%	26 Oct →
dust2	0–13	-0.07	0%	26 Oct →
ancient	0–13	-0.10	0%	25 Oct →
dust2	0–13	-0.07	20%	25 Oct →
nuke	0–13	-0.06	17%	25 Oct →
anubis	0–13	-0.08	0%	25 Oct →
inferno	0–13	-0.05	0%	19 Oct →
dust2	0–13	-0.05	6%	19 Oct →
mirage	0–13	-0.08	0%	19 Oct →
mirage	0–13	-0.06	57%	19 Oct →
mirage	2–13	-0.08	11%	19 Oct →
inferno	0–13	-0.06	25%	19 Oct →
dust2	0–13	-0.11	25%	19 Oct →
mirage	0–13	-0.06	0%	19 Oct →
inferno	0–13	-0.06	36%	19 Oct →
ancient	0–13	-0.07	10%	19 Oct →
nuke	0–13	-0.09	0%	19 Oct →
inferno	0–13	-0.06	0%	19 Oct →
ancient	0–13	-0.05	0%	19 Oct →
mirage	1–13	-0.11	0%	19 Oct →
dust2	6–13	-0.08	22%	19 Oct →
dust2	11–13	-0.13	33%	19 Oct →
mirage	0–2	0.00	0%	6 Oct →
nuke	0–3	-0.02	0%	6 Oct →
mirage	13–5	0.01	19%	6 Oct →
anubis	13–4	0.06	26%	5 Oct →
dust2	13–9	0.10	29%	5 Oct →
dust2	5–13	0.08	25%	5 Oct →
cache	13–2	0.05	17%	5 Oct →
anubis	13–3	0.14	19%	5 Oct →
nuke	13–7	0.05	27%	5 Oct →
inferno	13–3	0.04	22%	5 Oct →
mirage	13–2	0.12	37%	5 Oct →
mirage	13–7	0.02	13%	5 Oct →
dust2	13–8	0.15	28%	5 Oct →
dust2	13–1	0.11	26%	5 Oct →
anubis	13–3	0.16	28%	4 Oct →
nuke	13–5	-0.01	53%	4 Oct →
train	13–10	0.01	22%	4 Oct →
cache	13–11	0.06	15%	4 Oct →
overpass	13–10	-0.00	18%	4 Oct →
vertigo	13–10	0.15	33%	4 Oct →
ancient	13–3	0.21	35%	3 Oct →
nuke	13–7	0.07	28%	3 Oct →
nuke	13–8	0.14	23%	3 Oct →
anubis	6–13	0.05	31%	2 Oct →
ancient	13–1	0.21	24%	2 Oct →
dust2	13–3	0.06	21%	2 Oct →
dust2	13–10	0.05	23%	2 Oct →
train	13–3	0.08	32%	2 Oct →
vertigo	13–8	0.03	30%	2 Oct →
nuke	11–13	0.02	36%	2 Oct →
train	13–7	0.04	64%	2 Oct →
vertigo	13–7	0.01	33%	2 Oct →
dust2	4–13	-0.06	17%	2 Oct →
nuke	13–9	0.01	30%	2 Oct →
cache	13–10	0.05	37%	2 Oct →
cache	6–11	0.12	36%	1 Oct →
mirage	13–5	0.12	22%	1 Oct →
mirage	13–10	0.07	19%	1 Oct →
cache	13–6	-0.03	26%	1 Oct →
mirage	13–8	0.11	33%	1 Oct →
nuke	10–13	0.01	36%	1 Oct →
dust2	4–13	-0.03	42%	1 Oct →
cache	13–3	0.01	12%	1 Oct →
office	7–0	0.15	36%	30 Sept →
office	13–1	0.07	27%	30 Sept →
nuke	13–6	0.11	30%	30 Sept →
nuke	13–2	0.07	15%	30 Sept →
cache	13–9	0.10	20%	30 Sept →
nuke	13–1	0.00	30%	30 Sept →
inferno	13–3	0.19	27%	30 Sept →
cache	10–13	0.17	25%	30 Sept →
mirage	13–2	0.07	32%	30 Sept →
nuke	13–2	0.27	34%	29 Sept →
nuke	13–2	0.18	22%	29 Sept →
dust2	7–13	0.11	33%	29 Sept →
inferno	13–4	0.17	26%	29 Sept →
nuke	13–7	0.04	17%	29 Sept →
dust2	13–2	0.03	30%	29 Sept →
dust2	13–10	0.19	37%	29 Sept →
vertigo	13–4	0.16	23%	29 Sept →
vertigo	13–6	0.10	32%	29 Sept →
nuke	13–3	0.09	31%	29 Sept →
cache	13–3	0.16	50%	29 Sept →
cache	0–2	-0.04	0%	29 Sept →
inferno	2–13	-0.09	17%	29 Sept →
inferno	13–10	0.15	35%	28 Sept →
mirage	13–8	0.20	29%	28 Sept →
mirage	11–13	0.15	29%	28 Sept →
dust2	13–9	0.02	23%	28 Sept →