d4n7E — CS2 Stats

IN76561198072767971[U:1:112502243]Steam profile ↗✓ No bans

2,995Tracked matches46%Win rate2020Tracked since

6,478Hours in CS2Hrs last 2 wks

CSDB Rating5.3 DevelopingAll-Rounder

CSDB Leaderboard#132705 of 227599 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

Ladder ranks via Leetify

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 39 days played since 4 Nov 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 14,875 -1,476 8 Nov – 14 Dec · 8 days played

16,452Peak Premier in tracked matches

39Days played since 2025-11-04

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

Compare periods

Last 7 days vs previous 7

No matches recorded between 11 Sep 2026 and 19 Sep 2026.

Measured 11 Sep 2026 → 19 Sep 2026; no observation near 14 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 3 among CSDB-tracked players (n=8,862), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 3 median	Level 4 median	vs Level 4
Headshot rate	55.1%	41.9%	42.7%	above
Shot accuracy	17.5%	12.2%	11.2%	above
Kill/death ratio	0.82	0.98	1.00	0.17 short
Match win rate	40.3%	43.3%	43.9%	3.6% short

This profile matches the typical Level 4 player on 2 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim74

Positioning36

Utility42

0–100 skill scores via Leetify.

Recent form

STEADY48–44–8Last 10048%Win rateWWLWTWLLLL

Last 10 vs previous 10: −20pp win rate · −0.00 avg rating · +1.6pp headshot accuracy · +75ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

3–1–1 · 60% win rate
Avg rating -0.02
Avg headshot accuracy 25%
Avg reaction 673ms

Last 10

4–5–1 · 40% win rate
Avg rating -0.03
Avg headshot accuracy 22%
Avg reaction 644ms

Last 20

10–9–1 · 50% win rate
Avg rating -0.03
Avg headshot accuracy 21%
Avg reaction 606ms

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.

Aim7.4

Utility4.2

Positioning3.6

Opening Duels2.5

Clutch3.6

Limited 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 NiKo 91% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower utility contribution; lower positioning 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

Positioning. Positioning trails aim by 37 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 45% on CT to 19% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 632ms 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

Aim7.4

Positioning3.6

Utility4.2

Mechanics7.7

Opening Duels1.9

Win Impact3.8

Composite 5.3/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time627ms−81ms

first ⅓ avg 707ms → last ⅓ avg 627ms

Headshot accuracy21.4%−1.8%

first ⅓ avg 23.2% → last ⅓ avg 21.4%

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

0.09Best match rating · 13–1 · inferno, 7 Dec →

38%Best headshot accuracy · 13–1 · inferno, 7 Dec →

375msFastest reaction time · 13–7 · inferno, 15 Jul →

13–1Biggest win · inferno, 7 Dec →

Across the last 100 tracked matches.

Highlights

6Longest win streak

W2Current streak

6–10In matches decided by ≤2 rounds

5Overtime games

Map breakdown

anubisBest map · 67% over 6infernoWeakest map · 38% over 21

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	36	18–18	50%	-0.02
inferno	C	21	8–13	38%	-0.02
mirage	C	15	6–9	40%	-0.02
ancient	B	10	5–5	50%	-0.00
anubis	S	6	4–2	67%	-0.01
overpass	A	5	3–2	60%	-0.02
cache	—	3	1–2	33%	-0.02
nuke	—	3	2–1	67%	0.00
train	—	1	1–0	100%	-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

175,527Lifetime kills

0.82K/D

8,709Matches

40.3%Match win rate

55.1%Headshot % · Top 10% of Level 3 players

17.5%Shot accuracy · Top 25% of Level 3 players

19,734MVPs

4,884Hours (in match)

3,915Bombs planted

1,553Bombs defused

Most-used weapons

AK-4763,352

M4A4 / M4A1-S34,634

Desert Eagle20,590

P2000 / USP-S8,674

AWP7,671

Glock-184,995

MP93,413

UMP-453,157

MP72,713

P2502,681

Lifetime map wins

17,455inferno

13,860dust2

2,708nuke

2,556vertigo

846train

349cbble

302lake

124safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

888Matches

50%Win rate

1.03Avg K/D

71.6ADR

49%Headshot %

Clutches & streaks

38%1v1 clutch win

18%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	42	43%	0.96	14.5
Mirage	41	39%	0.91	15.8
Ancient	29	45%	0.91	13.4
Inferno	22	59%	0.81	11.3
Vertigo	10	40%	0.86	15.6
Nuke	5	60%	0.87	13.0
Dust2	2	100%	1.14	16.0

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.

21.1%Headshot accuracy

34.4%Accuracy (enemy spotted)

41.9%Spray accuracy

84.5%Counter-strafing

10.7°Preaim

632msReaction time

19.4%T opening success

45.3%CT opening success

0.51Enemies flashed / flash

4.2%Flash assists

9.24HE damage / grenade

4.38Flashes / 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 19.4169% — 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 21 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
dust2	13–8	-0.00	22%	9 Sept →
ancient	13–6	0.02	20%	9 Sept →
mirage	11–13	-0.07	31%	9 Sept →
train	13–11	-0.04	29%	19 Aug →
ancient	12–12	0.02	22%	27 Jul →
overpass	13–5	-0.01	22%	27 Jul →
inferno	10–13	-0.06	22%	27 Jul →
anubis	11–13	-0.06	18%	16 Jul →
inferno	9–13	-0.03	13%	16 Jul →
mirage	9–13	-0.03	16%	15 Jul →
dust2	13–4	0.03	33%	15 Jul →
inferno	8–13	-0.05	18%	15 Jul →
ancient	13–5	0.03	13%	15 Jul →
anubis	11–13	-0.01	23%	15 Jul →
inferno	13–7	-0.07	21%	15 Jul →
dust2	13–10	-0.09	13%	12 Jul →
ancient	10–13	-0.00	12%	12 Jul →
inferno	13–9	-0.03	23%	12 Jul →
mirage	13–9	-0.01	18%	12 Jul →
inferno	3–13	-0.03	24%	10 Jul →
dust2	13–11	0.00	18%	10 Jul →
cache	4–13	-0.04	17%	10 Jul →
inferno	6–13	-0.03	23%	9 Jul →
ancient	13–10	-0.02	15%	9 Jul →
dust2	1–13	-0.08	19%	5 Jul →
inferno	8–13	-0.07	26%	5 Jul →
dust2	8–13	0.05	19%	4 Jul →
dust2	15–15	0.06	23%	4 Jul →
dust2	13–5	0.04	31%	4 Jul →
dust2	14–16	-0.07	26%	4 Jul →
mirage	13–6	-0.01	19%	4 Jul →
dust2	13–4	-0.03	37%	4 Jul →
inferno	13–8	-0.01	18%	4 Jul →
dust2	5–13	-0.05	34%	4 Jul →
ancient	13–11	-0.05	29%	4 Jul →
dust2	15–15	-0.02	18%	4 Jul →
cache	13–8	-0.02	25%	4 Jul →
cache	11–13	-0.00	17%	4 Jul →
dust2	13–3	0.03	25%	4 Jul →
inferno	13–8	0.05	18%	4 Jul →
inferno	13–6	0.01	35%	28 Jun →
dust2	13–11	0.04	28%	28 Jun →
inferno	10–13	-0.01	24%	28 Jun →
anubis	13–8	-0.01	23%	28 Jun →
inferno	7–9	-0.10	21%	23 May →
ancient	7–13	0.04	18%	23 May →
dust2	9–13	0.03	24%	10 May →
dust2	1–4	-0.11	0%	30 Apr →
dust2	13–3	-0.02	24%	25 Apr →
mirage	13–9	-0.01	17%	25 Apr →
mirage	4–13	-0.07	29%	25 Apr →
mirage	13–8	-0.02	16%	23 Apr →
dust2	13–9	-0.02	13%	22 Apr →
inferno	13–4	-0.02	10%	22 Apr →
mirage	15–15	-0.04	7%	21 Apr →
dust2	13–6	-0.04	16%	18 Apr →
mirage	13–2	0.01	9%	18 Apr →
dust2	11–13	-0.03	27%	18 Apr →
ancient	10–13	-0.05	17%	17 Apr →
dust2	9–13	-0.02	18%	15 Apr →
dust2	13–5	-0.04	12%	15 Apr →
inferno	12–12	0.01	20%	15 Apr →
dust2	9–13	-0.08	13%	14 Apr →
dust2	13–6	0.02	33%	14 Apr →
anubis	13–4	0.04	22%	14 Apr →
anubis	13–11	0.03	16%	13 Apr →
dust2	13–11	-0.03	18%	13 Apr →
dust2	13–5	-0.00	17%	26 Mar →
dust2	13–9	0.02	19%	24 Mar →
dust2	12–12	-0.03	23%	19 Mar →
inferno	7–13	-0.01	24%	19 Mar →
mirage	12–12	-0.02	28%	19 Mar →
dust2	13–4	-0.05	24%	19 Mar →
dust2	4–13	-0.00	11%	19 Mar →
dust2	13–4	0.02	16%	16 Dec →
overpass	8–13	0.00	28%	14 Dec →
mirage	10–13	0.06	36%	14 Dec →
dust2	11–13	-0.02	22%	7 Dec →
inferno	13–1	0.09	38%	7 Dec →
dust2	10–13	0.04	23%	3 Dec →
nuke	13–3	-0.00	38%	29 Nov →
dust2	9–13	-0.11	21%	29 Nov →
inferno	7–3	-0.01	30%	23 Nov →
ancient	13–7	-0.04	29%	23 Nov →
dust2	14–16	-0.02	14%	23 Nov →
inferno	8–13	0.02	22%	22 Nov →
mirage	13–6	0.03	10%	22 Nov →
mirage	5–13	-0.07	28%	14 Nov →
overpass	13–8	-0.04	17%	14 Nov →
nuke	13–4	0.02	20%	14 Nov →
mirage	7–13	-0.04	14%	13 Nov →
dust2	2–13	-0.07	16%	13 Nov →
mirage	7–13	-0.08	23%	12 Nov →
ancient	11–13	0.02	23%	12 Nov →
inferno	7–13	0.00	19%	9 Nov →
overpass	8–13	-0.04	24%	9 Nov →
inferno	5–13	-0.06	22%	8 Nov →
overpass	13–7	-0.02	26%	8 Nov →
nuke	12–12	-0.02	33%	4 Nov →
anubis	13–10	-0.02	30%	4 Nov →