coldeN — CS2 Stats

76561198841187222[U:1:880921494]Steam profile ↗✓ No bans

1,067Tracked matches48%Win rate2020Tracked since

2,133Hours in CS

CSDB Rating4.9 DevelopingHybrid Rifler

WingmanLegendary Eagle Master

Ladder ranks via Leetify

Performance scores

Aim64

Positioning50

Utility26

0–100 skill scores via Leetify.

Recent form

COLD44–55–1Last 10044%Win rateWLLTLLWWLL

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

Player DNA

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

Aim6.4

Aggression5.0

Utility2.6

Positioning5.0

Opening Duels1.4

Clutch4.2

Strong CT-side openerLimited 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.

Your pro match

Plays most like NiKo 80% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

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

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 47% on CT to 24% 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

Aim6.4

Positioning5.0

Utility2.6

Mechanics5.6

Opening Duels2.2

Win Impact4.4

Composite 4.9/10 (Developing), 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 rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time632ms+38ms

first ⅓ avg 594ms → last ⅓ avg 632ms

Headshot accuracy26.8%+6.1%

first ⅓ avg 20.7% → last ⅓ avg 26.8%

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 — dust2 13–4

13–1Biggest win — inferno

6Longest win streak

8–16In matches decided by ≤2 rounds

31Overtime games

Map breakdown

trainBest map · 60% over 5anubisWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	21	10–11	48%	0.02
mirage	B	18	9–9	50%	0.01
dust2	B	15	8–7	53%	0.03
inferno	B	15	7–8	47%	0.01
nuke	D	12	3–9	25%	-0.01
anubis	D	6	1–5	17%	0.01
train	A	5	3–2	60%	0.03
overpass	C	5	2–3	40%	-0.02
vertigo	—	3	1–2	33%	0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

105,948Lifetime kills

1.18K/D · Top 25% of tracked players

3,682Matches

51.0%Match win rate · Top 25% of tracked players

50.0%Headshot % · Top 50% of tracked players

16.1%Shot accuracy · Top 25% of tracked players

15,572MVPs

2,133Hours (in match)

3,814Bombs planted

2,183Bombs defused

Most-used weapons

AK-4741,154

AWP18,590

M4A4 / M4A1-S15,799

P2000 / USP-S5,752

Desert Eagle4,116

Glock-183,774

Knife2,169

SG 5531,909

P2501,533

MP91,484

Lifetime map wins

8,344inferno

7,833dust2

3,235train

2,447nuke

1,106vertigo

320cbble

20lake

13office

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

Faceit stats

Combat

2,440Matches

52%Win rate

1.22Avg K/D

79.7ADR

50%Headshot %

Clutches & streaks

41%1v1 clutch win

26%1v2 clutch win

12Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	247	53%	1.12	16.3
Ancient	196	56%	1.12	17.2
Dust2	127	46%	1.16	16.6
Nuke	103	55%	1.21	16.9
Inferno	80	49%	1.20	16.8
Train	42	45%	1.22	17.9
Anubis	34	29%	1.05	16.0
Overpass	16	69%	1.17	16.6

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.

25.2%Headshot accuracy

31.8%Accuracy (enemy spotted)

35.1%Spray accuracy

75.1%Counter-strafing

10.4°Preaim

632msReaction time

23.6%T opening success

47.3%CT opening success

0.32Enemies flashed / flash

9.5%Flash assists

7.15HE damage / grenade

2.53Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3174 — below the 0.5 mark we flag
Grenade Lineups →
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 23.5701% — below the 40% mark we flag

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.

17% win rate across 6 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
dust2	13–8	0.00	24%	15 Aug →
dust2	11–13	-0.03	12%	5 Jul →
nuke	2–9	-0.10	19%	28 Jun →
train	12–12	0.03	33%	19 Jun →
nuke	5–13	-0.09	39%	10 May →
dust2	11–13	-0.02	19%	10 May →
nuke	13–9	-0.05	19%	3 May →
mirage	13–2	0.12	35%	27 Mar →
ancient	11–13	0.00	17%	25 Mar →
ancient	7–13	-0.00	24%	18 Mar →
overpass	13–9	0.00	34%	22 Feb →
dust2	13–10	-0.00	32%	22 Feb →
nuke	8–13	-0.02	29%	22 Feb →
nuke	10–13	0.02	20%	8 Feb →
nuke	13–16	-0.01	18%	25 Jan →
ancient	13–5	0.09	33%	25 Jan →
inferno	9–3	0.08	43%	11 Jan →
mirage	5–13	-0.07	19%	6 Jan →
mirage	16–13	0.01	22%	3 Jan →
nuke	11–13	0.08	22%	31 Dec →
mirage	4–13	-0.04	24%	31 Dec →
inferno	9–13	-0.01	15%	30 Dec →
dust2	19–17	0.01	21%	23 Dec →
inferno	8–13	0.05	20%	21 Dec →
mirage	13–10	0.01	24%	20 Dec →
nuke	13–11	0.01	29%	15 Dec →
dust2	13–4	0.00	19%	15 Dec →
dust2	13–11	0.03	37%	14 Dec →
mirage	13–8	-0.00	31%	11 Dec →
ancient	13–4	0.09	33%	27 Nov →
ancient	11–13	-0.02	44%	10 Oct →
nuke	2–13	-0.14	23%	10 Oct →
dust2	8–13	-0.04	53%	5 Oct →
ancient	13–11	0.01	29%	4 Oct →
inferno	13–1	0.05	33%	4 Oct →
inferno	13–8	0.13	17%	4 Oct →
dust2	13–15	0.05	32%	11 Sept →
mirage	17–19	0.01	24%	6 Sept →
ancient	3–13	-0.07	19%	29 Aug →
ancient	10–13	0.05	35%	29 Aug →
train	6–13	-0.03	30%	28 Aug →
ancient	13–9	0.01	38%	26 Aug →
inferno	0–9	-0.25	50%	23 Aug →
ancient	13–8	-0.01	33%	6 Aug →
inferno	14–16	0.01	24%	27 Jul →
mirage	3–13	-0.06	6%	27 Jul →
dust2	13–4	0.22	41%	23 Jul →
ancient	13–6	0.09	27%	20 Jul →
mirage	11–13	0.07	28%	20 Jul →
ancient	13–7	0.06	39%	10 Jul →
dust2	13–2	0.14	66%	6 Jul →
nuke	13–8	0.08	38%	6 Jul →
inferno	9–13	-0.05	26%	5 Jul →
inferno	13–7	0.02	17%	15 Jun →
ancient	11–13	-0.01	22%	15 Jun →
train	16–14	0.02	30%	13 Jun →
ancient	13–11	0.02	15%	11 Jun →
train	13–6	0.00	27%	9 Jun →
anubis	13–5	0.08	16%	9 Jun →
mirage	13–11	0.00	19%	7 Jun →
train	16–12	0.10	24%	7 Jun →
anubis	9–13	0.01	18%	6 Jun →
anubis	8–13	0.02	29%	1 Jun →
anubis	7–13	-0.00	28%	24 May →
nuke	10–13	0.02	29%	18 May →
ancient	11–13	-0.00	26%	17 Apr →
mirage	7–13	-0.01	27%	22 Dec →
mirage	8–13	-0.02	13%	23 Aug →
dust2	3–13	-0.03	12%	21 Aug →
dust2	10–13	0.00	18%	15 Aug →
inferno	11–13	0.00	18%	14 Jul →
anubis	8–13	-0.05	38%	13 Jul →
vertigo	5–13	0.01	24%	6 Jul →
anubis	5–13	-0.00	23%	30 Jun →
mirage	13–11	0.05	35%	9 Jun →
nuke	7–13	0.03	15%	20 Apr →
ancient	5–13	0.05	50%	30 Mar →
ancient	16–19	-0.03	14%	29 Aug →
overpass	3–16	0.00	22%	25 Aug →
inferno	5–16	-0.06	23%	25 Aug →
vertigo	14–16	0.05	23%	24 Aug →
mirage	16–9	0.07	44%	24 Aug →
mirage	16–7	0.04	15%	24 Aug →
inferno	19–16	0.07	19%	24 Aug →
ancient	14–16	0.01	21%	24 Aug →
ancient	28–25	0.08	12%	21 Aug →
ancient	14–16	0.02	14%	18 Aug →
dust2	16–8	0.04	20%	18 Aug →
mirage	23–25	-0.01	19%	18 Aug →
inferno	16–9	0.00	19%	17 Aug →
ancient	16–12	0.01	11%	17 Aug →
mirage	15–19	-0.02	17%	17 Aug →
overpass	19–15	0.02	20%	17 Aug →
inferno	8–16	0.04	23%	17 Aug →
dust2	11–16	0.01	31%	16 Aug →
mirage	19–16	0.07	27%	16 Aug →
overpass	13–16	0.01	13%	16 Aug →
inferno	16–7	-0.01	10%	16 Aug →
overpass	8–16	-0.11	14%	15 Aug →
vertigo	16–13	0.00	7%	15 Aug →