Himokoljonen — CS2 Stats

76561198256798871[U:1:296533143]Steam profile ↗✓ No bans

1,009Tracked matches36%Win rate2020Tracked since

CSDB Rating3.1 Learning

Premier CS Rating3,032Grey band · top ~87.1% of ranked players (population est.)

CSDB Leaderboard#44058 of 56539 tracked

WingmanGold Nova I

Ladder ranks via Leetify

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Performance scores

Aim33

Positioning36

Utility58

0–100 skill scores via Leetify.

Recent form

COLD27–69–4Last 10027%Win rateLLLWLWLWLL

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating

Player DNA

Aim3.3

Aggression2.6

Utility5.8

Positioning3.6

Opening Duels0.0

Clutch0.4

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 70% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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

Areas to improve

Reaction time. 738ms 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

Aim3.3

Positioning3.6

Utility5.8

Mechanics5.3

Opening Duels0.0

Win Impact0.2

Composite 3.1/10 (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-0.07−0.03

first ⅓ avg -0.04 → last ⅓ avg -0.07

Reaction time734ms−20ms

first ⅓ avg 754ms → last ⅓ avg 734ms

Headshot accuracy17.9%+1.6%

first ⅓ avg 16.3% → last ⅓ avg 17.9%

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.

Highlights

0.09Best rating — overpass 9–13

13–2Biggest win — nuke

3Longest win streak

L3Current streak

2–5In matches decided by ≤2 rounds

12Overtime games

Map breakdown

nukeBest map · 58% over 12trainWeakest map · 13% over 8

Map	Grade	Played	Record	Win rate	Avg rating
inferno	D	25	8–17	32%	-0.06
dust2	D	24	6–18	25%	-0.03
nuke	A	12	7–5	58%	-0.04
train	D	8	1–7	13%	-0.07
mirage	D	7	1–6	14%	-0.06
ancient	D	7	2–5	29%	-0.03
overpass	D	7	1–6	14%	-0.04
cache	D	6	1–5	17%	-0.06
anubis	—	4	0–4	0%	-0.09

Across the last 100 tracked matches.

Faceit stats

Combat

29Matches

34%Win rate

0.54Avg K/D

61.4ADR

31%Headshot %

Clutches & streaks

22%1v1 clutch win

27%1v2 clutch win

2Longest win streak

Recent Faceit resultsWLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Anubis	7	43%	0.57	10.9
Dust2	4	50%	0.79	11.5
Inferno	2	100%	0.98	14.0
Mirage	2	100%	0.87	12.5
Nuke	2	50%	0.70	12.0
Ancient	1	0%	0.65	11.0

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.

16.0%Headshot accuracy

28.4%Accuracy (enemy spotted)

35.8%Spray accuracy

73.7%Counter-strafing

11.3°Preaim

738msReaction time

17.3%T opening success

29.1%CT opening success

0.63Enemies flashed / flash

7.9%Flash assists

8.94HE damage / grenade

10.24Flashes / 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.

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 737.5289ms — above the 700ms mark we flag
Aim Training →
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 17.3361% — below the 40% mark we flag

Spend your practice time on Train

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

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
cache	8–13	-0.04	17%	22 Aug →
inferno	6–9	-0.08	5%	17 Aug →
mirage	3–13	-0.17	25%	17 Aug →
nuke	13–2	-0.05	29%	17 Aug →
inferno	6–9	-0.09	25%	17 Aug →
nuke	13–9	-0.07	14%	17 Aug →
inferno	10–13	-0.07	12%	15 Aug →
mirage	13–10	0.01	13%	15 Aug →
nuke	6–13	-0.06	25%	15 Aug →
dust2	7–13	-0.03	21%	15 Aug →
inferno	2–13	-0.07	12%	15 Aug →
mirage	9–13	-0.07	13%	15 Aug →
ancient	13–6	-0.06	20%	15 Aug →
train	12–12	-0.07	30%	15 Aug →
inferno	2–9	-0.20	42%	15 Aug →
inferno	9–2	-0.06	21%	15 Aug →
inferno	5–9	-0.08	15%	15 Aug →
inferno	2–9	-0.07	19%	15 Aug →
nuke	2–13	-0.07	47%	14 Aug →
train	1–13	-0.12	11%	14 Aug →
cache	8–13	-0.10	18%	14 Aug →
ancient	15–15	-0.06	19%	14 Aug →
cache	8–13	-0.03	11%	29 Jul →
inferno	13–5	-0.11	14%	26 Jul →
dust2	13–3	0.04	14%	26 Jul →
cache	13–5	-0.06	23%	26 Jul →
inferno	7–13	-0.10	4%	26 Jul →
dust2	1–13	-0.08	21%	26 Jul →
train	13–6	-0.05	14%	26 Jul →
dust2	10–13	-0.09	13%	25 Jul →
cache	11–13	-0.08	3%	24 Jul →
inferno	10–13	0.00	13%	24 Jul →
nuke	16–13	-0.05	11%	24 Jul →
inferno	11–2	0.04	0%	24 Jul →
dust2	13–16	0.04	15%	24 Jul →
cache	7–13	-0.08	11%	24 Jul →
nuke	3–13	-0.06	20%	24 Jul →
inferno	1–9	-0.11	12%	23 Jul →
dust2	7–13	-0.02	23%	18 Jul →
nuke	13–10	0.01	13%	31 May →
anubis	14–16	-0.05	18%	31 May →
overpass	8–13	-0.02	3%	18 Apr →
dust2	13–11	0.06	12%	18 Apr →
mirage	2–13	-0.09	11%	18 Apr →
inferno	13–5	0.01	11%	18 Apr →
dust2	6–13	0.03	13%	18 Apr →
nuke	13–10	-0.02	17%	18 Apr →
nuke	13–2	0.03	18%	18 Apr →
inferno	13–9	-0.01	11%	18 Apr →
inferno	8–13	-0.06	22%	18 Apr →
dust2	8–13	-0.07	10%	18 Apr →
dust2	7–13	0.00	15%	17 Apr →
overpass	16–14	-0.04	16%	16 Apr →
inferno	16–13	-0.07	13%	16 Apr →
overpass	5–13	-0.02	21%	16 Apr →
dust2	13–5	-0.02	13%	16 Apr →
nuke	1–13	-0.07	10%	16 Apr →
train	10–13	-0.06	18%	15 Apr →
mirage	5–13	-0.06	20%	15 Apr →
ancient	13–5	-0.00	18%	15 Apr →
inferno	7–13	-0.09	13%	15 Apr →
anubis	2–13	-0.12	50%	15 Apr →
overpass	2–13	-0.01	27%	11 Apr →
inferno	1–13	-0.06	12%	11 Apr →
inferno	7–13	-0.09	23%	11 Apr →
train	8–13	-0.04	11%	11 Apr →
inferno	9–13	-0.01	23%	31 Mar →
ancient	13–16	-0.03	7%	26 Mar →
overpass	9–13	-0.10	14%	26 Mar →
ancient	5–13	0.00	13%	25 Mar →
inferno	16–12	-0.00	18%	25 Mar →
inferno	7–13	-0.01	13%	25 Mar →
dust2	13–6	0.00	20%	25 Mar →
dust2	5–13	-0.01	35%	24 Mar →
ancient	15–15	0.00	28%	24 Mar →
dust2	9–13	0.01	16%	23 Mar →
mirage	14–16	-0.00	18%	21 Mar →
dust2	13–3	-0.01	24%	21 Mar →
overpass	7–13	-0.19	0%	20 Mar →
dust2	6–13	-0.02	13%	20 Mar →
inferno	6–13	-0.05	20%	14 Mar →
dust2	15–15	-0.07	5%	14 Mar →
dust2	13–3	-0.04	10%	14 Mar →
dust2	11–13	-0.04	13%	8 Mar →
nuke	10–13	-0.02	10%	8 Mar →
anubis	8–13	-0.06	33%	17 Feb →
train	5–9	-0.08	38%	16 Feb →
overpass	9–13	0.09	12%	15 Feb →
inferno	13–5	-0.01	17%	15 Feb →
dust2	4–13	-0.09	5%	10 Feb →
anubis	2–13	-0.11	25%	9 Feb →
dust2	8–13	-0.05	15%	29 Jan →
ancient	6–13	-0.03	6%	29 Jan →
dust2	2–13	-0.06	27%	29 Jan →
nuke	13–9	-0.03	12%	29 Jan →
train	7–13	-0.12	9%	26 Jan →
train	9–13	-0.00	13%	23 Jan →
dust2	11–13	-0.08	13%	23 Jan →
mirage	9–13	-0.05	32%	23 Jan →
dust2	13–16	-0.01	6%	23 Jan →