Shion — CS2 Stats

76561198803976078[U:1:843710350]

1,386Tracked matches30%Win rate2022Tracked since

2,109Hours in CS45Hrs last 2 wks

CSDB Rating3.9 Learning

Premier CS Rating15,664Purple band · top ~25.8% of ranked players (population est.)

CSDB Leaderboard#19843 of 33199 tracked

FaceitLevel 5 · 1,032 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=918), 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 5 median	Level 6 median	vs Level 6
Headshot rate	27.2%	44.2%	44.9%	17.7% short
Shot accuracy	1.5%	11.2%	11.8%	10.4% short
Kill/death ratio	0.96	1.04	1.04	0.08 short
Match win rate	48.6%	45.3%	45.3%	above

This profile matches the typical Level 6 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim57

Positioning41

Utility54

0–100 skill scores via Leetify.

Recent form

COLD48–47–5Last 10048%Win rateLTTLTLWLLL

Last 10 vs previous 10: -30pp win rate · +0.01 avg rating

Player DNA

Aim5.7

Aggression4.3

Utility5.4

Positioning4.1

Opening Duels0.0

Clutch2.2

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 82% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

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

Areas to improve

Counter-strafing. Only 66% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.7

Positioning4.1

Utility5.4

Mechanics3.6

Opening Duels0.6

Win Impact0.0

Composite 3.9/10 (Learning), 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-0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg -0.00

Reaction time543ms−68ms

first ⅓ avg 611ms → last ⅓ avg 543ms

Headshot accuracy11.8%−0.3%

first ⅓ avg 12.1% → last ⅓ avg 11.8%

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

0.16Best rating — dust2 13–6

13–0Biggest win — cache

7Longest win streak

11–9In matches decided by ≤2 rounds

6Overtime games

Map breakdown

cacheBest map · 67% over 9infernoWeakest map · 33% over 12

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	21	9–12	43%	-0.00
mirage	A	21	12–9	57%	0.02
ancient	B	15	7–8	47%	0.01
inferno	D	12	4–8	33%	-0.00
nuke	C	11	4–7	36%	-0.02
cache	S	9	6–3	67%	0.03
anubis	A	9	5–4	56%	0.01
italy	—	1	0–1	0%	0.00
vertigo	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

41,820Lifetime kills

0.96K/D

2,982Matches

48.6%Match win rate · Top 25% of Level 5 players

27.2%Headshot %

1.5%Shot accuracy

5,769MVPs

1,122Hours (in match)

5,127Bombs planted

736Bombs defused

Most-used weapons

AWP8,987

M4A4 / M4A1-S7,799

AK-477,561

MP92,518

MAC-102,432

P2000 / USP-S1,742

Galil AR1,469

Glock-18975

Dual Berettas973

Tec-9956

Lifetime map wins

5,264dust2

4,481nuke

4,405inferno

1,357train

523vertigo

117office

32cbble

26lake

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

Faceit stats

Combat

201Matches

51%Win rate

1.06Avg K/D

73.1ADR

27%Headshot %

Clutches & streaks

31%1v1 clutch win

25%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	50	50%	1.19	13.7
Dust2	38	61%	1.00	13.7
Ancient	33	67%	1.17	15.6
Inferno	32	34%	1.00	13.7
Nuke	25	52%	1.00	15.6
Anubis	14	36%	0.90	13.1
Cache	4	25%	0.65	9.3
Train	2	50%	0.84	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.

11.7%Headshot accuracy

34.9%Accuracy (enemy spotted)

40.9%Spray accuracy

66.1%Counter-strafing

10.5°Preaim

537msReaction time

25.6%T opening success

34.6%CT opening success

0.54Enemies flashed / flash

7.0%Flash assists

9.97HE damage / grenade

8.02Flashes / 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 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 11.7264% — below the 15% 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 25.5981% — 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.

33% win rate across 12 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
nuke	8–13	0.04	7%	28 Aug →
ancient	15–15	-0.01	3%	28 Aug →
dust2	15–15	0.02	9%	28 Aug →
mirage	3–13	0.03	11%	27 Aug →
mirage	15–15	0.01	16%	27 Aug →
dust2	9–13	0.01	29%	26 Aug →
cache	13–0	0.07	6%	26 Aug →
mirage	5–13	-0.01	15%	26 Aug →
nuke	6–13	-0.01	22%	25 Aug →
dust2	5–13	-0.04	19%	25 Aug →
inferno	13–9	0.05	10%	25 Aug →
mirage	13–6	0.11	31%	25 Aug →
ancient	9–13	0.01	10%	25 Aug →
ancient	12–16	-0.07	4%	23 Aug →
inferno	13–10	-0.02	20%	22 Aug →
nuke	11–13	-0.04	18%	22 Aug →
dust2	9–13	-0.01	8%	22 Aug →
mirage	7–13	0.01	20%	21 Aug →
mirage	11–13	-0.10	5%	20 Aug →
mirage	13–0	0.05	15%	20 Aug →
anubis	4–13	-0.06	14%	20 Aug →
nuke	13–11	-0.02	7%	20 Aug →
italy	3–5	0.00	9%	18 Aug →
anubis	4–13	-0.07	5%	18 Aug →
nuke	7–13	-0.03	7%	18 Aug →
dust2	7–13	-0.11	9%	17 Aug →
dust2	13–5	-0.02	15%	16 Aug →
inferno	8–13	-0.04	5%	16 Aug →
nuke	10–13	-0.03	6%	16 Aug →
dust2	13–9	0.02	5%	16 Aug →
mirage	11–13	0.10	14%	15 Aug →
anubis	13–8	0.03	7%	15 Aug →
mirage	13–5	0.04	8%	15 Aug →
inferno	13–11	-0.04	5%	15 Aug →
nuke	13–10	0.01	7%	15 Aug →
anubis	13–9	-0.02	14%	15 Aug →
ancient	13–5	0.13	10%	15 Aug →
cache	13–4	0.09	0%	14 Aug →
inferno	10–13	-0.00	9%	14 Aug →
inferno	9–13	-0.02	9%	14 Aug →
dust2	13–8	0.04	16%	14 Aug →
cache	6–13	0.12	11%	14 Aug →
dust2	4–13	-0.02	0%	14 Aug →
anubis	13–6	0.11	11%	13 Aug →
mirage	13–5	-0.08	10%	12 Aug →
mirage	13–7	-0.00	11%	12 Aug →
mirage	6–13	-0.05	9%	11 Aug →
mirage	13–11	0.09	14%	11 Aug →
dust2	4–13	-0.04	4%	11 Aug →
ancient	13–10	0.07	12%	9 Aug →
cache	2–13	-0.03	10%	9 Aug →
mirage	9–13	-0.05	12%	8 Aug →
ancient	5–12	0.03	20%	7 Aug →
dust2	9–13	0.05	8%	7 Aug →
ancient	13–8	0.04	6%	6 Aug →
ancient	5–13	-0.03	13%	6 Aug →
nuke	9–13	0.02	11%	5 Aug →
inferno	12–12	0.02	13%	5 Aug →
nuke	13–8	-0.08	17%	2 Aug →
anubis	13–6	0.11	36%	2 Aug →
cache	4–13	-0.06	4%	2 Aug →
mirage	13–11	-0.02	8%	2 Aug →
ancient	11–13	0.00	14%	1 Aug →
inferno	11–13	0.02	4%	1 Aug →
cache	13–8	-0.02	23%	1 Aug →
inferno	10–13	-0.02	11%	1 Aug →
anubis	13–10	-0.02	18%	1 Aug →
inferno	5–13	-0.03	20%	1 Aug →
ancient	13–11	0.04	13%	1 Aug →
dust2	3–13	-0.04	6%	31 Jul →
dust2	13–11	0.05	2%	30 Jul →
ancient	13–11	-0.05	9%	29 Jul →
dust2	13–6	-0.03	7%	29 Jul →
vertigo	13–6	-0.01	23%	29 Jul →
dust2	13–10	0.02	9%	28 Jul →
inferno	16–14	0.02	18%	28 Jul →
mirage	2–8	-0.01	4%	27 Jul →
ancient	11–13	0.00	17%	27 Jul →
ancient	13–3	-0.01	5%	27 Jul →
anubis	6–13	-0.04	8%	26 Jul →
cache	13–7	0.01	3%	26 Jul →
inferno	6–13	-0.01	4%	26 Jul →
dust2	11–13	-0.01	9%	26 Jul →
mirage	13–9	-0.01	10%	26 Jul →
mirage	13–8	0.04	15%	25 Jul →
dust2	13–6	0.16	26%	25 Jul →
mirage	13–7	0.12	19%	25 Jul →
ancient	9–13	-0.00	22%	25 Jul →
anubis	12–12	0.05	6%	25 Jul →
dust2	13–4	-0.03	22%	25 Jul →
dust2	10–13	-0.07	26%	24 Jul →
cache	16–13	0.03	11%	24 Jul →
dust2	13–10	0.02	4%	24 Jul →
mirage	13–11	0.07	11%	24 Jul →
mirage	13–11	0.01	10%	23 Jul →
nuke	13–10	0.01	6%	23 Jul →
cache	13–8	0.03	10%	23 Jul →
dust2	1–13	-0.08	10%	23 Jul →
nuke	11–13	-0.05	12%	23 Jul →
ancient	13–11	0.04	20%	23 Jul →