✪ Simon — CS2 Stats

GB76561198263053317[U:1:302787589]Steam profile ↗✓ No bans

1,204Tracked matches57%Win rate2022Tracked since

CSDB Rating6.3 SolidSupport

Premier CS Rating19,999Top 50% of 211,494 CSDB-tracked playersPurple band · top ~8.5% of ranked players (population est.)

CSDB Leaderboard#84884 of 258394 tracked

FaceitLevel 7Top 42.3% of ranked FACEIT players

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 Oct 2026 (12 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 19,999 → 19,999

+21Tracked matches · now 1,204

+3.3ppWin rate · 53.3% → 56.7%

Rating over time

Premier CS Rating: 19,999 +160 8 Sept – 17 Oct · 8 days played

19,999Peak Premier in tracked matches

31Days played since 2026-09-08

Premier CS Rating

At peak — 19,999
+881 over 30 days · improving
Next: Pink band at 20,000 — 1 to go
Reached: Purple band · Blue band · Light Blue band
Purple band first seen 2026-09-11
Blue band first seen 2026-09-11

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

Aim64

Positioning56

Utility70

0–100 skill scores via Leetify.

Recent form

STEADY51–49Last 10051%Win rateLLLLLWLWWW

Last 10 vs previous 10: −10pp win rate · +0.02 avg rating · +1.5pp headshot accuracy · −29ms reaction

Win rate −10pp 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 -0.02
Avg headshot accuracy 16%
Avg reaction 553ms

Last 10

4–6 · 40% win rate
Avg rating 0.00
Avg headshot accuracy 16%
Avg reaction 576ms

Last 20

9–11 · 45% win rate
Avg rating -0.00
Avg headshot accuracy 15%
Avg reaction 590ms

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: Support — Utility contribution stands above the rest of this profile (+2.7 against its own average).

Aim6.4

Utility7.0

Positioning5.6

Opening Duels2.6

Clutch2.2

Strong CT-side opener

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 iM 77% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: 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. 614ms 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

Positioning5.6

Utility7.0

Mechanics7.0

Opening Duels4.2

Win Impact7.2

Composite 6.3/10 (Solid), 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 rating0.00+0.02

first ⅓ avg -0.02 → last ⅓ avg 0.00

Reaction time618ms−32ms

first ⅓ avg 650ms → last ⅓ avg 618ms

Headshot accuracy14.9%+1.8%

first ⅓ avg 13.1% → last ⅓ avg 14.9%

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

0.20Best match rating · 5–1 · rush_001, 11 Oct →

50%Best headshot accuracy · 6–8 · rush_001, 11 Oct →

328msFastest reaction time · 0–4 · rush_001, 11 Oct →

13–1Biggest win · cache, 9 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak

L5Current streak

8–12In matches decided by ≤2 rounds

15Overtime games

Map breakdown

nukeBest map · 71% over 7infernoWeakest map · 38% over 8

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	25	11–14	44%	-0.01
ancient	A	16	10–6	63%	0.01
cache	A	15	9–6	60%	-0.01
anubis	B	11	5–6	45%	-0.01
rush_001	C	10	4–6	40%	-0.03
inferno	C	8	3–5	38%	-0.03
dust2	B	8	4–4	50%	-0.00
nuke	S	7	5–2	71%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

186Matches

56%Win rate

1.11Avg K/D

76.2ADR

37%Headshot %

Clutches & streaks

31%1v1 clutch win

20%1v2 clutch win

11Longest win streak

Recent Faceit resultsLLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	51	57%	1.04	14.2
Ancient	20	65%	1.17	18.1
Dust2	19	37%	0.97	14.3
Inferno	19	47%	0.92	14.3
Cache	14	79%	1.14	13.3
Nuke	13	46%	1.09	15.8
Anubis	11	45%	0.94	15.6
Train	4	100%	1.61	18.8

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.

14.6%Headshot accuracy

36.5%Accuracy (enemy spotted)

39.4%Spray accuracy

81.5%Counter-strafing

11.4°Preaim

614msReaction time

43.3%T opening success

50.0%CT opening success

0.61Enemies flashed / flash

11.2%Flash assists

8.62HE damage / grenade

13.70Flashes / 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 14.6381% — below the 15% mark we flag
Aim Training →

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 8 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
ancient	2–13	-0.02	19%	27 Oct →
mirage	13–16	-0.01	20%	27 Oct →
cache	6–13	-0.00	17%	27 Oct →
ancient	16–19	-0.00	10%	26 Oct →
mirage	7–13	-0.06	13%	26 Oct →
anubis	13–2	-0.00	18%	26 Oct →
anubis	10–13	-0.01	16%	23 Oct →
mirage	13–8	0.02	15%	23 Oct →
cache	13–6	0.07	18%	23 Oct →
mirage	13–9	0.06	13%	23 Oct →
mirage	8–13	0.03	18%	21 Oct →
inferno	8–13	-0.07	6%	20 Oct →
ancient	13–9	0.01	14%	20 Oct →
cache	16–13	-0.00	23%	20 Oct →
dust2	11–13	-0.06	11%	19 Oct →
mirage	22–20	-0.03	15%	19 Oct →
ancient	13–7	0.02	17%	18 Oct →
mirage	11–13	-0.06	16%	18 Oct →
anubis	13–11	0.04	10%	14 Oct →
ancient	9–13	0.00	12%	14 Oct →
dust2	13–3	0.11	16%	14 Oct →
cache	13–4	0.04	10%	14 Oct →
ancient	13–4	-0.01	22%	13 Oct →
inferno	13–6	0.01	15%	13 Oct →
dust2	6–1	0.04	21%	13 Oct →
inferno	8–13	0.05	9%	13 Oct →
mirage	13–7	-0.02	14%	12 Oct →
cache	13–3	0.04	17%	12 Oct →
nuke	13–6	0.04	10%	12 Oct →
nuke	5–13	-0.06	11%	12 Oct →
ancient	13–8	0.03	8%	12 Oct →
anubis	13–6	0.05	13%	12 Oct →
rush_001	2–6	-0.11	25%	11 Oct →
rush_001	0–4	-0.41	25%	11 Oct →
rush_001	5–1	0.20	23%	11 Oct →
rush_001	8–6	0.03	33%	11 Oct →
rush_001	8–5	0.13	8%	11 Oct →
rush_001	8–5	0.15	18%	11 Oct →
rush_001	0–4	-0.20	0%	11 Oct →
rush_001	7–8	-0.02	0%	11 Oct →
rush_001	1–5	-0.03	29%	11 Oct →
rush_001	6–8	-0.04	50%	11 Oct →
ancient	11–13	0.07	11%	11 Oct →
anubis	8–13	-0.06	2%	11 Oct →
cache	4–13	-0.04	14%	11 Oct →
inferno	13–11	-0.02	12%	11 Oct →
cache	5–13	-0.04	25%	10 Oct →
ancient	13–8	0.06	5%	10 Oct →
mirage	11–13	-0.02	12%	10 Oct →
ancient	1–13	-0.11	11%	10 Oct →
anubis	10–13	-0.02	4%	7 Oct →
mirage	13–4	0.06	6%	7 Oct →
nuke	11–13	-0.03	4%	7 Oct →
ancient	16–14	0.02	6%	6 Oct →
mirage	17–19	0.01	15%	6 Oct →
inferno	13–16	0.02	16%	6 Oct →
mirage	7–13	-0.02	11%	5 Oct →
cache	10–13	0.01	11%	5 Oct →
anubis	16–13	0.07	15%	4 Oct →
mirage	13–2	0.02	8%	4 Oct →
cache	13–10	0.00	14%	2 Oct →
ancient	16–14	0.02	6%	2 Oct →
mirage	13–8	-0.01	7%	2 Oct →
anubis	18–22	0.00	12%	1 Oct →
inferno	11–13	-0.05	4%	30 Sept →
anubis	14–16	-0.05	13%	30 Sept →
mirage	13–7	-0.00	20%	30 Sept →
dust2	10–13	-0.03	17%	30 Sept →
mirage	13–7	0.05	19%	29 Sept →
cache	3–13	-0.05	11%	29 Sept →
anubis	13–6	-0.03	13%	29 Sept →
cache	13–5	-0.02	23%	27 Sept →
inferno	1–9	-0.19	29%	27 Sept →
anubis	3–13	-0.03	13%	27 Sept →
ancient	13–6	-0.01	8%	27 Sept →
dust2	9–13	0.03	7%	27 Sept →
cache	16–14	-0.05	8%	26 Sept →
dust2	13–10	-0.04	11%	26 Sept →
mirage	8–13	-0.06	10%	25 Sept →
ancient	14–16	-0.03	16%	15 Sept →
mirage	13–7	0.02	15%	14 Sept →
nuke	13–9	0.03	6%	13 Sept →
cache	13–7	-0.09	6%	13 Sept →
mirage	6–13	-0.03	10%	13 Sept →
mirage	11–13	0.04	13%	13 Sept →
dust2	10–13	-0.04	23%	12 Sept →
mirage	5–13	-0.04	9%	12 Sept →
nuke	13–9	0.06	15%	12 Sept →
mirage	13–16	-0.03	7%	11 Sept →
nuke	13–2	0.05	10%	11 Sept →
ancient	16–14	-0.00	13%	10 Sept →
ancient	13–2	0.07	19%	10 Sept →
mirage	6–13	-0.09	9%	10 Sept →
nuke	13–9	-0.02	4%	10 Sept →
cache	6–13	-0.07	9%	10 Sept →
mirage	9–13	-0.01	10%	10 Sept →
inferno	13–10	0.02	9%	9 Sept →
cache	13–1	0.05	30%	9 Sept →
dust2	13–7	-0.03	21%	9 Sept →
mirage	13–10	-0.07	8%	8 Sept →