Spaysu — CS2 Stats

CR76561198132033693[U:1:171767965]Steam profile ↗✓ No bans

779Tracked matches52%Win rate2020Tracked since

CSDB Rating5.5 SolidAll-Rounder

Premier CS Rating15,903Purple band · top ~24.8% of ranked players (population est.)

FaceitLevel 1Top 100.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim54

Positioning58

Utility65

0–100 skill scores via Leetify.

Recent form

STEADY49–46–5Last 10049%Win rateWLWLLWWLWL

Last 10 vs previous 10: 0pp win rate · +0.00 avg rating · −0.4pp headshot accuracy · +44ms reaction

Win rate 0pp 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

2–3 · 40% win rate
Avg rating 0.00
Avg headshot accuracy 13%
Avg reaction 520ms

Last 10

5–5 · 50% win rate
Avg rating 0.01
Avg headshot accuracy 15%
Avg reaction 542ms

Last 20

10–10 · 50% win rate
Avg rating 0.01
Avg headshot accuracy 15%
Avg reaction 520ms

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.

Aim5.4

Utility6.5

Positioning5.8

Opening Duels4.9

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 jL 76% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim5.4

Positioning5.8

Utility6.5

Mechanics4.7

Opening Duels5.0

Win Impact5.6

Composite 5.5/10 (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 rating-0.00+0.01

first ⅓ avg -0.01 → last ⅓ avg -0.00

Reaction time530ms−12ms

first ⅓ avg 542ms → last ⅓ avg 530ms

Headshot accuracy15.0%−0.8%

first ⅓ avg 15.8% → last ⅓ avg 15.0%

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

0.12Best match rating · 13–11 · inferno, 28 Sept →

35%Best headshot accuracy · 7–13 · dust2, 7 Nov →

391msFastest reaction time · 8–13 · inferno, 26 Sept →

13–1Biggest win · mirage, 14 Nov →

Across the last 100 tracked matches.

Highlights

7Longest win streak

11–11In matches decided by ≤2 rounds

15Overtime games

Map breakdown

infernoBest map · 67% over 24ancientWeakest map · 20% over 10

Map	Grade	Played	Record	Win rate	Avg rating
inferno	S	24	16–8	67%	-0.00
cache	B	21	11–10	52%	-0.01
mirage	A	16	9–7	56%	0.01
dust2	C	13	5–8	38%	-0.02
ancient	D	10	2–8	20%	-0.01
nuke	C	10	4–6	40%	-0.01
anubis	D	6	2–4	33%	-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

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

32.3%Accuracy (enemy spotted)

33.3%Spray accuracy

71.2%Counter-strafing

10.7°Preaim

535msReaction time

45.1%T opening success

55.0%CT opening success

0.63Enemies flashed / flash

5.8%Flash assists

12.87HE damage / grenade

7.70Flashes / 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 14.5587% — below the 15% mark we flag
Aim Training →

Spend your practice time on Ancient

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

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	13–1	0.05	10%	14 Nov →
cache	12–16	0.03	18%	14 Nov →
cache	13–8	-0.05	7%	13 Nov →
cache	2–13	0.01	11%	13 Nov →
ancient	5–13	-0.03	18%	13 Nov →
mirage	13–8	0.02	12%	12 Nov →
ancient	16–13	0.02	8%	11 Nov →
dust2	7–13	-0.01	35%	7 Nov →
mirage	13–9	0.04	17%	7 Nov →
cache	8–13	-0.00	12%	7 Nov →
mirage	6–4	-0.05	33%	7 Nov →
mirage	13–4	0.06	13%	4 Nov →
ancient	11–13	0.03	12%	4 Nov →
mirage	3–13	0.05	10%	1 Nov →
inferno	13–5	0.01	15%	1 Nov →
nuke	16–14	-0.01	12%	1 Nov →
cache	13–8	0.03	11%	31 Oct →
anubis	8–13	-0.04	17%	31 Oct →
inferno	11–13	0.01	10%	31 Oct →
inferno	4–13	-0.04	20%	31 Oct →
dust2	5–13	0.00	18%	31 Oct →
dust2	13–4	-0.02	12%	31 Oct →
cache	13–2	-0.02	23%	25 Oct →
dust2	13–4	-0.00	6%	25 Oct →
nuke	5–13	-0.07	14%	25 Oct →
dust2	16–13	-0.06	13%	24 Oct →
ancient	9–13	0.02	21%	24 Oct →
anubis	15–15	0.00	17%	23 Oct →
dust2	11–13	-0.01	11%	23 Oct →
nuke	13–3	0.01	15%	23 Oct →
mirage	16–12	-0.03	12%	22 Oct →
inferno	13–6	0.05	18%	22 Oct →
inferno	13–3	0.01	15%	22 Oct →
inferno	13–9	-0.04	21%	21 Oct →
anubis	13–11	-0.02	27%	21 Oct →
ancient	13–2	-0.05	6%	21 Oct →
inferno	2–13	-0.02	17%	20 Oct →
cache	14–16	0.06	15%	20 Oct →
cache	13–5	0.01	19%	18 Oct →
inferno	13–11	0.01	12%	18 Oct →
nuke	13–4	0.05	20%	17 Oct →
ancient	8–13	-0.01	21%	16 Oct →
dust2	10–13	-0.03	26%	16 Oct →
inferno	15–15	-0.03	14%	16 Oct →
mirage	4–13	0.04	18%	16 Oct →
inferno	13–8	-0.06	13%	16 Oct →
dust2	9–13	0.00	23%	16 Oct →
mirage	13–4	0.02	25%	16 Oct →
mirage	13–11	0.09	9%	12 Oct →
nuke	1–13	-0.08	14%	12 Oct →
nuke	9–13	-0.03	6%	12 Oct →
cache	15–15	-0.06	24%	10 Oct →
anubis	13–7	0.03	12%	10 Oct →
cache	13–7	0.01	14%	10 Oct →
cache	15–15	-0.02	14%	10 Oct →
cache	13–4	-0.02	21%	10 Oct →
inferno	13–9	0.01	22%	10 Oct →
cache	11–13	-0.05	12%	5 Oct →
mirage	11–13	0.07	16%	3 Oct →
cache	11–13	-0.04	17%	3 Oct →
mirage	15–15	-0.04	11%	3 Oct →
nuke	7–13	0.04	20%	2 Oct →
inferno	1–13	-0.05	4%	2 Oct →
inferno	16–14	0.06	19%	1 Oct →
mirage	5–13	-0.05	14%	1 Oct →
cache	13–11	-0.05	15%	30 Sept →
inferno	13–8	-0.01	14%	30 Sept →
dust2	11–13	-0.02	14%	29 Sept →
inferno	13–11	0.12	13%	28 Sept →
cache	13–7	-0.01	13%	28 Sept →
cache	13–5	-0.01	18%	27 Sept →
ancient	7–13	-0.02	14%	27 Sept →
nuke	5–13	0.01	11%	27 Sept →
cache	10–0	-0.00	22%	27 Sept →
anubis	7–13	-0.10	20%	26 Sept →
inferno	8–13	-0.06	29%	26 Sept →
nuke	13–10	-0.02	7%	26 Sept →
inferno	8–13	-0.08	8%	24 Sept →
dust2	10–13	-0.03	6%	24 Sept →
inferno	7–13	-0.03	16%	19 Sept →
inferno	13–6	-0.03	17%	19 Sept →
inferno	13–11	0.00	20%	19 Sept →
mirage	14–16	-0.01	22%	19 Sept →
cache	13–16	-0.05	19%	19 Sept →
anubis	3–13	-0.02	15%	19 Sept →
dust2	14–16	-0.01	15%	18 Sept →
ancient	9–13	0.01	17%	16 Sept →
nuke	7–13	0.01	21%	16 Sept →
mirage	7–13	-0.05	9%	16 Sept →
inferno	13–10	0.03	14%	16 Sept →
inferno	13–10	-0.05	9%	16 Sept →
ancient	8–13	0.00	10%	6 Sept →
mirage	13–9	0.00	25%	6 Sept →
dust2	13–11	-0.04	10%	6 Sept →
inferno	13–9	0.08	23%	3 Sept →
ancient	4–13	-0.05	15%	3 Sept →
cache	11–13	0.01	21%	3 Sept →
inferno	13–3	0.11	23%	3 Sept →
cache	13–11	-0.03	15%	3 Sept →
dust2	13–8	0.01	13%	3 Sept →