Jay — CS2 Stats

76561198102034230[U:1:141768502]✓ No bans

102Tracked matches68%Win rate2026Tracked since

CSDB Rating4.1 Developing

Ladder ranks via Leetify

Performance scores

Aim29

Positioning43

Utility53

0–100 skill scores via Leetify.

Recent form

STEADY52–43–5Last 10052%Win rateLLWWWWTWWL

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

Player DNA

Aim2.9

Aggression5.2

Utility5.3

Positioning4.3

Opening Duels0.8

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 78% 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

Reaction time. 637ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

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

Aim2.9

Positioning4.3

Utility5.3

Mechanics3.5

Opening Duels0.9

Win Impact10.0

Composite 4.1/10 (Developing), 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 time639ms+2ms

first ⅓ avg 636ms → last ⅓ avg 639ms

Headshot accuracy13.6%+0.9%

first ⅓ avg 12.7% → last ⅓ avg 13.6%

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

0.15Best rating — cache 13–3

13–1Biggest win — nuke

5Longest win streak

L2Current streak

12–8In matches decided by ≤2 rounds

10Overtime games

Map breakdown

ancientBest map · 80% over 5infernoWeakest map · 48% over 23

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	23	11–12	48%	-0.01
dust2	A	22	12–10	55%	0.01
mirage	B	21	10–11	48%	-0.01
nuke	B	12	6–6	50%	0.01
anubis	A	9	5–4	56%	0.01
ancient	S	5	4–1	80%	-0.01
cache	—	4	2–2	50%	0.02
overpass	—	2	1–1	50%	0.01
train	—	1	1–0	100%	0.01
vertigo	—	1	0–1	0%	-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (48% over 23). Start with the 6 essential Inferno 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.

13.7%Headshot accuracy

31.6%Accuracy (enemy spotted)

34.9%Spray accuracy

65.6%Counter-strafing

13.7°Preaim

637msReaction time

29.0%T opening success

37.4%CT opening success

0.44Enemies flashed / flash

1.8%Flash assists

9.76HE damage / grenade

7.78Flashes / 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.

Advanced Mechanics
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.7135° — above the 12° mark we flag
Aim Training →
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 13.6574% — below the 15% mark we flag
Aim Training →
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 0.4393 — below the 0.5 mark we flag
Grenade Lineups →

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.

48% win rate across 23 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
inferno	5–13	-0.05	18%	21 Aug →
anubis	5–13	-0.01	14%	21 Aug →
anubis	13–11	-0.00	21%	21 Aug →
inferno	13–10	-0.03	26%	9 Aug →
dust2	13–8	0.03	13%	19 Jul →
nuke	13–11	0.02	11%	19 Jul →
cache	15–15	-0.04	13%	16 Jul →
ancient	13–6	-0.01	11%	27 Jun →
mirage	16–14	-0.01	8%	27 Jun →
dust2	5–13	0.00	8%	27 Jun →
dust2	10–13	-0.02	11%	27 Jun →
dust2	13–11	-0.00	17%	14 Jun →
inferno	6–13	-0.06	11%	14 Jun →
dust2	13–4	-0.00	26%	6 Jun →
mirage	11–13	0.03	21%	4 Jun →
ancient	13–10	-0.06	4%	31 May →
mirage	13–7	-0.06	11%	31 May →
inferno	13–6	0.09	12%	27 May →
inferno	13–8	0.02	17%	24 May →
dust2	13–10	0.05	11%	24 May →
ancient	8–13	-0.02	12%	23 May →
nuke	5–13	-0.04	9%	4 May →
cache	13–9	-0.00	17%	4 May →
anubis	13–5	0.04	14%	3 May →
cache	13–3	0.15	16%	3 May →
cache	11–13	-0.02	15%	3 May →
overpass	13–10	0.04	8%	27 Apr →
inferno	15–15	-0.01	16%	26 Apr →
inferno	16–12	-0.01	14%	26 Apr →
mirage	13–8	-0.04	10%	8 Apr →
dust2	8–13	-0.02	15%	8 Apr →
nuke	11–13	-0.05	11%	5 Apr →
inferno	9–13	-0.02	11%	5 Apr →
anubis	13–4	-0.05	12%	5 Apr →
anubis	11–13	-0.01	13%	4 Apr →
anubis	9–13	-0.03	6%	2 Apr →
inferno	8–13	-0.06	10%	2 Apr →
ancient	13–7	0.01	10%	29 Mar →
dust2	13–5	0.04	10%	29 Mar →
mirage	3–13	-0.08	13%	28 Mar →
dust2	9–13	-0.02	14%	28 Mar →
nuke	8–13	-0.07	10%	25 Mar →
inferno	13–11	0.04	15%	22 Mar →
anubis	13–7	0.03	8%	22 Mar →
dust2	6–13	0.02	11%	22 Mar →
dust2	9–13	-0.01	7%	22 Mar →
inferno	11–13	-0.00	11%	15 Mar →
mirage	9–13	-0.02	26%	9 Mar →
mirage	13–10	0.03	13%	5 Mar →
inferno	5–13	-0.02	11%	1 Mar →
nuke	13–2	0.06	13%	27 Feb →
mirage	13–11	0.02	8%	27 Feb →
anubis	7–13	0.04	20%	27 Feb →
mirage	9–13	-0.05	15%	26 Feb →
dust2	7–13	-0.04	12%	23 Feb →
inferno	12–16	-0.00	13%	23 Feb →
inferno	13–11	-0.02	7%	21 Feb →
dust2	8–13	0.01	9%	21 Feb →
dust2	13–11	0.01	11%	20 Feb →
inferno	8–13	0.00	17%	19 Feb →
dust2	13–11	-0.02	15%	15 Feb →
nuke	13–1	0.10	16%	15 Feb →
nuke	11–13	-0.01	12%	14 Feb →
dust2	10–2	0.04	12%	13 Feb →
mirage	7–13	-0.04	3%	13 Feb →
nuke	11–13	-0.02	9%	11 Feb →
mirage	14–16	0.04	19%	10 Feb →
inferno	13–4	0.03	17%	10 Feb →
nuke	13–5	-0.06	17%	9 Feb →
anubis	13–11	0.07	18%	9 Feb →
inferno	13–11	0.04	16%	6 Feb →
mirage	13–2	0.05	11%	6 Feb →
overpass	5–13	-0.02	16%	6 Feb →
mirage	4–13	-0.03	18%	6 Feb →
mirage	9–13	-0.01	13%	5 Feb →
mirage	5–13	-0.02	6%	3 Feb →
inferno	13–11	-0.02	8%	2 Feb →
mirage	16–12	0.02	8%	29 Jan →
mirage	12–12	0.01	5%	21 Jan →
train	13–4	0.01	17%	21 Jan →
vertigo	7–13	-0.05	7%	21 Jan →
dust2	13–10	-0.00	12%	15 Jan →
nuke	15–15	-0.00	10%	14 Jan →
mirage	13–7	0.01	11%	14 Jan →
dust2	13–6	0.10	14%	11 Jan →
inferno	9–13	-0.03	9%	10 Jan →
dust2	13–3	0.06	14%	10 Jan →
inferno	13–8	0.04	14%	10 Jan →
mirage	8–13	-0.04	11%	10 Jan →
inferno	10–13	-0.05	10%	10 Jan →
dust2	15–15	0.01	12%	10 Jan →
dust2	7–13	0.04	17%	8 Jan →
mirage	13–1	-0.03	17%	8 Jan →
inferno	13–2	-0.00	15%	8 Jan →
nuke	13–3	0.10	5%	8 Jan →
mirage	13–6	0.05	13%	4 Jan →
inferno	3–13	-0.07	11%	4 Jan →
nuke	13–3	0.04	24%	4 Jan →
dust2	13–4	-0.02	13%	4 Jan →
ancient	16–13	0.04	12%	4 Jan →