Joyrope — CS2 Stats

NP76561198275826277[U:1:315560549]Steam profile ↗✓ No bans

1,866Tracked matches66%Win rate2021Tracked since

3,185Hours in CS25Hrs last 2 wks

CSDB Rating3.6 Learning

WingmanSilver I

Ladder ranks via Leetify

Performance scores

Aim16

Positioning32

Utility57

0–100 skill scores via Leetify.

Recent form

HOT53–37–10Last 10053%Win rateTWWWLWWLWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating

Player DNA

Aim1.6

Aggression0.9

Utility5.7

Positioning3.2

Opening Duels0.0

Clutch6.0

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 66% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Strengths

Flashes. 0.78 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 43% on CT to 9% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 677ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% 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

Aim1.6

Positioning3.2

Utility5.7

Mechanics3.1

Opening Duels1.7

Win Impact10.0

Composite 3.6/10 (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-0.03+0.02

first ⅓ avg -0.05 → last ⅓ avg -0.03

Reaction time672ms−67ms

first ⅓ avg 738ms → last ⅓ avg 672ms

Headshot accuracy13.3%−0.0%

first ⅓ avg 13.4% → last ⅓ avg 13.3%

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

0.08Best rating — dust2 13–9

13–0Biggest win — dust2

5Longest win streak

7–2In matches decided by ≤2 rounds

3Overtime games

Map breakdown

ancientBest map · 100% over 6infernoWeakest map · 44% over 16

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	44	24–20	55%	-0.04
mirage	B	19	10–9	53%	-0.05
inferno	C	16	7–9	44%	-0.04
nuke	B	11	5–6	45%	-0.05
ancient	S	6	6–0	100%	-0.01
cache	—	2	1–1	50%	-0.07
anubis	—	1	0–1	0%	-0.03
train	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (44% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

40,808Lifetime kills

0.56K/D

4,535Matches

32.6%Match win rate

34.1%Headshot %

5.7%Shot accuracy

4,181MVPs

1,513Hours (in match)

4,951Bombs planted

510Bombs defused

Most-used weapons

M4A4 / M4A1-S10,109

AK-476,658

Galil AR4,299

FAMAS2,966

MP92,083

P2000 / USP-S2,000

Glock-181,948

P2501,685

SG 5531,666

AWP1,592

Lifetime map wins

12,593dust2

7,929inferno

2,409nuke

449train

395vertigo

41lake

38office

29italy

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

Faceit stats

Combat

6Matches

17%Win rate

0.43Avg K/D

49.3ADR

63%Headshot %

Clutches & streaks

50%1v1 clutch win

0%1v2 clutch win

1Longest win streak

Recent Faceit resultsLWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	3	33%	0.54	9.3
Cache	1	0%	0.41	7.0
Dust2	1	0%	0.25	4.0
Inferno	1	0%	0.29	5.0

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.

12.1%Headshot accuracy

27.6%Accuracy (enemy spotted)

35.5%Spray accuracy

63.9%Counter-strafing

15.3°Preaim

677msReaction time

8.7%T opening success

43.2%CT opening success

0.78Enemies flashed / flash

3.5%Flash assists

12.13HE damage / grenade

11.77Flashes / 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 15.332° — 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 12.1275% — 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.

44% win rate across 16 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	12–12	-0.04	24%	29 Aug →
dust2	13–0	-0.04	21%	29 Aug →
mirage	13–5	-0.04	8%	28 Aug →
ancient	13–5	0.03	6%	28 Aug →
mirage	4–13	-0.07	14%	28 Aug →
nuke	6–4	-0.06	0%	28 Aug →
dust2	13–1	0.01	14%	28 Aug →
mirage	10–13	-0.07	5%	28 Aug →
mirage	13–11	-0.02	13%	26 Aug →
dust2	13–9	0.08	10%	26 Aug →
cache	13–8	-0.06	11%	26 Aug →
dust2	10–13	-0.05	4%	25 Aug →
nuke	5–13	-0.06	8%	25 Aug →
dust2	13–8	-0.06	9%	23 Aug →
anubis	6–13	-0.03	8%	23 Aug →
mirage	9–13	-0.01	9%	22 Aug →
dust2	13–8	-0.03	14%	22 Aug →
inferno	13–4	0.01	33%	22 Aug →
dust2	10–13	-0.06	17%	21 Aug →
ancient	13–8	0.02	2%	21 Aug →
dust2	13–5	0.02	12%	20 Aug →
ancient	16–13	-0.03	7%	19 Aug →
nuke	8–13	-0.07	13%	18 Aug →
ancient	13–4	-0.07	27%	18 Aug →
mirage	6–3	-0.05	29%	18 Aug →
inferno	6–1	-0.02	33%	18 Aug →
dust2	13–2	-0.03	5%	17 Aug →
nuke	8–13	-0.14	14%	16 Aug →
inferno	6–13	-0.10	6%	16 Aug →
ancient	13–0	0.04	15%	16 Aug →
dust2	2–9	0.02	18%	16 Aug →
nuke	13–9	0.04	14%	16 Aug →
nuke	13–7	-0.07	16%	16 Aug →
nuke	4–13	-0.07	14%	11 Aug →
mirage	5–13	-0.06	6%	11 Aug →
inferno	15–15	-0.09	6%	9 Aug →
dust2	3–13	-0.03	18%	9 Aug →
inferno	12–12	-0.06	10%	9 Aug →
dust2	12–12	-0.04	8%	9 Aug →
nuke	8–13	-0.01	20%	9 Aug →
dust2	13–11	-0.05	11%	8 Aug →
inferno	13–2	0.01	8%	8 Aug →
mirage	13–8	-0.02	12%	8 Aug →
dust2	13–2	0.05	15%	8 Aug →
nuke	13–9	-0.05	3%	5 Aug →
mirage	5–13	-0.08	8%	5 Aug →
dust2	12–12	-0.10	6%	4 Aug →
dust2	10–13	-0.06	12%	4 Aug →
dust2	15–15	-0.08	22%	1 Aug →
mirage	13–8	-0.05	14%	1 Aug →
dust2	4–13	-0.10	19%	1 Aug →
dust2	12–12	-0.04	16%	27 Jul →
dust2	13–2	-0.02	5%	27 Jul →
dust2	13–4	-0.10	13%	27 Jul →
inferno	13–6	-0.06	12%	26 Jul →
mirage	3–13	-0.04	16%	26 Jul →
dust2	10–13	-0.04	14%	25 Jul →
dust2	13–9	-0.02	13%	25 Jul →
mirage	1–13	-0.08	8%	22 Jul →
dust2	6–13	-0.06	16%	22 Jul →
dust2	13–11	-0.05	13%	21 Jul →
dust2	13–2	0.03	18%	21 Jul →
inferno	13–6	0.03	20%	19 Jul →
dust2	8–0	0.02	31%	19 Jul →
dust2	8–13	-0.02	24%	19 Jul →
mirage	13–7	0.02	14%	18 Jul →
dust2	13–4	0.01	32%	17 Jul →
dust2	1–13	-0.05	13%	14 Jul →
dust2	13–4	0.04	20%	14 Jul →
mirage	8–13	-0.09	13%	12 Jul →
mirage	13–3	-0.01	10%	12 Jul →
dust2	13–6	-0.07	7%	12 Jul →
dust2	13–2	-0.03	17%	12 Jul →
inferno	6–13	-0.10	12%	12 Jul →
ancient	13–9	-0.02	16%	12 Jul →
nuke	3–13	-0.11	6%	11 Jul →
dust2	13–9	-0.06	10%	11 Jul →
mirage	13–11	-0.04	14%	11 Jul →
inferno	8–13	-0.07	10%	11 Jul →
mirage	13–9	-0.10	20%	11 Jul →
dust2	6–13	-0.11	18%	10 Jul →
dust2	13–11	-0.09	4%	10 Jul →
inferno	10–13	0.00	22%	10 Jul →
dust2	10–13	-0.12	16%	8 Jul →
nuke	13–7	0.00	13%	7 Jul →
mirage	12–12	-0.07	15%	7 Jul →
dust2	12–12	-0.10	13%	7 Jul →
dust2	12–12	-0.05	16%	7 Jul →
inferno	3–13	-0.12	9%	30 Jun →
dust2	13–6	-0.02	20%	30 Jun →
dust2	13–5	-0.03	29%	28 Jun →
mirage	13–10	-0.08	12%	28 Jun →
dust2	11–13	-0.03	7%	28 Jun →
dust2	13–9	-0.04	4%	28 Jun →
inferno	13–11	-0.03	13%	28 Jun →
inferno	13–6	-0.06	15%	27 Jun →
train	4–13	-0.06	10%	25 Jun →
dust2	6–13	0.02	7%	25 Jun →
inferno	5–13	-0.03	17%	24 Jun →
cache	11–13	-0.08	13%	22 Jun →