Cinco. — CS2 Stats

PT76561198048536536[U:1:88270808]Steam profile ↗✓ No bans

1,816Tracked matches36%Win rate2020Tracked since

CSDB Rating2.2 Learning

Premier CS Rating9,312Light Blue band · top ~58.2% of ranked players (population est.)

CSDB Leaderboard#17999 of 24282 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

WingmanGold Nova II

Ladder ranks via Leetify

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Performance scores

Aim20

Positioning37

Utility45

0–100 skill scores via Leetify.

Recent form

STEADY41–56–3Last 10041%Win rateLLLLWWWLLW

Last 10 vs previous 10: +20pp win rate · +0.03 avg rating

Player DNA

Aim2.0

Aggression1.9

Utility4.5

Positioning3.7

Opening Duels0.0

Clutch5.4

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 67% 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

Areas to improve

Reaction time. 651ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 62% 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

Aim2.0

Positioning3.7

Utility4.5

Mechanics2.7

Opening Duels0.1

Win Impact0.2

Composite 2.2/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.05−0.02

first ⅓ avg -0.02 → last ⅓ avg -0.05

Reaction time676ms+14ms

first ⅓ avg 662ms → last ⅓ avg 676ms

Headshot accuracy11.7%−1.5%

first ⅓ avg 13.2% → last ⅓ avg 11.7%

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

0.17Best rating — nuke 9–3

13–0Biggest win — mirage

3Longest win streak

L4Current streak

6–8In matches decided by ≤2 rounds

6Overtime games

Map breakdown

nukeBest map · 75% over 8ancientWeakest map · 0% over 5

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	20	8–12	40%	-0.05
inferno	D	19	6–13	32%	-0.03
dust2	C	15	6–9	40%	-0.03
anubis	S	12	8–4	67%	-0.04
cache	D	11	3–8	27%	-0.05
nuke	S	8	6–2	75%	0.03
ancient	D	5	0–5	0%	-0.06
overpass	C	5	2–3	40%	-0.03
train	—	3	0–3	0%	-0.03
debris	—	1	1–0	100%	-0.02
office	—	1	1–0	100%	-0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

105Matches

48%Win rate

0.62Avg K/D

61.1ADR

33%Headshot %

Clutches & streaks

47%1v1 clutch win

29%1v2 clutch win

4Longest win streak

Recent Faceit resultsWWWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	8	62%	0.76	14.6
Mirage	8	50%	0.55	9.4
Dust2	7	71%	0.72	10.0
Ancient	5	60%	0.89	16.2
Anubis	5	100%	0.74	9.2
Nuke	3	100%	0.91	14.3

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

28.9%Accuracy (enemy spotted)

30.9%Spray accuracy

62.2%Counter-strafing

13.2°Preaim

651msReaction time

30.5%T opening success

21.9%CT opening success

0.55Enemies flashed / flash

2.9%Flash assists

10.35HE damage / grenade

5.83Flashes / 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 13.2386° — 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 12.0859% — 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.

0% win rate across 5 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
inferno	11–13	-0.02	8%	27 Aug →
ancient	4–13	-0.04	8%	27 Aug →
cache	4–13	-0.05	14%	26 Aug →
dust2	11–13	-0.05	15%	25 Aug →
dust2	13–6	0.01	20%	25 Aug →
inferno	25–23	0.02	13%	24 Aug →
anubis	13–6	-0.06	17%	24 Aug →
mirage	1–13	-0.06	10%	20 Aug →
dust2	9–13	0.03	27%	19 Aug →
dust2	13–10	-0.04	21%	13 Aug →
dust2	13–11	0.04	9%	13 Aug →
train	12–12	-0.05	4%	13 Aug →
cache	13–8	-0.13	8%	12 Aug →
cache	3–13	-0.04	3%	12 Aug →
ancient	5–13	-0.09	12%	12 Aug →
mirage	11–13	-0.10	4%	12 Aug →
train	9–13	-0.08	4%	12 Aug →
inferno	8–13	-0.07	18%	11 Aug →
mirage	12–12	-0.03	11%	11 Aug →
cache	11–13	-0.03	14%	11 Aug →
anubis	13–6	-0.02	4%	11 Aug →
mirage	13–8	-0.07	27%	11 Aug →
ancient	12–16	-0.07	11%	11 Aug →
ancient	9–13	-0.02	19%	10 Aug →
overpass	13–4	0.02	10%	10 Aug →
debris	9–0	-0.02	0%	10 Aug →
anubis	13–3	-0.08	9%	10 Aug →
inferno	5–13	-0.10	14%	10 Aug →
cache	1–13	-0.05	12%	9 Aug →
anubis	7–13	-0.07	9%	9 Aug →
dust2	7–13	-0.08	6%	9 Aug →
mirage	6–13	-0.05	10%	9 Aug →
dust2	13–11	-0.03	17%	6 Aug →
dust2	5–13	-0.06	18%	28 Jul →
inferno	13–8	-0.01	21%	27 Jul →
anubis	13–9	0.05	8%	27 Jul →
inferno	9–13	0.03	10%	27 Jul →
inferno	8–13	-0.06	20%	27 Jul →
dust2	2–13	-0.10	27%	26 Jul →
mirage	13–9	-0.05	7%	26 Jul →
cache	8–13	0.01	12%	25 Jul →
anubis	13–10	-0.03	15%	25 Jul →
cache	13–6	-0.02	16%	24 Jul →
inferno	9–13	-0.04	12%	24 Jul →
mirage	4–13	-0.08	39%	24 Jul →
cache	13–10	-0.05	3%	23 Jul →
mirage	13–0	-0.03	11%	23 Jul →
anubis	13–4	-0.05	7%	23 Jul →
anubis	3–13	-0.05	29%	22 Jul →
anubis	13–11	-0.04	6%	22 Jul →
mirage	13–4	-0.03	13%	21 Jul →
cache	5–13	-0.05	3%	21 Jul →
anubis	13–6	-0.00	9%	20 Jul →
mirage	10–13	0.02	14%	20 Jul →
overpass	13–4	0.01	6%	20 Jul →
inferno	13–11	-0.06	2%	20 Jul →
dust2	12–12	0.00	12%	20 Jul →
cache	11–13	-0.08	10%	19 Jul →
inferno	13–2	0.04	8%	19 Jul →
anubis	8–13	-0.09	9%	19 Jul →
nuke	16–13	0.01	9%	19 Jul →
dust2	13–7	0.06	12%	19 Jul →
inferno	10–13	-0.08	16%	16 Jul →
inferno	19–16	0.01	11%	16 Jul →
inferno	3–13	-0.03	15%	15 Jul →
dust2	1–13	-0.09	14%	15 Jul →
mirage	4–13	-0.05	6%	15 Jul →
inferno	5–13	-0.08	23%	14 Jul →
office	13–7	-0.06	8%	14 Jul →
mirage	10–13	-0.06	15%	14 Jul →
dust2	10–13	-0.06	13%	14 Jul →
nuke	13–6	-0.01	13%	14 Jul →
mirage	13–11	-0.03	27%	14 Jul →
mirage	11–13	-0.06	12%	13 Jul →
dust2	13–1	-0.01	10%	13 Jul →
ancient	10–13	-0.06	4%	1 Jul →
cache	4–13	-0.07	18%	1 Jul →
inferno	13–4	0.06	9%	27 Jun →
anubis	7–13	-0.02	22%	27 Jun →
mirage	6–13	-0.04	10%	27 Jun →
nuke	6–13	-0.04	12%	27 Jun →
mirage	16–13	-0.04	14%	26 Jun →
inferno	8–13	-0.03	6%	26 Jun →
nuke	13–5	0.04	2%	26 Jun →
dust2	5–13	-0.06	13%	26 Jun →
mirage	13–10	-0.06	14%	26 Jun →
nuke	14–16	0.02	15%	25 Jun →
overpass	6–13	-0.08	12%	25 Jun →
overpass	5–13	-0.01	14%	24 Jun →
nuke	9–0	0.11	21%	24 Jun →
inferno	6–13	-0.01	8%	24 Jun →
mirage	8–13	-0.07	10%	24 Jun →
nuke	9–3	0.17	11%	22 Jun →
inferno	4–13	-0.07	10%	21 Jun →
inferno	5–9	-0.03	21%	20 Jun →
overpass	7–13	-0.09	11%	20 Jun →
nuke	13–4	-0.05	13%	20 Jun →
mirage	13–10	0.00	24%	19 Jun →
mirage	1–13	-0.03	17%	19 Jun →
train	11–13	0.03	8%	19 Jun →