✦︎ coco -

✦︎ coco - — CS2 Stats

IN76561199533506372[U:1:1573240644]Steam profile ↗✓ No bans

581Tracked matches46%Win rate2024Tracked since
CSDB Rating6.5 SolidPositional Player
Premier CS Rating15,387Purple band · top ~26.9% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Nov 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 15,387 +1,511 7 Oct – 13 Nov · 18 days played
12,35016,267peak 16,2677 Oct13 Nov
16,267Peak Premier in tracked matches
31Days played since 2026-09-17

Premier CS Rating

  • 880 below peak (16,267)
  • +2,828 over 30 days · improving
  • Next: Pink band at 20,000 — 4,613 to go
  • Reached: Purple band · Blue band · Light Blue band

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GG✦︎ coco -PREMIER15,387 · Purple bandcsdb.gg/stats

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Performance scores

Aim76
Positioning68
Utility56

0–100 skill scores via Leetify.

Recent form

HOT51–43–6Last 10051%Win rateWTWWLWWWWL

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · −3.9pp headshot accuracy · −50ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 3–1–1 · 60% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 538ms

Last 10

  • 7–2–1 · 70% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 19%
  • Avg reaction 559ms

Last 20

  • 12–7–1 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 21%
  • Avg reaction 584ms

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: Positional Player — Positioning stands above the rest of this profile (+1.3 against its own average).

Aim7.6
Utility5.6
Positioning6.8
Opening Duels4.8
Clutch4.8

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

m0NESY

Plays most like m0NESY 89% playstyle similarity

Most alike: positioning profile, utility contribution.

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

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. 593ms 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

Aim7.6
Positioning6.8
Utility5.6
Mechanics7.2
Opening Duels6.0
Win Impact3.8

Composite 6.5/10 (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 rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time581ms−28ms
first ⅓ avg 609ms → last ⅓ avg 581ms
Headshot accuracy23.5%−1.7%
first ⅓ avg 25.2% → last ⅓ avg 23.5%

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 · 13–2 · dust2, 9 Oct →
57%Best headshot accuracy · 13–10 · nuke, 22 Oct →
391msFastest reaction time · 2–9 · inferno, 13 Nov →
13–2Biggest win · dust2, 9 Oct →

Across the last 100 tracked matches.

Highlights

7Longest win streak
8–8In matches decided by ≤2 rounds
6Overtime games

Map breakdown

nukeBest map · 75% over 8ancientWeakest map · 40% over 10
MapGradePlayedRecordWin rateAvg rating
dust2B2914–1548%0.01
mirageC198–1142%0.02
cacheA169–756%0.01
infernoA138–562%-0.01
ancientC104–640%0.02
nukeS86–275%0.03
anubis—21–150%0.03
fachwerk—10–10%-0.02
train—11–0100%-0.04
vertigo—10–10%-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (40% over 10). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

30Matches
53%Win rate
1.14Avg K/D
85.7ADR
52%Headshot %

Clutches & streaks

44%1v1 clutch win
30%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWLWL

MapMatchesWin rateAvg K/DAvg kills
Mirage1338%1.1918.9
Dust21258%0.9316.3
Inferno3100%1.5521.7
Ancient250%1.3625.5

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.

25.9%Headshot accuracy
33.5%Accuracy (enemy spotted)
33.1%Spray accuracy
82.4%Counter-strafing
9.7°Preaim
593msReaction time
58.6%T opening success
49.0%CT opening success
0.58Enemies flashed / flash
11.1%Flash assists
8.03HE damage / grenade
10.41Flashes / match

Recommended for you

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.

40% 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

MapScoreRatingHS%Date
nuke9–50.058%14 Nov →
mirage12–120.0626%14 Nov →
inferno13–9-0.0321%14 Nov →
inferno9–4-0.0215%13 Nov →
inferno2–9-0.196%13 Nov →
inferno9–60.0423%13 Nov →
inferno9–60.0717%13 Nov →
inferno9–70.1121%13 Nov →
dust213–8-0.0025%13 Nov →
dust211–13-0.0627%13 Nov →
dust24–13-0.1119%13 Nov →
dust213–40.0918%12 Nov →
inferno6–13-0.0525%12 Nov →
cache3–13-0.0530%12 Nov →
dust26–20.0927%12 Nov →
mirage16–120.0324%6 Nov →
dust25–130.0227%6 Nov →
dust21–7-0.028%6 Nov →
cache13–100.0125%5 Nov →
dust213–80.0028%5 Nov →
inferno11–130.0136%5 Nov →
nuke12–160.0122%5 Nov →
inferno13–7-0.0121%4 Nov →
dust211–130.0036%4 Nov →
dust212–120.0328%4 Nov →
mirage13–90.0221%4 Nov →
cache13–110.0223%3 Nov →
inferno2–13-0.0532%3 Nov →
ancient5–130.0038%3 Nov →
cache10–130.0934%2 Nov →
cache3–13-0.0617%2 Nov →
inferno13–60.0321%29 Oct →
ancient13–40.0428%29 Oct →
cache13–90.0435%28 Oct →
dust29–13-0.0120%28 Oct →
inferno3–11-0.1227%27 Oct →
dust213–10-0.0037%27 Oct →
dust213–100.0515%26 Oct →
cache16–140.1030%26 Oct →
mirage6–13-0.0125%25 Oct →
ancient13–90.1025%25 Oct →
ancient13–110.0429%25 Oct →
cache13–40.0433%25 Oct →
mirage13–80.0738%25 Oct →
nuke13–9-0.0020%25 Oct →
nuke13–110.0226%25 Oct →
nuke13–100.0857%22 Oct →
dust210–13-0.0827%22 Oct →
cache13–4-0.0225%21 Oct →
cache13–9-0.0432%20 Oct →
fachwerk4–13-0.0233%20 Oct →
cache13–100.0522%20 Oct →
cache0–90.0428%19 Oct →
dust213–7-0.0120%19 Oct →
cache10–13-0.0431%19 Oct →
mirage8–130.0619%17 Oct →
mirage13–60.0340%16 Oct →
mirage13–30.1323%16 Oct →
mirage13–50.0917%14 Oct →
dust212–120.0310%14 Oct →
dust21–13-0.1037%12 Oct →
mirage11–13-0.0316%9 Oct →
dust213–60.0139%9 Oct →
dust213–20.2025%9 Oct →
dust214–16-0.0232%8 Oct →
cache4–13-0.0431%8 Oct →
ancient9–13-0.0218%8 Oct →
mirage13–50.0433%7 Oct →
anubis13–40.0522%7 Oct →
anubis3–130.0220%7 Oct →
mirage11–13-0.0127%7 Oct →
mirage10–13-0.0020%7 Oct →
nuke13–6-0.0029%7 Oct →
mirage6–13-0.0611%7 Oct →
mirage11–13-0.0118%7 Oct →
ancient4–130.0224%7 Oct →
ancient13–11-0.0016%3 Oct →
ancient15–150.0414%3 Oct →
dust213–60.0322%3 Oct →
mirage13–100.0132%3 Oct →
ancient12–12-0.0139%3 Oct →
cache5–13-0.0124%3 Oct →
nuke13–70.0432%3 Oct →
mirage10–130.0220%2 Oct →
dust213–110.0330%2 Oct →
mirage9–13-0.0128%2 Oct →
ancient2–130.0032%1 Oct →
dust213–100.0935%1 Oct →
dust24–13-0.0250%1 Oct →
mirage4–13-0.0317%30 Sept →
train13–7-0.0430%30 Sept →
inferno13–80.0222%30 Sept →
dust213–110.0313%24 Sept →
dust25–130.0125%24 Sept →
cache12–60.0518%24 Sept →
vertigo11–13-0.0222%24 Sept →
nuke15–150.0321%23 Sept →
dust26–130.0124%23 Sept →
dust27–13-0.0214%17 Sept →
dust23–00.0250%17 Sept →

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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