Priceyy_

Priceyy_ — CS2 Stats

76561198188764353[U:1:228498625]Steam profile ↗✓ No bans

903Tracked matches48%Win rate2020Tracked since
CSDB Rating4.2 DevelopingAll-Rounder
Premier CS Rating13,541Blue band · top ~36.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 Sep 2026 (14 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 903 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 13,541 -5,984 16 Mar – 17 Sept · 23 days played
13,21120,375peak 20,37516 Mar17 Sept
20,499Peak Premier in tracked matches
50Days played since 2025-03-16

Premier CS Rating

  • 6,834 below peak (20,375)
  • Next: Purple band at 15,000 — 1,459 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-09-17
  • Light Blue band first seen 2026-09-17

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

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CSDB.GGPriceyy_PREMIER13,541 · Blue bandcsdb.gg/stats

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Performance scores

Aim46
Positioning48
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY45–54–1Last 10045%Win rateLWWWWLWLTW

Last 10 vs previous 10: +20pp win rate · +0.06 avg rating · +1.9pp headshot accuracy · −20ms 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

  • 4–1 · 80% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 21%
  • Avg reaction 707ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 19%
  • Avg reaction 662ms

Last 20

  • 10–9–1 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 18%
  • Avg reaction 672ms

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.

Aim4.6
Utility4.6
Positioning4.8
Opening Duels4.0

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

ZywOo

Plays most like ZywOo 78% 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 →

Strengths & areas to improve

Areas to improve

T-side openings. Opening success drops from 49% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 648ms 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

Aim4.6
Positioning4.8
Utility4.6
Mechanics4.8
Opening Duels2.7
Win Impact4.4

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.02
first ⅓ avg -0.02 → last ⅓ avg 0.00
Reaction time641ms+2ms
first ⅓ avg 639ms → last ⅓ avg 641ms
Headshot accuracy18.0%+2.1%
first ⅓ avg 15.9% → last ⅓ avg 18.0%

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

0.15Best match rating · 13–4 · anubis, 17 Apr →
37%Best headshot accuracy · 4–13 · train, 21 Aug →
430msFastest reaction time · 7–13 · overpass, 28 Jan →
13–1Biggest win · mirage, 3 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–8In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 60% over 15dust2Weakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
mirageC218–1338%0.00
nukeA2112–957%-0.01
infernoB158–753%-0.01
anubisA159–660%0.01
ancientD112–918%-0.02
overpassB63–350%-0.05
dust2D61–517%-0.03
trainC52–340%-0.01

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Dust 2 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.

18.0%Headshot accuracy
30.7%Accuracy (enemy spotted)
34.7%Spray accuracy
71.5%Counter-strafing
11.1°Preaim
648msReaction time
33.0%T opening success
48.5%CT opening success
0.54Enemies flashed / flash
4.1%Flash assists
9.29HE damage / grenade
5.29Flashes / 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.

  1. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 33.0113% — below the 40% mark we flag

Spend your practice time on Dust 2

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage12–160.0123%17 Apr →
inferno13–60.1022%4 Apr →
anubis16–140.0520%28 Mar →
nuke13–20.0922%28 Mar →
nuke13–9-0.0221%28 Mar →
nuke10–13-0.0414%26 Mar →
mirage13–70.1323%26 Mar →
mirage9–13-0.0117%19 Mar →
ancient15–150.0112%19 Mar →
overpass13–80.0118%14 Mar →
nuke8–13-0.0714%7 Mar →
overpass13–9-0.0415%7 Mar →
anubis12–160.0025%7 Mar →
mirage6–130.0022%5 Mar →
mirage5–13-0.0410%5 Mar →
mirage8–13-0.0413%3 Mar →
nuke13–8-0.0515%22 Feb →
anubis16–140.0116%22 Feb →
inferno13–10-0.0321%22 Feb →
dust211–130.0121%21 Feb →
mirage13–3-0.0123%20 Feb →
anubis13–20.0621%20 Feb →
ancient7–13-0.074%30 Jan →
overpass7–13-0.0514%28 Jan →
anubis13–60.0828%28 Jan →
nuke8–13-0.0117%21 Jan →
mirage13–50.0318%21 Jan →
inferno5–13-0.0424%17 Jan →
mirage9–13-0.0218%17 Jan →
overpass11–13-0.0213%10 Jan →
ancient13–70.0214%9 Jan →
nuke13–8-0.0024%31 Aug →
inferno13–40.0212%31 Aug →
inferno9–13-0.0327%31 Aug →
mirage9–130.0227%24 Aug →
dust213–7-0.0214%24 Aug →
nuke10–13-0.0217%22 Aug →
ancient2–13-0.0722%22 Aug →
mirage16–120.0522%22 Aug →
overpass13–9-0.0836%21 Aug →
dust29–130.0123%21 Aug →
train4–130.0037%21 Aug →
overpass5–13-0.1027%10 Aug →
mirage11–13-0.0316%9 Aug →
mirage13–10.0119%3 Aug →
inferno9–13-0.0124%3 Aug →
mirage6–13-0.0413%27 Jul →
nuke13–70.0324%24 Jul →
mirage13–8-0.0221%24 Jul →
ancient4–13-0.0313%24 Jul →
inferno13–50.0722%20 Jul →
nuke13–50.0933%20 Jul →
mirage8–13-0.0022%31 May →
inferno11–13-0.0417%31 May →
anubis8–13-0.0622%31 May →
inferno8–130.0116%26 May →
dust29–13-0.0414%25 May →
anubis3–13-0.0512%5 May →
nuke13–8-0.0214%5 May →
nuke13–10-0.0421%5 May →
nuke13–80.0020%5 May →
dust26–13-0.0611%3 May →
inferno8–13-0.0410%22 Apr →
nuke13–90.0527%22 Apr →
anubis5–13-0.0526%21 Apr →
ancient8–130.0113%20 Apr →
inferno16–13-0.0116%20 Apr →
nuke14–160.0116%20 Apr →
ancient3–13-0.0418%20 Apr →
nuke9–13-0.0122%20 Apr →
nuke8–130.0123%18 Apr →
ancient11–130.0018%18 Apr →
anubis13–70.0517%18 Apr →
mirage13–10-0.0213%18 Apr →
ancient13–11-0.0417%18 Apr →
nuke11–13-0.0623%18 Apr →
anubis13–9-0.0713%17 Apr →
anubis13–40.1516%17 Apr →
dust212–16-0.0623%13 Apr →
anubis13–30.0013%13 Apr →
nuke16–14-0.0017%6 Apr →
anubis1–13-0.0117%6 Apr →
mirage13–90.0515%6 Apr →
nuke13–11-0.0012%6 Apr →
inferno9–13-0.0512%5 Apr →
anubis2–13-0.0818%4 Apr →
ancient4–130.0214%4 Apr →
train13–80.0515%4 Apr →
nuke8–13-0.0617%25 Mar →
inferno13–12-0.0323%24 Mar →
train1–13-0.070%23 Mar →
mirage9–130.0016%21 Mar →
mirage11–130.0110%21 Mar →
ancient6–13-0.083%20 Mar →
anubis13–80.0221%20 Mar →
train13–10-0.0219%18 Mar →
inferno13–50.0013%17 Mar →
inferno13–7-0.0711%17 Mar →
mirage3–13-0.0619%17 Mar →
train12–16-0.0421%16 Mar →

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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