炸蟹角

炸蟹角 — CS2 Stats

US76561198017752982[U:1:57487254]Steam profile ↗✓ No bans

441Tracked matches41%Win rate2020Tracked since
3,645Hours in CS27Hrs last 2 wks
CSDB Rating3.4 LearningClutch Specialist
Premier CS Rating13,404Blue band · top ~36.9% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Oct 2026 (yesterday). Ranks are recorded once per day this page is viewed.

+733Premier CS Rating · 12,671 → 13,404

Rating over time

Premier CS Rating: 13,404 -1,601 12 Feb – 17 Oct · 29 days played
12,55215,005peak 15,00512 Feb17 Oct
15,005Peak Premier in tracked matches
54Days played since 2026-02-12

Premier CS Rating

  • 1,601 below peak (15,005)
  • Next: Purple band at 15,000 — 1,596 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.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate37.4%42.0%44.3%6.9% short
Shot accuracy16.8%9.6%11.9%above
Kill/death ratio1.010.981.03meets
Match win rate42.2%43.8%45.2%3.0% short

This profile matches the typical Purple band player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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CSDB.GG炸蟹角PREMIER13,404 · Blue bandcsdb.gg/stats

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Performance scores

Aim42
Positioning33
Utility39

0–100 skill scores via Leetify.

Recent form

STEADY39–57–4Last 10039%Win rateWWLWTLLWLL

Last 10 vs previous 10: −10pp win rate · −0.02 avg rating · +0.0pp headshot accuracy · +31ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 3–1–1 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 10%
  • Avg reaction 630ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 613ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 598ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+3.6 against its own average).

Aim4.2
Utility3.9
Positioning3.3
Opening Duels0.0
Clutch7.2

Limited utility dependenceReliable in 1v1s

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 85% 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

Reaction time. 589ms 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

Aim4.2
Positioning3.3
Utility3.9
Mechanics5.0
Opening Duels1.0
Win Impact2.1

Composite 3.4/10 (Learning), 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 rating-0.04−0.02
first ⅓ avg -0.02 → last ⅓ avg -0.04
Reaction time593ms−49ms
first ⅓ avg 642ms → last ⅓ avg 593ms
Headshot accuracy13.2%−4.6%
first ⅓ avg 17.8% → last ⅓ avg 13.2%

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

0.12Best match rating · 1–6 · mirage, 17 Feb →
32%Best headshot accuracy · 13–8 · dust2, 24 Apr →
375msFastest reaction time · 13–1 · inferno, 10 Aug →
13–1Biggest win · mirage, 25 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W2Current streak
5–5In matches decided by ≤2 rounds
10Overtime games

Map breakdown

dust2Best map · 67% over 9infernoWeakest map · 11% over 9
MapGradePlayedRecordWin rateAvg rating
cacheC198–1142%-0.02
mirageD174–1324%-0.04
ancientC146–843%-0.03
nukeB126–650%-0.04
infernoD91–811%-0.05
dust2S96–367%0.00
anubisA74–357%-0.03
overpassD72–529%-0.02
train—21–150%-0.00
poseidon—10–10%-0.12
debris—11–0100%-0.09
office—10–10%-0.09
vertigo—10–10%0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (11% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

82,185Lifetime kills
1.01K/D · Top 50% of Blue band
3,526Matches
42.2%Match win rate
37.4%Headshot %
16.8%Shot accuracy · Top 25% of Blue band
7,470MVPs
1,760Hours (in match)
4,162Bombs planted
1,045Bombs defused

Most-used weapons

AWP17,357
AK-4715,620
P2504,150
P902,024
MP71,185
FAMAS1,148

Lifetime map wins

6,220dust2
5,378inferno
4,302nuke
2,524train
737cbble
531vertigo
137militia
99office

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

Faceit stats

Combat

39Matches
49%Win rate
0.90Avg K/D
57.1ADR
42%Headshot %

Clutches & streaks

56%1v1 clutch win
0%1v2 clutch win
5Longest win streak

Recent Faceit resultsWLLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient540%0.498.6
Mirage50%0.458.2
Overpass3100%0.7111.3
Nuke30%0.538.3
Vertigo250%0.459.5
Inferno1100%2.3023.0

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.

13.2%Headshot accuracy
30.3%Accuracy (enemy spotted)
32.2%Spray accuracy
72.3%Counter-strafing
11.3°Preaim
589msReaction time
37.2%T opening success
30.5%CT opening success
0.41Enemies flashed / flash
9.3%Flash assists
11.33HE damage / grenade
1.46Flashes / 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. 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 13.2257% — below the 15% mark we flag

    Aim Training →
  2. 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 0.4059 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 37.1589% — below the 40% mark we flag

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.

11% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–6-0.0514%17 Oct →
cache13–20.026%17 Oct →
inferno10–13-0.068%16 Oct →
nuke13–60.0216%16 Oct →
anubis15–15-0.067%16 Oct →
cache13–16-0.0411%14 Oct →
ancient8–13-0.0524%14 Oct →
dust213–60.0120%12 Oct →
cache3–13-0.059%12 Oct →
cache0–13-0.0811%11 Oct →
mirage9–130.0216%11 Oct →
nuke8–13-0.0216%10 Oct →
ancient6–13-0.0511%10 Oct →
cache16–13-0.0317%9 Oct →
inferno2–13-0.0211%8 Oct →
dust213–100.0210%8 Oct →
ancient13–6-0.0012%8 Oct →
nuke13–90.0424%8 Oct →
anubis13–11-0.073%6 Oct →
inferno11–13-0.037%3 Oct →
dust213–100.0211%3 Oct →
nuke9–13-0.0326%3 Oct →
mirage6–13-0.086%2 Oct →
mirage7–13-0.0616%2 Oct →
ancient13–90.0117%1 Oct →
nuke7–13-0.0924%28 Sept →
inferno8–8-0.0913%28 Sept →
poseidon1–9-0.1221%28 Sept →
debris9–6-0.098%28 Sept →
dust27–13-0.0516%25 Sept →
mirage13–1-0.105%25 Sept →
ancient6–13-0.0613%23 Sept →
cache9–13-0.0612%7 Sept →
anubis13–10-0.076%30 Aug →
cache8–13-0.0728%30 Aug →
ancient2–13-0.0425%29 Aug →
cache13–6-0.0113%29 Aug →
inferno10–13-0.085%29 Aug →
cache6–13-0.0611%23 Aug →
ancient10–13-0.0315%15 Aug →
inferno13–1-0.080%10 Aug →
nuke13–10-0.0513%10 Aug →
anubis13–4-0.0423%2 Aug →
nuke13–11-0.0910%1 Aug →
mirage8–13-0.1113%1 Aug →
mirage7–13-0.0431%29 Jul →
ancient13–10-0.0514%29 Jul →
anubis6–13-0.0014%29 Jul →
ancient7–13-0.0613%12 Jun →
mirage3–13-0.059%9 Jun →
overpass4–13-0.0629%9 Jun →
anubis7–130.0017%28 May →
overpass9–13-0.0026%28 May →
mirage11–13-0.0313%25 May →
nuke13–6-0.0311%25 May →
ancient13–9-0.0518%24 May →
inferno15–150.0120%24 May →
mirage13–110.0118%24 May →
overpass8–13-0.040%20 May →
mirage2–13-0.0514%16 May →
cache13–9-0.0325%13 May →
mirage4–13-0.0525%13 May →
overpass13–16-0.049%12 May →
mirage13–6-0.098%11 May →
dust212–160.0120%11 May →
ancient16–130.0010%10 May →
train13–6-0.0116%8 May →
cache11–130.0421%8 May →
cache7–13-0.039%8 May →
cache8–130.0618%7 May →
cache5–13-0.0623%7 May →
ancient5–130.0625%6 May →
cache12–12-0.029%6 May →
dust213–11-0.033%5 May →
nuke4–13-0.130%5 May →
cache13–100.0514%5 May →
office3–13-0.0912%5 May →
mirage9–13-0.079%4 May →
cache13–110.0225%1 May →
cache13–8-0.0216%29 Apr →
inferno7–13-0.0415%26 Apr →
dust213–6-0.0024%26 Apr →
nuke6–13-0.046%26 Apr →
inferno9–13-0.0330%25 Apr →
anubis13–30.0521%25 Apr →
ancient16–12-0.0620%25 Apr →
mirage13–8-0.0323%25 Apr →
mirage11–13-0.0822%24 Apr →
dust213–80.0032%24 Apr →
nuke13–6-0.0320%24 Apr →
overpass13–70.0924%22 Apr →
overpass11–13-0.0513%18 Apr →
mirage13–16-0.0723%16 Apr →
nuke7–13-0.0417%14 Apr →
dust25–130.0222%12 Apr →
overpass16–13-0.0623%19 Mar →
vertigo2–130.037%18 Feb →
train9–130.0020%18 Feb →
mirage1–60.1229%17 Feb →
ancient6–13-0.1012%12 Feb →

Match data via Leetify.

Recent teammates

Milestones

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

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