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山鬼不识字

山鬼不识字 — CS2 Stats

CN76561198856665425[U:1:896399697]Steam profile ↗✓ No bans

2,239Tracked matches57%Win rate2020Tracked since
1,621Hours in CS
CSDB Rating4.1 Developing
FaceitLevel 4Top 81.0% of ranked FACEIT players
Ladder ranks via Leetify

How this compares with the same rank

Median values for Level 4 among CSDB-tracked players (n=928), 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 playerLevel 4 medianLevel 5 medianvs Level 5
Headshot rate34.7%42.5%44.2%9.5% short
Shot accuracy6.0%10.9%11.2%5.2% short
Kill/death ratio0.800.991.040.24 short
Match win rate46.0%44.2%45.3%meets

This profile matches the typical Level 5 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GG山鬼不识字FACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim38
Positioning35
Utility48

0–100 skill scores via Leetify.

Recent form

HOT49–45–6Last 10049%Win rateWWLLWLWWWW

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

Player DNA

Aim3.8
Aggression3.0
Utility4.8
Positioning3.5
Opening Duels0.3
Clutch2.2

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

NiKo

Plays most like NiKo 74% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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. 639ms 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

Aim3.8
Positioning3.5
Utility4.8
Mechanics4.9
Opening Duels0.8
Win Impact7.2

Composite 4.1/10 (Developing), 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-0.02−0.02
first ⅓ avg 0.00 → last ⅓ avg -0.02
Reaction time657ms−9ms
first ⅓ avg 666ms → last ⅓ avg 657ms
Headshot accuracy12.7%−1.0%
first ⅓ avg 13.7% → last ⅓ avg 12.7%

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

0.18Best rating — ancient 13–9
13–2Biggest win — dust2
4Longest win streak
W2Current streak
11–4In matches decided by ≤2 rounds
20Overtime games

Map breakdown

infernoBest map · 58% over 19trainWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
mirageB2815–1354%-0.02
dust2B2110–1148%-0.01
infernoA1911–858%-0.01
ancientA116–555%0.00
nukeD62–433%-0.01
trainD51–420%0.00
anubis—42–250%-0.02
overpass—42–250%-0.03
cache—10–10%-0.09
vertigo—10–10%-0.08

Across the last 100 tracked matches.

Lifetime stats

53,445Lifetime kills
0.80K/D
3,819Matches
46.0%Match win rate · Top 50% of Level 4 players
34.7%Headshot %
6.0%Shot accuracy
6,387MVPs
1,621Hours (in match)
5,131Bombs planted
829Bombs defused

Most-used weapons

MP79,952
AWP7,992
AK-475,196
M4A4 / M4A1-S4,986
XM10143,378
Desert Eagle2,881
P2000 / USP-S1,914
MP91,745
AUG1,649
MAC-101,631

Lifetime map wins

14,745dust2
7,812inferno
2,674nuke
2,422vertigo
449train
29office
26safehouse
20ar_shoots

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

Faceit stats

Combat

38Matches
42%Win rate
0.81Avg K/D
66.0ADR
40%Headshot %

Clutches & streaks

31%1v1 clutch win
29%1v2 clutch win
5Longest win streak

Recent Faceit resultsLWLWW

MapMatchesWin rateAvg K/DAvg kills
Dust21127%0.6310.4
Inferno757%0.9515.0
Mirage667%0.8713.0
Ancient520%1.0313.4
Nuke450%0.6613.0
Anubis450%0.8614.3
Vertigo10%0.609.0

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.

12.3%Headshot accuracy
30.4%Accuracy (enemy spotted)
36.5%Spray accuracy
72.1%Counter-strafing
11.8°Preaim
639msReaction time
26.1%T opening success
36.3%CT opening success
0.59Enemies flashed / flash
4.5%Flash assists
11.20HE damage / grenade
8.52Flashes / 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 12.3328% — below the 15% mark we flag

    Aim Training →
  2. 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 26.1399% — below the 40% mark we flag

Spend your practice time on Train

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
mirage16–140.0212%23 Jul →
inferno13–10-0.0324%13 Jul →
nuke8–130.0220%13 Jul →
mirage8–13-0.0017%13 Jul →
anubis13–100.0314%13 Jul →
mirage7–13-0.0719%12 Jul →
dust213–50.029%12 Jul →
mirage13–9-0.0311%12 Jul →
mirage13–11-0.045%12 Jul →
inferno16–14-0.0316%11 Jul →
cache4–13-0.0933%11 Jul →
mirage16–14-0.034%24 Jun →
dust29–13-0.065%24 Jun →
dust216–140.026%24 Jun →
inferno16–12-0.029%21 Jun →
mirage7–13-0.0610%1 Jun →
inferno13–90.036%1 Jun →
ancient16–14-0.0310%1 Jun →
overpass10–13-0.0420%1 Jun →
mirage16–130.055%30 May →
mirage2–13-0.0615%30 May →
inferno4–13-0.0519%30 May →
inferno13–8-0.045%29 May →
anubis4–13-0.044%29 May →
mirage7–13-0.018%29 May →
dust213–100.0914%28 May →
dust213–60.0613%20 May →
inferno5–13-0.0326%20 May →
ancient13–10-0.0315%9 May →
dust28–130.0511%14 Apr →
inferno12–12-0.0319%14 Apr →
dust24–13-0.078%10 Apr →
vertigo1–13-0.088%9 Apr →
inferno13–5-0.0410%9 Apr →
mirage13–11-0.0410%8 Apr →
inferno7–13-0.0313%6 Apr →
mirage16–13-0.039%4 Apr →
mirage13–9-0.0221%4 Apr →
mirage15–15-0.075%4 Apr →
ancient13–90.1812%3 Apr →
mirage13–80.0013%3 Apr →
overpass13–50.0217%3 Apr →
dust215–15-0.069%31 Mar →
mirage8–13-0.087%31 Mar →
inferno15–15-0.0522%30 Mar →
inferno13–8-0.039%30 Mar →
dust22–13-0.0819%30 Mar →
mirage4–13-0.1121%29 Mar →
dust211–130.007%29 Mar →
nuke13–60.056%29 Mar →
dust213–90.0511%29 Mar →
overpass13–7-0.0213%29 Mar →
anubis10–130.0129%29 Mar →
dust213–9-0.055%28 Mar →
mirage5–13-0.045%27 Mar →
inferno4–13-0.005%26 Mar →
nuke16–13-0.0210%25 Mar →
inferno13–80.057%19 Mar →
nuke6–13-0.066%16 Mar →
anubis13–7-0.0710%16 Mar →
nuke8–13-0.0612%16 Mar →
dust26–13-0.1112%15 Mar →
inferno16–12-0.0418%14 Mar →
mirage13–16-0.0312%8 Mar →
inferno11–130.0015%6 Mar →
train7–13-0.0110%11 Jan →
mirage15–150.009%10 Jan →
ancient3–13-0.038%29 Dec →
dust213–70.0022%29 Dec →
ancient5–13-0.0510%29 Dec →
dust29–130.0322%28 Dec →
train7–13-0.0212%26 Dec →
mirage4–13-0.0527%22 Dec →
dust213–80.0717%22 Dec →
dust26–13-0.0517%22 Dec →
ancient8–130.0212%14 Dec →
mirage11–13-0.0518%11 Dec →
inferno13–10-0.0124%11 Dec →
mirage13–110.058%31 Oct →
mirage16–140.039%31 Oct →
ancient13–16-0.048%30 Oct →
mirage13–60.0213%29 Oct →
mirage13–80.0122%29 Oct →
nuke2–130.0111%29 Oct →
ancient16–14-0.0013%29 Oct →
dust26–13-0.0510%28 Oct →
inferno13–50.1212%28 Oct →
inferno14–160.0314%27 Oct →
dust213–11-0.042%26 Oct →
train7–130.016%26 Oct →
overpass15–15-0.079%26 Oct →
ancient13–5-0.049%26 Oct →
train6–13-0.0417%25 Oct →
train13–50.0721%25 Oct →
dust213–20.1113%25 Oct →
mirage13–70.103%25 Oct →
ancient7–13-0.0610%23 Oct →
ancient13–60.1011%23 Oct →
mirage13–9-0.0117%23 Oct →
dust21–13-0.0426%23 Oct →

Match data via Leetify.

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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