死于 awesome

死于 awesome — CS2 Stats

GS76561198178912403[U:1:218646675]Steam profile ↗✓ No bans

2,283Tracked matches52%Win rate2020Tracked since
6,545Hours in CS44Hrs last 2 wks
CSDB Rating5.8 SolidPositional Player
Ladder ranks via Leetify
Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. Today is the first observation — history builds from here and cannot be backfilled. Come back after the next session and the change shows above.

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Performance scores

Aim65
Positioning75
Utility34

0–100 skill scores via Leetify.

Recent form

STEADY47449Last 10047%Win rateLWLLWWLWLL

Last 10 vs previous 10: −10pp win rate · +0.03 avg rating · +7.9pp headshot accuracy · −30ms 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

  • 23 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 17%
  • Avg reaction 577ms

Last 10

  • 46 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 22%
  • Avg reaction 549ms

Last 20

  • 992 · 45% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 18%
  • Avg reaction 564ms

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 PlayerPositioning stands above the rest of this profile (+2.4 against its own average).

Aim6.5
Utility3.4
Positioning7.5
Opening Duels4.6
Clutch5.0

Limited utility dependence

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

s1mple

Plays most like s1mple 76% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 563ms 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

Aim6.5
Positioning7.5
Utility3.4
Mechanics5.2
Opening Duels5.2
Win Impact5.6

Composite 5.8/10 (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 rating0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg 0.00
Reaction time566ms−32ms
first ⅓ avg 597ms → last ⅓ avg 566ms
Headshot accuracy17.4%−1.4%
first ⅓ avg 18.9% → last ⅓ avg 17.4%

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 · 13–1 · train, 18 Sept
48%Best headshot accuracy · 13–11 · dust2, 16 Sept
414msFastest reaction time · 2–13 · office, 9 Sept
13–1Biggest win · train, 18 Sept

Across the last 100 tracked matches.

Highlights

4Longest win streak
57In matches decided by ≤2 rounds

Map breakdown

officeBest map · 80% over 5infernoWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
mirageC2381535%0.00
dust2C1981142%-0.01
cacheA127558%0.01
nukeD124833%0.01
infernoD92722%-0.01
anubisC52340%0.01
officeS54180%0.02
ancient440100%0.01
train330100%0.07
vertigo32167%0.03
overpass21150%0.01
italy110100%0.04
fachwerk110100%0.03
shelter1010%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

81,079Lifetime kills
0.92K/D
5,065Matches
38.4%Match win rate
45.3%Headshot % · Top 50% of tracked players
13.1%Shot accuracy · Top 50% of tracked players
14,724MVPs
1,543Hours (in match)
4,000Bombs planted
1,031Bombs defused

Most-used weapons

AK-4723,328
AWP12,613
SG 5534,722
XM10142,314
SSG 081,968
FAMAS1,436

Lifetime map wins

5,289dust2
4,408nuke
3,258inferno
2,600vertigo
1,458train
941office
426cbble
103italy

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

Faceit stats

Combat

57Matches
54%Win rate
0.99Avg K/D
79.9ADR
35%Headshot %

Clutches & streaks

45%1v1 clutch win
26%1v2 clutch win
6Longest win streak

Recent Faceit resultsWWLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage1753%0.9815.3
Dust21164%0.9913.0
Inferno743%0.9915.4
Anubis667%1.2917.7
Ancient450%0.9416.5
Nuke250%1.2829.0
Cache250%0.9012.5
Overpass10%0.5516.0

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.

18.3%Headshot accuracy
33.5%Accuracy (enemy spotted)
34.1%Spray accuracy
73.3%Counter-strafing
9.5°Preaim
563msReaction time
48.8%T opening success
53.0%CT opening success
0.61Enemies flashed / flash
4.9%Flash assists
10.63HE damage / grenade
2.42Flashes / 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. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 2.4212 — below the 4 mark we flag

    Grenade Lineups
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.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
inferno5–130.029%18 Sept
dust213–10-0.0118%18 Sept
anubis8–130.0225%18 Sept
inferno4–13-0.0526%18 Sept
train13–10.155%18 Sept
dust213–70.0722%18 Sept
dust28–130.0121%17 Sept
dust213–11-0.0048%16 Sept
mirage9–130.0032%16 Sept
cache4–13-0.0211%16 Sept
mirage13–7-0.063%16 Sept
mirage7–13-0.0614%16 Sept
nuke7–13-0.075%16 Sept
mirage12–12-0.0221%16 Sept
anubis13–20.0611%15 Sept
inferno12–120.0120%15 Sept
vertigo13–9-0.0115%14 Sept
inferno7–13-0.0716%14 Sept
nuke13–80.1218%14 Sept
inferno13–11-0.0115%14 Sept
nuke5–130.0311%14 Sept
office13–5-0.0518%13 Sept
nuke6–130.0112%13 Sept
dust212–12-0.0830%13 Sept
ancient13–90.009%12 Sept
mirage6–130.0633%12 Sept
mirage4–13-0.0215%12 Sept
cache13–10-0.0318%12 Sept
dust213–90.0219%12 Sept
nuke13–10.1210%12 Sept
dust25–13-0.0820%12 Sept
cache13–9-0.0312%11 Sept
mirage9–13-0.0313%11 Sept
vertigo13–60.0916%11 Sept
dust213–7-0.0013%11 Sept
mirage12–120.1023%9 Sept
office2–130.0523%9 Sept
dust212–12-0.0216%9 Sept
ancient13–40.059%8 Sept
mirage13–70.0521%8 Sept
mirage3–13-0.0418%8 Sept
mirage13–10.0313%8 Sept
nuke13–2-0.013%8 Sept
nuke10–13-0.0310%7 Sept
mirage13–100.1326%7 Sept
cache3–130.079%6 Sept
dust25–13-0.1011%6 Sept
mirage13–50.0410%5 Sept
mirage7–13-0.0714%5 Sept
mirage13–6-0.0114%5 Sept
dust211–130.0010%28 Aug
anubis13–6-0.0013%28 Aug
inferno5–13-0.0210%28 Aug
dust23–130.0223%28 Aug
dust24–13-0.0313%28 Aug
nuke6–13-0.0418%27 Aug
mirage13–80.0213%27 Aug
mirage6–13-0.0233%27 Aug
office13–7-0.0129%27 Aug
dust211–2-0.0215%27 Aug
dust212–120.0313%27 Aug
cache13–7-0.0213%27 Aug
mirage11–130.0211%26 Aug
italy13–70.0418%26 Aug
cache13–50.0722%26 Aug
cache10–130.0314%26 Aug
mirage4–13-0.0823%24 Aug
dust27–130.0520%24 Aug
mirage0–9-0.0714%24 Aug
nuke13–100.0112%24 Aug
nuke12–12-0.0325%24 Aug
cache13–7-0.0516%23 Aug
mirage8–130.0026%23 Aug
cache13–70.0414%23 Aug
inferno7–130.0526%17 Aug
nuke11–130.0512%16 Aug
anubis12–120.0119%16 Aug
cache12–12-0.0518%3 Aug
dust28–5-0.0029%3 Aug
office13–100.1424%28 Jul
inferno13–7-0.0010%28 Jul
mirage9–13-0.058%28 Jul
office13–11-0.0414%27 Jul
vertigo11–130.0124%27 Jul
overpass13–10-0.0412%25 Jul
ancient13–11-0.0221%25 Jul
dust213–11-0.0819%25 Jul
train13–90.0217%25 Jul
overpass9–130.0616%17 Jul
dust211–13-0.0138%16 Jul
ancient13–50.0111%16 Jul
train13–80.0219%16 Jul
inferno11–13-0.0421%15 Jul
cache8–130.0720%15 Jul
nuke3–5-0.0326%15 Jul
cache13–80.0629%15 Jul
anubis7–13-0.066%11 Jul
fachwerk13–90.0317%9 Jul
mirage13–70.0925%9 Jul
shelter10–130.0413%9 Jul

Match data via Leetify.

Recent teammates

Milestones

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