cra1gB

cra1gB — CS2 Stats

US76561198209260109[U:1:248994381]Steam profile ↗✓ No bans

666Tracked matches36%Win rate2022Tracked since
496Hours in CS
CSDB Rating3.7 LearningClutch Specialist
Premier CS Rating14,985Blue band · top ~28.5% of ranked players (population est.)
FaceitLevel 4Top 81.0% of ranked FACEIT players
WingmanMaster Guardian II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 21 Oct 2026 (14 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 666 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 14,985 -666 14 Jun – 21 Oct · 18 days played
14,98517,815peak 17,81514 Jun21 Oct
18,136Peak Premier in tracked matches
40Days played since 2026-06-14

Premier CS Rating

  • 2,830 below peak (17,815)
  • -318 over 30 days · steady
  • Next: Purple band at 15,000 — 15 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-10-21
  • Light Blue band first seen 2026-10-21

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 Level 4 among CSDB-tracked players (n=14,630), 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 rate38.8%42.7%43.8%4.9% short
Shot accuracy5.6%11.2%12.0%6.5% short
Kill/death ratio0.970.991.020.05 short
Match win rate35.5%43.9%44.7%9.2% short

This profile sits below the typical Level 5 player on every metric we can compare.

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.GGcra1gBFACEITLevel 4STANDINGTop 81.0% of rankedPREMIER14,985 · Blue bandcsdb.gg/stats

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Performance scores

Aim46
Positioning46
Utility57

0–100 skill scores via Leetify.

Recent form

COLD39–53–8Last 10039%Win rateLWWLLLLLWL

Last 10 vs previous 10: 0pp win rate · +0.02 avg rating · +0.3pp headshot accuracy · +53ms reaction

Win rate 0pp 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

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 572ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 625ms

Last 20

  • 6–12–2 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 599ms

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 (+3.1 against its own average).

Aim4.6
Utility5.7
Positioning4.6
Opening Duels1.2
Clutch8.0

Reliable 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

iM

Plays most like iM 72% 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. 600ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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
Positioning4.6
Utility5.7
Mechanics3.3
Opening Duels2.1
Win Impact0.3

Composite 3.7/10 (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-0.01−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time611ms−40ms
first ⅓ avg 651ms → last ⅓ avg 611ms
Headshot accuracy12.5%−5.3%
first ⅓ avg 17.8% → last ⅓ avg 12.5%

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

0.28Best match rating · 9–1 · inferno, 25 Aug →
50%Best headshot accuracy · 0–10 · office, 3 Aug →
422msFastest reaction time · 13–11 · inferno, 25 Aug →
13–3Biggest win · dust2, 6 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
9–9In matches decided by ≤2 rounds
13Overtime games

Map breakdown

dust2Best map · 86% over 7officeWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
mirageD165–1131%-0.02
cacheD144–1029%-0.02
nukeC135–838%-0.01
ancientA116–555%0.00
infernoD102–820%-0.01
trainA74–357%0.01
dust2S76–186%0.01
officeD71–614%-0.02
anubisD62–433%0.01
vertigo—31–233%0.01
shelter—21–150%-0.01
fachwerk—21–150%0.06
boulder—10–10%-0.03
overpass—11–0100%-0.02

Across the last 100 tracked matches.

Lifetime stats

26,216Lifetime kills
0.97K/D
1,502Matches
35.5%Match win rate
38.8%Headshot %
5.6%Shot accuracy
2,437MVPs
496Hours (in match)
1,144Bombs planted
236Bombs defused

Most-used weapons

Lifetime map wins

2,350dust2
1,572nuke
1,227inferno
601vertigo
435train
434office
75bank
53lake

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

Faceit stats

Combat

15Matches
47%Win rate
1.01Avg K/D
81.6ADR
41%Headshot %

Clutches & streaks

60%1v1 clutch win
60%1v2 clutch win
3Longest win streak

Recent Faceit resultsLWWWL

MapMatchesWin rateAvg K/DAvg kills
Dust2475%1.0615.0
Nuke367%1.0012.7
Vertigo333%1.1613.7
Mirage30%0.6811.3
Train1100%1.1416.0
Inferno10%1.2316.0

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
35.5%Accuracy (enemy spotted)
38.7%Spray accuracy
64.6%Counter-strafing
11.7°Preaim
600msReaction time
34.7%T opening success
41.8%CT opening success
0.57Enemies flashed / flash
7.1%Flash assists
11.45HE damage / grenade
18.95Flashes / 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 12.2576% — 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 34.7314% — 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.

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
train4–13-0.0214%7 Oct →
train13–7-0.0315%7 Oct →
mirage13–8-0.048%1 Oct →
nuke7–13-0.0410%1 Oct →
ancient2–7-0.0424%30 Sept →
anubis1–8-0.0514%30 Sept →
mirage1–6-0.106%30 Sept →
cache13–160.0210%30 Sept →
mirage16–120.088%24 Sept →
anubis11–130.059%24 Sept →
inferno14–16-0.0811%19 Sept →
nuke13–11-0.0019%19 Sept →
mirage8–13-0.064%19 Sept →
cache6–12-0.0613%15 Sept →
mirage4–13-0.049%15 Sept →
inferno15–15-0.0413%14 Sept →
cache7–13-0.0410%14 Sept →
inferno8–80.015%7 Sept →
anubis13–70.0416%7 Sept →
mirage13–11-0.0314%3 Sept →
mirage15–15-0.059%31 Aug →
dust24–13-0.0210%30 Aug →
inferno15–15-0.0110%29 Aug →
cache10–13-0.0318%29 Aug →
mirage4–13-0.0514%29 Aug →
dust213–11-0.0414%29 Aug →
cache12–12-0.0310%27 Aug →
inferno13–11-0.0317%25 Aug →
inferno9–10.2814%25 Aug →
office3–13-0.0514%21 Aug →
anubis13–60.0620%21 Aug →
ancient15–150.0612%21 Aug →
nuke11–13-0.0019%20 Aug →
mirage9–130.0416%19 Aug →
nuke0–30.0340%19 Aug →
mirage2–13-0.048%19 Aug →
nuke8–13-0.0411%12 Aug →
mirage9–13-0.0111%12 Aug →
train13–110.089%12 Aug →
train13–40.0622%12 Aug →
dust213–30.0419%6 Aug →
ancient6–13-0.0617%6 Aug →
inferno7–13-0.0514%6 Aug →
office0–10-0.1950%3 Aug →
vertigo13–60.0420%3 Aug →
vertigo11–130.0018%3 Aug →
inferno4–13-0.0218%30 Jul →
office12–120.0218%26 Jul →
mirage6–13-0.047%26 Jul →
train13–9-0.0026%26 Jul →
inferno3–9-0.1416%26 Jul →
cache4–90.015%18 Jul →
cache11–130.0112%18 Jul →
ancient13–7-0.0012%18 Jul →
office10–130.0723%18 Jul →
dust216–13-0.038%18 Jul →
cache6–130.0116%18 Jul →
nuke13–9-0.0327%16 Jul →
ancient9–130.0113%16 Jul →
cache6–13-0.1218%16 Jul →
dust216–120.1018%16 Jul →
nuke16–13-0.047%15 Jul →
anubis5–13-0.0216%15 Jul →
cache13–90.029%15 Jul →
shelter13–100.0250%14 Jul →
fachwerk13–50.0838%14 Jul →
ancient16–130.027%13 Jul →
ancient13–110.0117%12 Jul →
boulder10–13-0.0325%12 Jul →
fachwerk10–130.0317%12 Jul →
shelter8–13-0.0314%10 Jul →
office13–6-0.0814%8 Jul →
office7–13-0.0348%8 Jul →
mirage13–11-0.0112%6 Jul →
nuke12–16-0.0212%6 Jul →
ancient13–10-0.018%6 Jul →
mirage13–70.0219%6 Jul →
anubis5–13-0.0422%6 Jul →
cache13–8-0.0022%1 Jul →
cache9–13-0.0416%1 Jul →
mirage11–130.0913%29 Jun →
inferno11–13-0.0513%29 Jun →
nuke13–110.0511%28 Jun →
nuke6–90.0311%28 Jun →
nuke4–13-0.0826%28 Jun →
vertigo3–13-0.0222%28 Jun →
office5–120.1015%27 Jun →
ancient13–90.0317%26 Jun →
ancient13–100.0223%24 Jun →
dust213–70.0024%24 Jun →
cache13–110.019%24 Jun →
overpass13–3-0.0213%18 Jun →
nuke13–7-0.0318%18 Jun →
train11–13-0.0115%18 Jun →
cache13–7-0.0220%18 Jun →
nuke7–9-0.0119%18 Jun →
train12–12-0.0228%17 Jun →
dust216–130.0013%14 Jun →
mirage4–13-0.0418%14 Jun →
ancient10–13-0.0212%14 Jun →

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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