KRAT

KRAT — CS2 Stats

76561197997049282[U:1:36783554]Steam profile ↗✓ No bans

1,224Tracked matches67%Win rate2020Tracked since
3,356Hours in CS
CSDB Rating5.4 DevelopingOpening Duellist
FaceitLevel 6 · 1,314 ELOTop 54.0% of ranked FACEIT players
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 14,999 -3,547 2 Jan – 18 Jun · 24 days played
10,67218,546peak 18,5462 Jan18 Jun
18,546Peak Premier in tracked matches
1,314Highest Faceit ELO seen on CSDB
50Days played since 2025-12-25

Faceit ELO

  • At peak — 1,314
  • Next: Level 7 at 1,351 — 37 to go
  • Reached: Level 6 · Level 5 · Level 4 · Level 3

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 6 among CSDB-tracked players (n=13,496), 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 6 medianLevel 7 medianvs Level 7
Headshot rate43.9%44.8%45.7%1.8% short
Shot accuracy19.2%12.4%12.7%above
Kill/death ratio1.111.031.05above
Match win rate43.8%45.2%45.7%1.9% short

This profile matches the typical Level 7 player on 2 of 4 comparable metrics.

Widest gap: Match win rate. That is the metric furthest from the Level 7 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGKRATFACEITLevel 6 · 1,314 ELOSTANDINGTop 54.0% of rankedPEAK ELO1,314csdb.gg/stats

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Performance scores

Aim73
Positioning54
Utility28

0–100 skill scores via Leetify.

Recent form

STEADY53–45–2Last 10053%Win rateLWLWWLWLLW

Last 10 vs previous 10: −10pp win rate · −0.00 avg rating · −3.2pp headshot accuracy · +62ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 10%
  • Avg reaction 564ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 12%
  • Avg reaction 583ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 552ms

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: Opening Duellist — Winning opening duels is what stands out in this profile (+1.1 against its own average). How often you WIN the first duel — CSDB cannot yet see how often you take it.

Aim7.3
Utility2.8
Positioning5.4
Opening Duels5.9
Clutch5.2

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 90% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower positioning profile; lower utility contribution.

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. 561ms 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

Aim7.3
Positioning5.4
Utility2.8
Mechanics5.2
Opening Duels5.7
Win Impact10.0

Composite 5.4/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.03
first ⅓ avg -0.01 → last ⅓ avg 0.02
Reaction time572ms−23ms
first ⅓ avg 595ms → last ⅓ avg 572ms
Headshot accuracy13.9%−1.2%
first ⅓ avg 15.1% → last ⅓ avg 13.9%

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

0.35Best match rating · 9–1 · nuke, 23 Feb →
37%Best headshot accuracy · 13–4 · ancient, 7 Mar →
398msFastest reaction time · 13–5 · anubis, 28 Sept →
13–0Biggest win · ancient, 10 Jun →

Across the last 100 tracked matches.

Highlights

8Longest win streak
5–4In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 68% over 25dust2Weakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
infernoS2517–868%0.03
nukeA2414–1058%0.04
ancientC146–843%0.01
anubisA106–460%0.02
dust2C83–538%-0.00
mirageC73–443%0.04
overpassB63–350%0.01
cache—21–150%-0.03
train—20–20%-0.05
cache_b—10–10%0.02
vertigo—10–10%-0.08

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

176,299Lifetime kills
1.11K/D · Top 50% of Level 6 players
6,419Matches
43.8%Match win rate
43.9%Headshot %
19.2%Shot accuracy · Top 5% of Level 6 players
17,298MVPs
3,356Hours (in match)
3,291Bombs planted
1,450Bombs defused

Most-used weapons

AK-4767,140
AWP23,256
P2504,778
FAMAS4,096
Knife2,553
MAC-102,436

Lifetime map wins

18,588inferno
10,479dust2
7,557nuke
2,746train
2,009vertigo
1,383cbble
51aztec
36militia

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

Faceit stats

Combat

1,280Matches
50%Win rate
1.05Avg K/D
79.7ADR
44%Headshot %

Clutches & streaks

46%1v1 clutch win
18%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Inferno9751%0.9815.3
Ancient6448%1.0115.8
Nuke6045%0.9415.6
Anubis4959%1.0116.3
Mirage1553%1.1415.9
Vertigo1346%1.0017.2
Dust2933%0.8013.4
Train714%0.8615.1

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.

13.6%Headshot accuracy
42.1%Accuracy (enemy spotted)
42.6%Spray accuracy
73.4%Counter-strafing
11.1°Preaim
561msReaction time
47.5%T opening success
57.8%CT opening success
0.28Enemies flashed / flash
5.9%Flash assists
8.74HE damage / grenade
2.96Flashes / 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 13.5991% — 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 0.2791 — below the 0.5 mark we flag

    Grenade Lineups →
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.

38% win rate across 8 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
cache7–13-0.054%5 Oct →
mirage16–130.0513%4 Oct →
dust25–13-0.0510%30 Sept →
inferno13–30.0812%30 Sept →
anubis13–5-0.048%28 Sept →
anubis4–130.0220%17 Sept →
dust213–30.0215%12 Sept →
dust28–130.0722%9 Sept →
nuke5–13-0.0312%25 Aug →
nuke13–8-0.018%24 Aug →
ancient9–13-0.057%24 Aug →
inferno10–130.0415%23 Aug →
nuke13–10-0.0321%22 Aug →
ancient6–130.0113%22 Aug →
ancient13–70.0520%22 Aug →
cache13–3-0.0014%19 Aug →
ancient13–7-0.0316%16 Aug →
overpass13–40.0119%18 Jun →
ancient5–13-0.0113%18 Jun →
inferno13–110.0819%17 Jun →
nuke13–60.1022%17 Jun →
anubis13–80.0217%17 Jun →
anubis16–120.0716%10 Jun →
ancient13–00.1619%10 Jun →
ancient13–10-0.0313%9 Jun →
inferno13–7-0.065%9 Jun →
nuke13–40.0013%9 Jun →
nuke13–16-0.0113%1 Jun →
inferno13–7-0.057%1 Jun →
inferno9–70.0814%1 Jun →
anubis16–120.0211%31 Mar →
ancient11–130.027%31 Mar →
ancient8–130.0419%30 Mar →
inferno13–110.1116%30 Mar →
nuke13–50.0014%30 Mar →
nuke13–50.1618%29 Mar →
anubis16–140.0717%29 Mar →
mirage7–130.0915%26 Mar →
mirage13–20.0315%26 Mar →
inferno2–13-0.0829%16 Mar →
nuke7–130.0117%8 Mar →
nuke7–130.0618%7 Mar →
inferno13–110.0718%7 Mar →
nuke13–100.0725%7 Mar →
ancient13–40.0237%7 Mar →
anubis13–10.0723%7 Mar →
mirage13–80.1224%3 Mar →
nuke15–150.0723%3 Mar →
anubis4–13-0.0816%2 Mar →
inferno16–120.1120%1 Mar →
inferno13–90.0722%1 Mar →
dust23–130.0012%27 Feb →
anubis7–130.0317%27 Feb →
nuke13–80.0518%26 Feb →
inferno13–80.1522%26 Feb →
mirage12–160.0725%25 Feb →
ancient9–130.0115%25 Feb →
inferno13–70.1121%25 Feb →
inferno13–50.0919%23 Feb →
nuke9–10.3514%23 Feb →
inferno5–90.0635%23 Feb →
anubis8–130.0124%3 Feb →
nuke8–13-0.0116%25 Jan →
ancient13–10-0.0113%21 Jan →
cache_b10–130.0217%21 Jan →
overpass7–13-0.0216%20 Jan →
overpass0–13-0.0014%19 Jan →
inferno11–13-0.0113%19 Jan →
dust213–90.0020%18 Jan →
nuke13–70.057%18 Jan →
train15–15-0.0514%18 Jan →
nuke9–13-0.0314%15 Jan →
inferno13–8-0.0216%13 Jan →
mirage7–13-0.0620%13 Jan →
inferno13–6-0.0712%12 Jan →
nuke8–13-0.0531%12 Jan →
nuke13–9-0.0416%11 Jan →
inferno13–30.0418%11 Jan →
inferno13–100.0219%11 Jan →
inferno13–10-0.0511%10 Jan →
nuke13–10.1927%10 Jan →
overpass6–130.0417%10 Jan →
train2–13-0.0414%9 Jan →
inferno10–13-0.0120%9 Jan →
ancient7–13-0.044%9 Jan →
overpass13–70.0413%9 Jan →
inferno10–13-0.0112%9 Jan →
nuke12–16-0.0112%6 Jan →
inferno8–13-0.0513%6 Jan →
nuke13–70.0921%6 Jan →
dust213–8-0.0023%4 Jan →
inferno11–13-0.0513%4 Jan →
ancient11–130.0211%3 Jan →
dust210–13-0.0117%3 Jan →
nuke8–13-0.0116%3 Jan →
dust29–13-0.0410%3 Jan →
overpass13–10-0.0114%2 Jan →
nuke13–10.0121%2 Jan →
vertigo6–13-0.085%27 Dec →
mirage5–13-0.054%25 Dec →

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 →

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