lokenslok

lokenslok — CS2 Stats

EE76561198077045826[U:1:116780098]Steam profile ↗✓ No bans

885Tracked matches43%Win rate2020Tracked since
3,700Hours in CS
CSDB Rating5.0 DevelopingSupport
FaceitLevel 6Top 54.0% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 17,219 +2,220 2 Mar – 28 Jun · 31 days played
14,99920,420peak 20,4202 Mar28 Jun
20,420Peak Premier in tracked matches
45Days played since 2025-01-29

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Compare periods

Last 30 days vs previous 30

No matches recorded between 7 Sep 2026 and 8 Oct 2026.

Measured 7 Sep 2026 → 8 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Level 6 among CSDB-tracked players (n=12,879), 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 rate36.9%44.8%45.7%8.8% short
Shot accuracy19.3%12.4%12.7%above
Kill/death ratio0.941.031.050.11 short
Match win rate45.3%45.2%45.7%meets

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

Widest gap: Headshot 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.GGlokenslokFACEITLevel 6STANDINGTop 54.0% of rankedcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim59
Positioning49
Utility68

0–100 skill scores via Leetify.

Recent form

STEADY45–50–5Last 10045%Win rateWLLTLTWWWW

Last 10 vs previous 10: +10pp win rate · +0.02 avg rating · −1.8pp headshot accuracy · −60ms 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

  • 1–3–1 · 20% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 13%
  • Avg reaction 533ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 566ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 14%
  • Avg reaction 596ms

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: Support — Utility contribution stands above the rest of this profile (+2.8 against its own average).

Aim5.9
Utility6.8
Positioning4.9
Opening Duels2.6
Clutch1.8

Effective flashes

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

NiKo

Plays most like NiKo 74% 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

Strengths

Flashes. 0.78 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 588ms 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

Aim5.9
Positioning4.9
Utility6.8
Mechanics5.9
Opening Duels1.3
Win Impact2.6

Composite 5.0/10 (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 rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time595ms−41ms
first ⅓ avg 635ms → last ⅓ avg 595ms
Headshot accuracy15.5%−0.4%
first ⅓ avg 15.9% → last ⅓ avg 15.5%

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

0.11Best match rating · 13–8 · ancient, 26 Oct →
42%Best headshot accuracy · 13–7 · inferno, 11 Oct →
438msFastest reaction time · 10–13 · inferno, 1 Jan →
13–3Biggest win · nuke, 15 Feb →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–8In matches decided by ≤2 rounds
16Overtime games

Map breakdown

nukeBest map · 60% over 15ancientWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2B2413–1154%0.00
infernoB2411–1346%-0.00
mirageC166–1038%-0.01
nukeA159–660%-0.00
ancientD61–517%-0.01
overpassB63–350%0.01
trainC52–340%-0.01
anubis—30–30%-0.00
cache—10–10%0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

150,813Lifetime kills
0.94K/D
7,555Matches
45.3%Match win rate · Top 50% of Level 6 players
36.9%Headshot %
19.3%Shot accuracy · Top 5% of Level 6 players
18,399MVPs
3,700Hours (in match)
9,150Bombs planted
1,871Bombs defused

Most-used weapons

AK-4748,152
AWP14,878
P2505,263
FAMAS3,278
Knife3,006
UMP-452,879

Lifetime map wins

17,000inferno
12,755dust2
6,600nuke
5,335train
1,961cbble
1,261vertigo
342office
127aztec

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

Faceit stats

Combat

2,630Matches
49%Win rate
1.05Avg K/D
81.2ADR
34%Headshot %

Clutches & streaks

29%1v1 clutch win
24%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Dust21638%0.8513.3
Inferno1346%0.9215.2
Nuke838%0.8815.0
Mirage667%0.8017.2
Overpass560%0.6915.2
Cache520%1.0618.4
Train333%1.0916.0
Vertigo20%1.1016.0

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.

15.3%Headshot accuracy
32.8%Accuracy (enemy spotted)
33.5%Spray accuracy
76.6%Counter-strafing
9.5°Preaim
588msReaction time
30.4%T opening success
40.2%CT opening success
0.78Enemies flashed / flash
12.1%Flash assists
14.93HE damage / grenade
8.13Flashes / 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. 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 30.414% — below the 40% mark we flag

Spend your practice time on Ancient

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–90.0823%21 Aug →
nuke11–130.058%20 Aug →
cache13–160.0615%20 Aug →
ancient15–15-0.0414%20 Aug →
dust27–13-0.048%28 Jun →
overpass15–150.038%21 Jun →
nuke13–8-0.0516%21 Jun →
dust216–14-0.0413%24 May →
mirage13–60.0415%15 Apr →
overpass16–140.0416%19 Mar →
dust213–5-0.039%19 Mar →
inferno5–13-0.0418%19 Mar →
inferno5–130.0220%8 Mar →
mirage5–13-0.0312%18 Feb →
dust21–130.0319%18 Feb →
nuke13–30.0518%15 Feb →
inferno11–13-0.0118%15 Feb →
nuke10–3-0.068%15 Feb →
overpass13–16-0.0517%14 Feb →
inferno13–60.0813%14 Feb →
mirage7–13-0.0012%14 Feb →
dust213–60.0217%14 Feb →
dust213–80.0712%14 Feb →
inferno8–130.0415%8 Feb →
nuke7–13-0.0124%8 Feb →
dust213–60.0231%8 Feb →
anubis5–13-0.0112%25 Jan →
dust28–13-0.0312%10 Jan →
inferno10–13-0.0328%1 Jan →
mirage11–130.0114%1 Jan →
inferno13–50.0719%1 Jan →
mirage7–130.0216%1 Jan →
nuke13–60.0714%28 Dec →
nuke8–13-0.0113%27 Dec →
overpass13–40.0223%27 Dec →
dust211–130.0321%21 Dec →
dust213–50.0416%21 Dec →
nuke14–16-0.0215%22 Nov →
ancient8–13-0.0314%22 Nov →
dust22–13-0.0817%22 Nov →
train13–70.0120%22 Nov →
inferno13–8-0.0614%21 Nov →
inferno16–14-0.0413%16 Nov →
dust213–60.0114%16 Nov →
ancient4–130.0213%16 Nov →
nuke13–50.0624%16 Nov →
dust28–130.0127%16 Nov →
overpass6–130.0517%16 Nov →
nuke10–13-0.0522%16 Nov →
inferno4–13-0.0615%16 Nov →
overpass13–11-0.0215%15 Nov →
mirage8–130.0212%15 Nov →
nuke13–10-0.0516%15 Nov →
train8–130.0215%1 Nov →
inferno13–8-0.0020%26 Oct →
ancient13–80.1119%26 Oct →
mirage15–150.0010%26 Oct →
inferno13–7-0.0142%11 Oct →
mirage8–13-0.0121%11 Oct →
inferno16–14-0.0014%27 Jul →
train8–13-0.0218%10 Jul →
nuke13–100.0114%10 Jul →
inferno11–130.0316%10 Jul →
mirage9–13-0.057%27 Jun →
mirage0–13-0.0910%14 Jun →
dust23–13-0.0820%14 Jun →
ancient1–13-0.0917%22 Apr →
dust213–50.068%20 Apr →
inferno13–4-0.0110%18 Apr →
mirage16–14-0.029%18 Apr →
inferno3–13-0.0616%18 Apr →
dust25–13-0.0214%18 Apr →
mirage13–9-0.0228%13 Apr →
inferno14–16-0.0111%13 Apr →
anubis10–13-0.0015%6 Apr →
nuke13–3-0.0112%6 Apr →
dust213–16-0.0315%6 Apr →
mirage13–70.0118%6 Apr →
dust213–100.0123%6 Apr →
inferno13–80.0119%4 Apr →
dust211–130.0318%4 Apr →
nuke4–13-0.0920%29 Mar →
dust213–90.0215%23 Mar →
inferno13–8-0.0124%23 Mar →
mirage13–80.0417%16 Mar →
train9–13-0.0410%16 Mar →
dust29–130.0014%15 Mar →
inferno12–12-0.079%4 Mar →
dust213–10-0.0323%4 Mar →
train13–10-0.0018%4 Mar →
inferno10–130.0213%4 Mar →
inferno13–110.0310%2 Mar →
mirage16–12-0.0227%2 Mar →
inferno15–150.0213%2 Mar →
ancient6–13-0.0411%2 Mar →
anubis3–130.0029%1 Mar →
dust216–13-0.0123%9 Feb →
inferno8–130.0211%9 Feb →
dust213–100.0713%1 Feb →
mirage6–13-0.0711%29 Jan →

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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