Kevlor

Kevlor — CS2 Stats

DE76561198018415178[U:1:58149450]Steam profile ↗VAC banned

95Tracked matches53%Win rate2026Tracked since
50Hours in CS
CSDB Rating3.3 LearningPositional Player
Premier CS Rating12,015Blue band · top ~44.2% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Sep 2026 (46 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 12,015 → 12,015
+1Tracked matches · now 95
−3.3ppWin rate · 56.7% → 53.3%

Rating over time

Premier CS Rating: 12,015 +421 9 Aug – 2 Sept · 11 days played
11,59413,478peak 13,4789 Aug2 Sept
13,478Peak Premier in tracked matches
25Days played since 2026-07-23

Premier CS Rating

  • 1,463 below peak (13,478)
  • +421 over 30 days · improving
  • Next: Purple band at 15,000 — 2,985 to go
  • Reached: Blue band · Light Blue band
  • Blue band first seen 2026-09-02
  • Light Blue band first seen 2026-09-02

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 Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate45.6%42.0%44.3%above
Shot accuracy7.8%9.6%11.9%4.1% short
Kill/death ratio0.730.981.030.30 short
Match win rate31.4%43.8%45.2%13.8% short

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

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

Share this profile

CSDB.GGKevlorPREMIER12,015 · Blue bandcsdb.gg/stats

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Performance scores

Aim41
Positioning34
Utility22

0–100 skill scores via Leetify.

Recent form

COLD51–43–1Last 9554%Win rateLLWLLLWLLW

Last 10 vs previous 10: −40pp win rate · +0.02 avg rating · +5.8pp headshot accuracy · −92ms reaction

Win rate down 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 597ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 16%
  • Avg reaction 555ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 601ms

Newest first, from the last 95 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.5 against its own average).

Aim4.1
Utility2.2
Positioning3.4
Opening Duels0.0

Strong CT-side openerLimited 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

iM

Plays most like iM 86% 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

T-side openings. Opening success drops from 34% on CT to 16% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 605ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% 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

Aim4.1
Positioning3.4
Utility2.2
Mechanics3.7
Opening Duels0.5
Win Impact6.1

Composite 3.3/10 (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-0.02+0.03
first ⅓ avg -0.05 → last ⅓ avg -0.02
Reaction time609ms−95ms
first ⅓ avg 704ms → last ⅓ avg 609ms
Headshot accuracy12.5%−4.8%
first ⅓ avg 17.3% → last ⅓ avg 12.5%

Rolling 5-match average across the last 95 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.13Best match rating · 9–13 · inferno, 18 Aug →
50%Best headshot accuracy · 10–13 · cache, 31 Jul →
344msFastest reaction time · 0–4 · inferno, 17 Aug →
13–0Biggest win · cache, 6 Aug →

Across the last 95 tracked matches.

Highlights

6Longest win streak
L2Current streak
6–4In matches decided by ≤2 rounds
2Overtime games

Map breakdown

ancientBest map · 67% over 15dust2Weakest map · 30% over 10
MapGradePlayedRecordWin rateAvg rating
cacheB1910–953%-0.05
infernoB179–853%-0.02
ancientS1510–567%-0.04
anubisA116–555%-0.06
dust2D103–730%-0.05
mirageD103–730%-0.05
vertigo—43–175%-0.06
fachwerk—31–233%-0.05
train—22–0100%-0.01
boulder—22–0100%-0.08
nuke—11–0100%-0.05
shelter—11–0100%-0.03

Across the last 95 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

2,660Lifetime kills
0.73K/D
172Matches
31.4%Match win rate
45.6%Headshot % · Top 50% of Blue band
7.8%Shot accuracy
165MVPs
50Hours (in match)
62Bombs planted
16Bombs defused

Most-used weapons

Lifetime map wins

169inferno
94dust2
47vertigo
26train
15nuke
3ar_shoots
2safehouse
1cbble

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

11.4%Headshot accuracy
33.2%Accuracy (enemy spotted)
30.4%Spray accuracy
66.5%Counter-strafing
9.8°Preaim
605msReaction time
15.7%T opening success
34.1%CT opening success
0.30Enemies flashed / flash
2.6%Flash assists
8.08HE damage / grenade
1.62Flashes / 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 11.3952% — 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 0.2953 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 15.7259% — below the 40% mark we flag

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.

30% win rate across 10 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
cache11–13-0.0215%9 Sept →
dust23–13-0.0220%19 Aug →
inferno13–100.0212%18 Aug →
inferno9–130.1310%18 Aug →
mirage3–13-0.0516%17 Aug →
inferno0–4-0.0033%17 Aug →
mirage13–20.0412%17 Aug →
inferno11–13-0.0117%17 Aug →
inferno7–13-0.0816%16 Aug →
ancient13–10-0.048%15 Aug →
mirage13–11-0.088%15 Aug →
ancient10–13-0.026%15 Aug →
ancient9–3-0.039%15 Aug →
train13–9-0.0210%15 Aug →
train13–3-0.019%14 Aug →
inferno13–60.085%14 Aug →
nuke13–2-0.055%13 Aug →
mirage0–7-0.0129%13 Aug →
ancient5–13-0.047%13 Aug →
inferno13–6-0.0214%13 Aug →
cache12–16-0.0816%13 Aug →
mirage5–13-0.0217%12 Aug →
cache13–7-0.0510%11 Aug →
fachwerk4–8-0.1014%9 Aug →
fachwerk13–3-0.038%9 Aug →
anubis13–7-0.078%9 Aug →
inferno13–30.0311%9 Aug →
cache11–13-0.036%9 Aug →
anubis16–120.0313%9 Aug →
inferno13–100.019%9 Aug →
dust213–100.0118%9 Aug →
dust211–13-0.1217%8 Aug →
ancient3–13-0.0916%8 Aug →
anubis8–13-0.099%8 Aug →
dust26–13-0.0820%8 Aug →
dust213–90.0022%8 Aug →
inferno7–13-0.0613%7 Aug →
ancient13–3-0.064%7 Aug →
inferno13–7-0.0514%7 Aug →
cache5–13-0.0315%7 Aug →
mirage9–13-0.136%6 Aug →
cache13–00.0918%6 Aug →
ancient13–9-0.0512%6 Aug →
dust23–13-0.1011%6 Aug →
ancient13–10.067%5 Aug →
boulder13–4-0.047%5 Aug →
boulder1–1-0.120%5 Aug →
vertigo6–13-0.106%5 Aug →
cache13–2-0.087%5 Aug →
mirage13–6-0.039%5 Aug →
cache13–9-0.0415%5 Aug →
cache13–4-0.087%4 Aug →
anubis13–4-0.058%4 Aug →
ancient13–11-0.0120%4 Aug →
mirage2–13-0.0514%2 Aug →
ancient8–13-0.0619%2 Aug →
dust29–13-0.0725%1 Aug →
dust22–9-0.0918%1 Aug →
cache13–9-0.0015%1 Aug →
cache7–13-0.1213%1 Aug →
fachwerk6–13-0.027%1 Aug →
inferno3–13-0.0722%31 Jul →
mirage6–13-0.148%31 Jul →
anubis13–8-0.093%31 Jul →
shelter13–2-0.039%31 Jul →
vertigo13–9-0.0315%31 Jul →
vertigo13–40.0119%31 Jul →
anubis5–13-0.1017%31 Jul →
cache10–13-0.1450%31 Jul →
cache7–13-0.0527%30 Jul →
cache5–13-0.1114%30 Jul →
cache13–6-0.0513%30 Jul →
inferno13–8-0.0914%30 Jul →
anubis13–8-0.0913%30 Jul →
inferno13–5-0.0120%28 Jul →
anubis5–13-0.084%28 Jul →
cache13–11-0.0814%28 Jul →
anubis13–11-0.0115%28 Jul →
inferno9–13-0.0817%28 Jul →
cache13–90.018%28 Jul →
dust25–13-0.0725%28 Jul →
cache13–7-0.0325%27 Jul →
inferno13–11-0.0418%27 Jul →
dust213–30.0518%27 Jul →
cache7–13-0.065%27 Jul →
anubis1–130.007%27 Jul →
mirage8–130.0119%27 Jul →
ancient13–8-0.0428%27 Jul →
vertigo13–5-0.1112%27 Jul →
ancient13–10-0.0220%27 Jul →
ancient13–6-0.058%26 Jul →
ancient5–13-0.0722%26 Jul →
ancient13–8-0.0526%25 Jul →
inferno4–9-0.0719%25 Jul →
anubis12–12-0.0615%23 Jul →

Match data via Leetify.

Recent teammates

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

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