MrVilsa

MrVilsa — CS2 Stats

DE76561198131620528[U:1:171354800]Steam profile ↗✓ No bans

266Tracked matches44%Win rate2023Tracked since
599Hours in CS5Hrs last 2 wks
CSDB Rating3.9 LearningPositional Player
Premier CS Rating9,652Light Blue band · top ~56.6% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Oct 2026 (2 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 9,652 +2,006 21 Mar – 1 Oct · 30 days played
7,64612,302peak 12,30221 Mar1 Oct
12,336Peak Premier in tracked matches
51Days played since 2026-03-21

Premier CS Rating

  • 2,650 below peak (12,302)
  • -1,209 over 90 days
  • Next: Blue band at 10,000 — 348 to go
  • Reached: Blue band · Light Blue band

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 Light Blue band among CSDB-tracked players (n=8,820), 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 playerLight Blue band medianBlue band medianvs Blue band
Headshot rate26.8%39.9%42.0%15.1% short
Shot accuracy10.6%7.0%9.6%above
Kill/death ratio0.900.920.980.08 short
Match win rate37.1%42.3%43.8%6.7% short

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

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

Share this profile

CSDB.GGMrVilsaPREMIER9,652 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim52
Positioning44
Utility30

0–100 skill scores via Leetify.

Recent form

COLD48–44–8Last 10048%Win rateWLLLLLLWLW

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · −4.7pp headshot accuracy · −13ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 9%
  • Avg reaction 569ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 8%
  • Avg reaction 561ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 568ms

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 Player — Positioning stands above the rest of this profile (+1.3 against its own average).

Aim5.2
Utility3.0
Positioning4.4
Opening Duels2.0

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

jL

Plays most like jL 91% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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. 596ms 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

Aim5.2
Positioning4.4
Utility3.0
Mechanics6.5
Opening Duels2.1
Win Impact3.1

Composite 3.9/10 (Learning), 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 rating-0.03−0.00
first ⅓ avg -0.03 → last ⅓ avg -0.03
Reaction time607ms−68ms
first ⅓ avg 675ms → last ⅓ avg 607ms
Headshot accuracy10.5%+1.7%
first ⅓ avg 8.8% → last ⅓ avg 10.5%

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

0.15Best match rating · 13–3 · cache, 30 Apr →
26%Best headshot accuracy · 11–13 · ancient, 18 Jul →
461msFastest reaction time · 11–13 · ancient, 15 Sept →
13–0Biggest win · ancient, 13 Apr →

Across the last 100 tracked matches.

Highlights

4Longest win streak
10–7In matches decided by ≤2 rounds
8Overtime games

Map breakdown

infernoBest map · 60% over 20nukeWeakest map · 31% over 13
MapGradePlayedRecordWin rateAvg rating
ancientB2512–1348%-0.02
infernoA2012–860%-0.02
cacheA148–657%-0.01
nukeD134–931%-0.03
anubisC125–742%-0.04
vertigo—42–250%-0.05
dust2—42–250%-0.06
train—31–233%-0.02
overpass—21–150%0.01
mirage—20–20%-0.01
boulder—11–0100%0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (31% over 13). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

14,981Lifetime kills
0.90K/D
1,123Matches
37.1%Match win rate
26.8%Headshot %
10.6%Shot accuracy · Top 50% of Light Blue band
1,571MVPs
367Hours (in match)
1,125Bombs planted
155Bombs defused

Most-used weapons

Lifetime map wins

1,516inferno
659dust2
441nuke
355vertigo
293train
40cbble
33ar_shoots
14office

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.

10.6%Headshot accuracy
32.8%Accuracy (enemy spotted)
30.1%Spray accuracy
79.2%Counter-strafing
9.3°Preaim
596msReaction time
37.1%T opening success
40.1%CT opening success
0.26Enemies flashed / flash
1.8%Flash assists
9.92HE damage / grenade
3.81Flashes / 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 10.5578% — 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 0.2601 — 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 37.062% — below the 40% mark we flag

Spend your practice time on Nuke

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

31% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–10-0.024%1 Oct →
cache5–13-0.005%29 Sept →
inferno5–130.0412%29 Sept →
ancient6–13-0.0316%26 Sept →
inferno11–13-0.059%20 Sept →
ancient11–13-0.0414%15 Sept →
cache4–13-0.105%15 Sept →
ancient13–7-0.0111%14 Sept →
anubis5–13-0.070%11 Sept →
ancient13–7-0.027%11 Sept →
anubis13–10-0.0113%30 Aug →
cache10–13-0.0111%30 Aug →
inferno13–80.0325%23 Aug →
inferno13–80.0810%23 Aug →
ancient10–130.0225%19 Aug →
vertigo13–2-0.044%6 Aug →
boulder13–50.0316%6 Aug →
nuke8–13-0.0513%30 Jul →
inferno8–13-0.093%26 Jul →
ancient15–150.0110%20 Jul →
cache3–13-0.166%19 Jul →
ancient13–11-0.019%19 Jul →
inferno13–70.0411%19 Jul →
nuke13–10-0.028%18 Jul →
ancient11–13-0.0326%18 Jul →
cache13–9-0.0711%17 Jul →
anubis6–13-0.0810%14 Jul →
ancient4–13-0.089%14 Jul →
inferno12–12-0.108%7 Jul →
train12–12-0.040%7 Jul →
cache13–30.0016%7 Jul →
ancient7–13-0.0213%6 Jul →
nuke11–13-0.037%6 Jul →
overpass10–130.0015%30 Jun →
inferno13–90.0316%29 Jun →
anubis11–13-0.039%26 Jun →
anubis10–13-0.0513%25 Jun →
ancient13–80.0612%25 Jun →
nuke11–13-0.073%24 Jun →
anubis16–14-0.027%24 Jun →
inferno15–15-0.0811%24 Jun →
anubis5–13-0.0620%23 Jun →
ancient13–6-0.0018%23 Jun →
inferno13–90.0511%23 Jun →
nuke16–13-0.0911%22 Jun →
train13–50.0510%17 Jun →
train11–13-0.070%17 Jun →
ancient5–13-0.0411%31 May →
nuke13–90.0614%31 May →
inferno2–13-0.0812%31 May →
inferno7–13-0.0511%20 May →
mirage15–150.029%10 May →
nuke9–13-0.0610%10 May →
anubis13–4-0.0112%10 May →
cache13–11-0.0422%8 May →
cache13–60.079%8 May →
ancient3–13-0.050%6 May →
inferno16–14-0.039%3 May →
cache13–50.007%2 May →
dust21–13-0.098%2 May →
cache6–13-0.0216%2 May →
cache13–110.026%2 May →
nuke10–13-0.033%30 Apr →
mirage5–13-0.034%30 Apr →
cache13–70.019%30 Apr →
cache7–13-0.044%30 Apr →
cache13–30.156%30 Apr →
anubis4–13-0.053%25 Apr →
nuke2–13-0.137%25 Apr →
inferno13–9-0.077%21 Apr →
dust213–10-0.0113%19 Apr →
anubis6–130.0125%19 Apr →
ancient3–13-0.066%19 Apr →
overpass13–70.028%19 Apr →
ancient13–11-0.0512%16 Apr →
inferno13–6-0.070%16 Apr →
nuke15–15-0.0010%13 Apr →
ancient13–00.0910%13 Apr →
ancient13–11-0.009%13 Apr →
ancient7–13-0.037%13 Apr →
inferno13–8-0.013%11 Apr →
vertigo12–12-0.028%10 Apr →
vertigo13–11-0.0612%10 Apr →
nuke13–50.0315%10 Apr →
ancient5–13-0.033%8 Apr →
dust25–13-0.0511%8 Apr →
ancient13–3-0.050%3 Apr →
nuke10–13-0.0111%29 Mar →
anubis13–10-0.055%29 Mar →
nuke7–13-0.034%28 Mar →
inferno13–10-0.0813%28 Mar →
ancient13–9-0.018%28 Mar →
anubis13–11-0.0110%26 Mar →
vertigo10–13-0.0710%25 Mar →
dust213–11-0.0814%25 Mar →
ancient15–15-0.069%24 Mar →
inferno13–6-0.0110%24 Mar →
ancient13–70.0210%24 Mar →
inferno13–3-0.025%21 Mar →
inferno4–130.0010%21 Mar →

Match data via Leetify.

Recent teammates

Milestones

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

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