Vilperis

Vilperis — CS2 Stats

FI76561198180896494[U:1:220630766]Steam profile ↗✓ No bans

976Tracked matches50%Win rate2020Tracked since
CSDB Rating5.6 SolidSupport
FaceitLevel 5 · 1,568 ELOTop 67.6% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 17,210 +858 13 Oct – 29 Dec · 18 days played
13,67617,817peak 17,81713 Oct29 Dec
17,817Peak Premier in tracked matches
1,568Highest Faceit ELO seen on CSDB
56Days played since 2024-10-11

Faceit ELO

  • At peak — 1,568
  • Next: Level 9 at 1,751 — 183 to go
  • Reached: Level 8 · Level 7 · Level 6 · Level 5

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

Share this profile

CSDB.GGVilperisFACEITLevel 5 · 1,568 ELOSTANDINGTop 67.6% of rankedPEAK ELO1,568csdb.gg/stats

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Performance scores

Aim64
Positioning57
Utility61

0–100 skill scores via Leetify.

Recent form

STEADY47–50–3Last 10047%Win rateLLWWWLLWWL

Last 10 vs previous 10: +10pp win rate · +0.03 avg rating · +5.0pp 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 -0.03
  • Avg headshot accuracy 24%
  • Avg reaction 647ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 22%
  • Avg reaction 625ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 19%
  • Avg reaction 656ms

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 (+1 against its own average).

Aim6.4
Utility6.1
Positioning5.7
Opening Duels5.1
Clutch3.4

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

device

Plays most like device 83% 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

Areas to improve

Reaction time. 656ms 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

Aim6.4
Positioning5.7
Utility6.1
Mechanics6.8
Opening Duels3.6
Win Impact5.0

Composite 5.6/10 (Solid), 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-0.01−0.02
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time658ms+35ms
first ⅓ avg 623ms → last ⅓ avg 658ms
Headshot accuracy24.2%+6.5%
first ⅓ avg 17.7% → last ⅓ avg 24.2%

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 · dust2, 5 Dec →
57%Best headshot accuracy · 13–5 · dust2, 28 Oct →
438msFastest reaction time · 9–13 · train, 16 Nov →
13–0Biggest win · dust2, 30 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
4–8In matches decided by ≤2 rounds
11Overtime games

Map breakdown

dust2Best map · 58% over 33trainWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
dust2A3319–1458%-0.00
nukeB157–847%-0.01
ancientC146–843%-0.02
infernoA116–555%0.01
mirageC104–640%-0.01
anubisD93–633%-0.02
trainD72–529%-0.00
vertigo—10–10%0.00

Across the last 100 tracked matches.

Faceit stats

Combat

893Matches
50%Win rate
1.04Avg K/D
70.3ADR
39%Headshot %

Clutches & streaks

37%1v1 clutch win
21%1v2 clutch win
7Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Ancient6951%0.8913.9
Dust25850%0.9915.8
Nuke5459%1.0014.9
Anubis3543%0.8313.6
Mirage3345%0.7812.3
Inferno1932%0.8113.3
Vertigo1625%0.9014.5
Train1662%0.8312.6

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.

23.4%Headshot accuracy
31.1%Accuracy (enemy spotted)
32.3%Spray accuracy
80.8%Counter-strafing
9.2°Preaim
656msReaction time
41.9%T opening success
47.0%CT opening success
0.74Enemies flashed / flash
5.0%Flash assists
8.32HE damage / grenade
10.64Flashes / match

Recommended for you

Spend your practice time on Train

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
anubis10–13-0.0318%17 Oct →
ancient7–13-0.0736%17 Oct →
dust213–80.019%10 Oct →
anubis7–3-0.0133%10 Oct →
ancient16–13-0.0422%10 Oct →
inferno10–13-0.0419%4 Sept →
mirage10–13-0.0122%10 Apr →
dust213–30.1022%10 Apr →
nuke16–14-0.0013%1 Jan →
nuke5–13-0.0421%30 Dec →
dust24–13-0.0823%29 Dec →
mirage13–9-0.0721%29 Dec →
nuke0–13-0.106%29 Dec →
dust213–100.0120%18 Dec →
nuke13–70.0213%18 Dec →
dust29–13-0.0516%16 Dec →
train2–13-0.0912%10 Dec →
dust213–10-0.0426%24 Nov →
mirage8–130.0015%20 Nov →
mirage8–130.0015%20 Nov →
dust213–20.0930%30 Oct →
mirage13–60.0430%30 Oct →
ancient8–130.0119%30 Oct →
dust213–00.0835%30 Oct →
dust26–13-0.0130%28 Oct →
dust213–50.0557%28 Oct →
train5–13-0.0447%24 Oct →
nuke13–5-0.0730%24 Oct →
mirage13–30.0135%24 Oct →
dust25–13-0.0326%24 Oct →
inferno12–12-0.0323%24 Oct →
ancient2–13-0.0633%17 Sept →
nuke13–110.0118%17 Sept →
dust213–10-0.0232%16 Sept →
nuke11–130.0224%10 Sept →
ancient13–16-0.0222%27 Aug →
inferno10–13-0.0013%27 Jul →
dust213–7-0.0322%27 Jul →
dust210–13-0.0230%25 Jul →
dust213–60.0012%25 Jul →
train13–60.0915%8 Jul →
dust213–70.0220%22 Apr →
mirage13–7-0.0326%12 Apr →
nuke6–13-0.0612%11 Apr →
ancient16–130.0314%11 Apr →
anubis10–13-0.0728%9 Apr →
ancient13–7-0.0516%26 Mar →
nuke11–13-0.0413%3 Mar →
dust215–15-0.0520%3 Mar →
dust213–90.0110%3 Mar →
nuke0–90.000%1 Mar →
dust213–7-0.0121%28 Feb →
train9–130.0013%10 Feb →
dust211–13-0.0812%6 Feb →
dust213–100.0312%31 Jan →
dust213–7-0.005%31 Jan →
dust216–130.008%21 Jan →
dust211–13-0.0514%21 Jan →
mirage6–13-0.0521%15 Jan →
ancient13–6-0.0214%15 Jan →
anubis9–130.0012%14 Jan →
nuke15–150.0517%13 Jan →
dust29–13-0.0614%13 Jan →
nuke13–8-0.0511%7 Jan →
dust211–13-0.0418%7 Jan →
ancient3–13-0.0218%7 Jan →
ancient13–110.0310%30 Dec →
anubis25–23-0.0217%19 Dec →
inferno13–90.017%19 Dec →
ancient10–130.0112%16 Dec →
inferno10–13-0.0227%16 Dec →
inferno13–90.0121%16 Dec →
mirage2–130.0130%16 Dec →
ancient9–13-0.019%15 Dec →
dust210–13-0.078%15 Dec →
dust210–130.0213%12 Dec →
anubis4–13-0.066%12 Dec →
ancient12–16-0.0314%12 Dec →
inferno3–13-0.0125%12 Dec →
nuke13–60.0521%5 Dec →
inferno13–70.0026%5 Dec →
nuke13–30.0818%5 Dec →
dust213–30.1530%5 Dec →
dust213–60.0420%4 Dec →
anubis11–130.0520%4 Dec →
dust213–100.0834%2 Dec →
anubis13–100.0114%26 Nov →
anubis10–13-0.0422%25 Nov →
inferno13–80.0520%25 Nov →
ancient13–10-0.0014%25 Nov →
train11–13-0.0215%18 Nov →
train13–100.0418%18 Nov →
dust24–13-0.0513%16 Nov →
train9–13-0.0028%16 Nov →
dust23–13-0.1014%10 Nov →
mirage3–13-0.0414%9 Nov →
inferno19–160.0210%2 Nov →
nuke6–130.0622%20 Oct →
inferno13–90.0711%13 Oct →
vertigo17–190.0014%11 Oct →

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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