Grūtas

Grūtas — CS2 Stats

LT76561198141141821[U:1:180876093]Steam profile ↗✓ No bans

758Tracked matches59%Win rate2020Tracked since
2,925Hours in CS42Hrs last 2 wks
CSDB Rating6.6 SolidPositional Player
Premier CS Rating22,759Top 25% of 215,248 CSDB-tracked playersPink band · top ~5.5% of ranked players (population est.)
CSDB Leaderboard#46968 of 261485 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Nov 2026 (yesterday). Ranks are recorded once per day this page is viewed.

+362Premier CS Rating · 22,397 → 22,759

Rating over time

Premier CS Rating: 22,759 -140 18 Oct – 14 Nov · 18 days played
20,35222,899peak 22,89918 Oct14 Nov
25,254Peak Premier in tracked matches
18Days played since 2026-10-18

Premier CS Rating

  • 140 below peak (22,899)
  • -140 over 30 days · steady
  • Next: Red band at 25,000 — 2,241 to go
  • Reached: Pink band · Purple band · 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 Pink band among CSDB-tracked players (n=38,294), 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 playerPink band medianRed band medianvs Red band
Headshot rate43.3%46.9%49.3%6.0% short
Shot accuracy13.6%13.0%13.4%above
Kill/death ratio0.881.081.120.24 short
Match win rate42.8%46.7%48.5%5.7% short

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

Widest gap: Kill/death ratio. That is the metric furthest from the Red band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGGrūtasPREMIER22,759 · Pink bandcsdb.gg/stats

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Performance scores

Aim65
Positioning76
Utility46

0–100 skill scores via Leetify.

Recent form

STEADY43–54–3Last 10043%Win rateWLLLWLWWWW

Last 10 vs previous 10: +10pp win rate · +0.05 avg rating · +2.9pp headshot accuracy · −41ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 18%
  • Avg reaction 473ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 17%
  • Avg reaction 479ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 499ms

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).

Aim6.5
Utility4.6
Positioning7.6
Opening Duels6.8

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 80% 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

Strengths

CT openings. 63% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

T openings. 65% T opening-duel success — entries that actually open the round.

Areas to improve

Counter-strafing. Only 68% 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

Aim6.5
Positioning7.6
Utility4.6
Mechanics4.1
Opening Duels8.6
Win Impact7.9

Composite 6.6/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.01
first ⅓ avg 0.01 → last ⅓ avg 0.02
Reaction time490ms+16ms
first ⅓ avg 475ms → last ⅓ avg 490ms
Headshot accuracy17.3%−1.4%
first ⅓ avg 18.8% → last ⅓ avg 17.3%

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

0.13Best match rating · 5–13 · cache, 11 Nov →
36%Best headshot accuracy · 8–13 · inferno, 18 Oct →
297msFastest reaction time · 11–13 · nuke, 19 Oct →
13–1Biggest win · ancient, 11 Nov →

Across the last 100 tracked matches.

Highlights

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

Map breakdown

dust2Best map · 71% over 21infernoWeakest map · 19% over 16
MapGradePlayedRecordWin rateAvg rating
dust2S2115–671%0.03
infernoD163–1319%0.01
nukeB147–750%0.00
ancientC146–843%0.01
mirageC145–936%-0.00
anubisC114–736%0.02
cacheD103–730%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (19% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

75,654Lifetime kills
0.88K/D
4,032Matches
42.8%Match win rate
43.3%Headshot %
13.6%Shot accuracy · Top 50% of Pink band
9,059MVPs
1,945Hours (in match)
1,970Bombs planted
914Bombs defused

Most-used weapons

AK-4717,771
AWP13,544
Knife2,206
P2502,073
SSG 081,502
P901,429

Lifetime map wins

8,000dust2
4,402inferno
1,977nuke
423train
400cbble
126office
97italy
86dust

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

Faceit stats

Combat

10Matches
60%Win rate
0.83Avg K/D
—ADR
45%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
3Longest win streak

Recent Faceit resultsWWLWW

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.

16.8%Headshot accuracy
31.8%Accuracy (enemy spotted)
35.3%Spray accuracy
68.3%Counter-strafing
8.9°Preaim
493msReaction time
65.5%T opening success
62.9%CT opening success
0.55Enemies flashed / flash
6.4%Flash assists
9.47HE damage / grenade
3.63Flashes / 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. Grenades & Utility

    You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.

    Flashes per match 3.6274 — below the 4 mark we flag

    Grenade Lineups →
Spend your practice time on Inferno

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

19% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–80.0321%14 Nov →
ancient7–13-0.0613%13 Nov →
cache7–130.0726%13 Nov →
inferno2–130.0614%13 Nov →
nuke13–110.0316%13 Nov →
dust25–13-0.0120%13 Nov →
nuke13–110.0213%13 Nov →
mirage13–100.0915%13 Nov →
dust213–90.0113%13 Nov →
ancient13–70.1215%13 Nov →
nuke3–13-0.0714%13 Nov →
ancient9–13-0.0513%13 Nov →
nuke13–8-0.0625%12 Nov →
cache13–70.0010%12 Nov →
ancient13–50.0311%12 Nov →
mirage13–2-0.067%12 Nov →
inferno13–160.0215%12 Nov →
ancient9–130.0613%12 Nov →
mirage5–13-0.0115%12 Nov →
mirage13–7-0.0414%12 Nov →
inferno13–70.0120%12 Nov →
cache13–70.0022%12 Nov →
mirage15–15-0.0216%11 Nov →
ancient13–10.1115%11 Nov →
nuke13–80.0119%11 Nov →
dust213–11-0.0218%11 Nov →
cache5–130.1323%11 Nov →
anubis13–110.0724%11 Nov →
inferno8–130.0419%11 Nov →
inferno7–130.0323%11 Nov →
ancient7–13-0.0016%11 Nov →
nuke13–70.0524%11 Nov →
anubis14–16-0.0130%11 Nov →
dust213–70.0017%11 Nov →
dust213–10-0.0326%11 Nov →
dust213–60.1126%11 Nov →
dust27–130.0117%11 Nov →
dust216–14-0.0518%11 Nov →
ancient13–10-0.0116%11 Nov →
anubis6–130.0416%10 Nov →
cache13–40.0119%10 Nov →
nuke5–130.1225%10 Nov →
dust213–80.0928%10 Nov →
cache11–130.0118%10 Nov →
mirage7–13-0.0621%10 Nov →
dust213–11-0.0116%10 Nov →
dust213–30.1318%10 Nov →
mirage9–130.0123%10 Nov →
nuke6–13-0.0015%10 Nov →
nuke7–13-0.0510%10 Nov →
ancient13–40.0320%7 Nov →
dust213–60.1220%4 Nov →
anubis7–13-0.0125%4 Nov →
dust213–30.0123%4 Nov →
ancient9–13-0.1011%3 Nov →
inferno13–60.0626%3 Nov →
nuke10–130.0732%3 Nov →
mirage13–16-0.0515%3 Nov →
inferno10–130.0818%3 Nov →
dust26–13-0.0611%2 Nov →
inferno7–13-0.0423%2 Nov →
dust27–13-0.0514%2 Nov →
dust213–90.1327%29 Oct →
cache11–130.0517%29 Oct →
mirage13–110.0316%29 Oct →
cache10–130.1318%28 Oct →
inferno4–130.0116%27 Oct →
ancient13–30.0613%26 Oct →
inferno11–13-0.0125%25 Oct →
mirage10–13-0.0125%24 Oct →
anubis8–13-0.0013%24 Oct →
dust210–130.0236%24 Oct →
dust213–9-0.029%24 Oct →
anubis13–100.0419%24 Oct →
mirage13–60.1129%24 Oct →
anubis16–14-0.0220%24 Oct →
cache7–130.0318%24 Oct →
dust216–140.1121%24 Oct →
cache14–16-0.0316%22 Oct →
ancient6–130.0015%22 Oct →
inferno9–13-0.0715%22 Oct →
nuke11–13-0.0323%19 Oct →
inferno4–13-0.0213%19 Oct →
inferno15–15-0.0316%19 Oct →
anubis13–60.0515%19 Oct →
anubis6–130.1123%19 Oct →
ancient15–15-0.0520%18 Oct →
inferno13–110.0214%18 Oct →
mirage2–13-0.040%18 Oct →
ancient5–13-0.0211%18 Oct →
dust213–50.0712%18 Oct →
mirage11–13-0.0120%18 Oct →
mirage6–130.0519%18 Oct →
inferno9–130.0528%18 Oct →
anubis9–130.0023%18 Oct →
inferno8–130.0136%18 Oct →
nuke8–13-0.0421%18 Oct →
dust28–130.0118%18 Oct →
nuke13–5-0.0211%18 Oct →
anubis6–13-0.0422%18 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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