groberUnfug #joinJesusNow

groberUnfug #joinJesusNow — CS2 Stats

76561197994369358[U:1:34103630]Steam profile ↗✓ No bans

3,818Tracked matches22%Win rate2020Tracked since
CSDB Rating4.8 DevelopingPositional Player
Premier CS Rating19,391Top 50% of 204,097 CSDB-tracked playersPurple band · top ~10.9% of ranked players (population est.)
CSDB Leaderboard#90827 of 251169 tracked
FaceitLevel 7 · 1,806 ELOTop 42.3% of ranked FACEIT players
WingmanMaster Guardian I
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 8 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: 19,391 -81 31 Jul – 8 Oct · 16 days played
19,39121,266peak 21,26631 Jul8 Oct
21,390Peak Premier in tracked matches
1,806Highest Faceit ELO seen on CSDB
25Days played since 2026-07-31

Faceit ELO

  • At peak — 1,806
  • Next: Level 10 at 2,001 — 195 to go
  • Reached: Level 9 · Level 8 · Level 7 · Level 6
  • Level 9 first seen 2026-09-16
  • Level 8 first seen 2026-09-16

Premier CS Rating

  • 1,875 below peak (21,266)
  • -788 over 30 days · declining
  • Next: Pink band at 20,000 — 609 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-09-16
  • Purple band first seen 2026-09-16

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGgroberUnfug #joinJesusNowFACEITLevel 7 · 1,806 ELOSTANDINGTop 42.3% of rankedPREMIER19,391 · Purple bandPEAK ELO1,806csdb.gg/stats

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Performance scores

Aim66
Positioning49
Utility47

0–100 skill scores via Leetify.

Recent form

COLD41–50–9Last 10041%Win rateLLLLTLLLLL

Last 10 vs previous 10: −30pp win rate · +0.00 avg rating · +0.4pp headshot accuracy · −7ms reaction

Win rate down 30pp 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 (+0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 0–4–1 · 0% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 14%
  • Avg reaction 644ms

Last 10

  • 0–9–1 · 0% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 590ms

Last 20

  • 3–16–1 · 15% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 593ms

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 (+1.2 against its own average).

Aim6.6
Utility4.7
Positioning4.9
Opening Duels1.3
Clutch4.0

Strong T-side opener

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 87% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim profile; lower opening-duel success.

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

CT openings. Opening success drops from 49% on T to 27% on CT — first contacts on the defending side are being lost.

Reaction time. 612ms 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

Aim6.6
Positioning4.9
Utility4.7
Mechanics6.2
Opening Duels2.4
Win Impact0.0

Composite 4.8/10 (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 rating-0.01−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time609ms−34ms
first ⅓ avg 643ms → last ⅓ avg 609ms
Headshot accuracy19.8%+2.0%
first ⅓ avg 17.8% → last ⅓ avg 19.8%

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

0.12Best match rating · 13–6 · dust2, 11 Sept →
38%Best headshot accuracy · 13–7 · dust2, 18 Sept →
438msFastest reaction time · 4–13 · inferno, 3 Oct →
13–1Biggest win · nuke, 11 Sept →

Across the last 100 tracked matches.

Highlights

3Longest win streak
L4Current streak
8–6In matches decided by ≤2 rounds
4Overtime games

Map breakdown

cacheBest map · 43% over 14infernoWeakest map · 32% over 22
MapGradePlayedRecordWin rateAvg rating
dust2C3313–2039%-0.00
infernoD227–1532%-0.01
cacheC146–843%0.01
mirageC73–443%-0.02
vertigoC52–340%0.04
nukeC52–340%-0.01
overpass—43–175%0.03
ancient—44–0100%-0.02
anubis—31–233%0.03
train—20–20%-0.07
boulder—10–10%-0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (32% over 22). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,135Matches
50%Win rate
0.96Avg K/D
70.9ADR
44%Headshot %

Clutches & streaks

40%1v1 clutch win
26%1v2 clutch win
8Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Dust28141%0.8713.4
Inferno8052%0.9113.4
Ancient7948%1.0715.9
Mirage3661%0.8413.4
Nuke3453%1.0115.0
Anubis3222%0.7912.6
Overpass2843%0.9512.8
Train771%0.8712.7

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.

19.2%Headshot accuracy
37.4%Accuracy (enemy spotted)
39.2%Spray accuracy
77.9%Counter-strafing
12.1°Preaim
612msReaction time
48.9%T opening success
26.6%CT opening success
0.39Enemies flashed / flash
4.8%Flash assists
9.64HE damage / grenade
9.72Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.1346° — above the 12° 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 0.3862 — below the 0.5 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.

32% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache10–130.0516%8 Oct →
dust211–130.0220%8 Oct →
inferno11–13-0.0012%8 Oct →
vertigo6–13-0.029%8 Oct →
mirage15–15-0.0016%8 Oct →
dust29–130.047%3 Oct →
inferno4–13-0.0220%3 Oct →
inferno4–13-0.0733%3 Oct →
inferno5–13-0.0720%3 Oct →
inferno9–13-0.0031%3 Oct →
cache10–13-0.0624%3 Oct →
cache6–13-0.0616%1 Oct →
dust213–11-0.0313%1 Oct →
dust213–90.0324%26 Sept →
inferno3–13-0.0214%26 Sept →
overpass13–100.0618%25 Sept →
cache9–130.0620%25 Sept →
dust23–13-0.090%25 Sept →
anubis5–130.0219%25 Sept →
cache10–13-0.0332%24 Sept →
nuke11–13-0.0624%24 Sept →
vertigo2–130.1118%24 Sept →
inferno2–13-0.0324%24 Sept →
dust212–120.0617%24 Sept →
mirage13–3-0.0223%24 Sept →
train1–13-0.0829%18 Sept →
mirage13–80.0016%18 Sept →
dust29–130.0219%18 Sept →
inferno12–12-0.0034%18 Sept →
ancient13–8-0.0411%18 Sept →
cache13–60.0527%18 Sept →
dust213–70.0038%18 Sept →
boulder12–12-0.0012%18 Sept →
dust27–13-0.0220%18 Sept →
dust25–13-0.0325%12 Sept →
dust27–13-0.0529%11 Sept →
inferno6–13-0.0217%11 Sept →
train6–13-0.0532%11 Sept →
nuke13–10.0419%11 Sept →
dust213–60.1217%11 Sept →
cache13–7-0.0120%10 Sept →
dust20–6-0.130%10 Sept →
cache12–12-0.0514%10 Sept →
dust211–13-0.129%5 Sept →
inferno13–11-0.0211%3 Sept →
dust22–13-0.0721%3 Sept →
inferno13–70.0421%3 Sept →
nuke5–13-0.0323%3 Sept →
inferno10–13-0.0111%3 Sept →
dust213–110.0719%29 Aug →
mirage12–12-0.0111%29 Aug →
vertigo13–50.1115%29 Aug →
inferno12–16-0.0320%29 Aug →
overpass13–90.0518%29 Aug →
cache13–80.0628%29 Aug →
mirage5–13-0.0425%27 Aug →
dust213–50.0834%27 Aug →
overpass3–13-0.0626%27 Aug →
anubis13–90.1028%27 Aug →
cache8–130.1018%27 Aug →
inferno13–11-0.0221%27 Aug →
dust23–130.0421%27 Aug →
dust213–11-0.0618%27 Aug →
ancient13–9-0.0413%26 Aug →
inferno12–12-0.0429%26 Aug →
vertigo10–13-0.0122%26 Aug →
dust213–90.0331%26 Aug →
dust213–10.0224%26 Aug →
dust211–13-0.0225%26 Aug →
cache13–90.0516%25 Aug →
inferno5–130.0622%25 Aug →
nuke1–13-0.0316%22 Aug →
inferno13–110.0119%22 Aug →
nuke13–20.0412%22 Aug →
dust210–13-0.0217%22 Aug →
ancient13–9-0.0115%21 Aug →
dust25–13-0.0321%21 Aug →
inferno13–30.0518%21 Aug →
inferno12–12-0.0211%13 Aug →
dust213–70.0820%13 Aug →
vertigo10–30.0224%13 Aug →
inferno8–13-0.0711%8 Aug →
mirage13–70.0214%8 Aug →
anubis3–13-0.053%7 Aug →
cache6–130.0329%7 Aug →
dust26–13-0.0229%7 Aug →
inferno13–70.038%6 Aug →
cache13–5-0.0314%6 Aug →
overpass13–110.069%6 Aug →
mirage6–13-0.0820%6 Aug →
dust216–14-0.0220%6 Aug →
dust213–50.0620%2 Aug →
dust213–60.0216%1 Aug →
dust29–13-0.0812%1 Aug →
cache13–50.0224%1 Aug →
dust211–130.059%1 Aug →
inferno13–70.1122%1 Aug →
ancient13–90.0319%1 Aug →
dust215–15-0.0119%31 Jul →
dust23–13-0.0528%31 Jul →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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