Gabinniee.

Gabinniee. — CS2 Stats

MV76561198290119673[U:1:329853945]Steam profile ↗✓ No bans

259Tracked matches62%Win rate2020Tracked since
CSDB Rating4.4 DevelopingPositional Player
Premier CS Rating11,563Blue band · top ~46.6% of ranked players (population est.)
FaceitLevel 4 · 942 ELOTop 81.0% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Oct 2026 (22 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 11,563 → 11,563
0Faceit ELO · 942 → 942
+2Tracked matches · now 259
0.0ppWin rate · 62.1% → 62.1%

Rating over time

Premier CS Rating: 11,563 -156 6 Feb – 23 Oct · 31 days played
11,56315,550peak 15,5506 Feb23 Oct
Faceit ELO: 942 +0 14 Sept – 23 Oct · 4 observations
942942peak 94214 Sept23 Oct
15,829Peak Premier in tracked matches
942Highest Faceit ELO seen on CSDB
40Days played since 2026-01-31

Faceit ELO

  • At peak — 942
  • 0 over 30 days · steady
  • Next: Level 5 at 1,051 — 109 to go
  • Reached: Level 4 · Level 3 · Level 2
  • Level 4 first seen 2026-09-14
  • Level 3 first seen 2026-09-14

Premier CS Rating

  • 3,987 below peak (15,550)
  • 0 over 30 days · steady
  • Next: Purple band at 15,000 — 3,437 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Blue band first seen 2026-09-21
  • Light Blue band first seen 2026-09-21

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.GGGabinniee.FACEITLevel 4 · 942 ELOSTANDINGTop 81.0% of rankedPREMIER11,563 · Blue band30 DAYS0 ELOPEAK ELO942csdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim41
Positioning61
Utility20

0–100 skill scores via Leetify.

Recent form

HOT56–40–4Last 10056%Win rateWWWWWWWLLW

Last 10 vs previous 10: +40pp win rate · −0.03 avg rating · −1.1pp headshot accuracy · −21ms reaction

Win rate up 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 (−0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 5–0 · 100% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 597ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 621ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 632ms

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 (+3.3 against its own average).

Aim4.1
Utility2.0
Positioning6.1
Opening Duels3.0
Clutch0.0

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

jL

Plays most like jL 76% 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

T-side openings. Opening success drops from 50% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 649ms 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

Aim4.1
Positioning6.1
Utility2.0
Mechanics4.9
Opening Duels2.7
Win Impact9.0

Composite 4.4/10 (Developing), 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+0.01
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time649ms−31ms
first ⅓ avg 680ms → last ⅓ avg 649ms
Headshot accuracy13.8%−7.2%
first ⅓ avg 21.0% → last ⅓ avg 13.8%

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

0.11Best match rating · 13–10 · mirage, 19 Aug →
39%Best headshot accuracy · 13–10 · dust2, 25 Feb →
477msFastest reaction time · 14–16 · mirage, 24 May →
13–1Biggest win · anubis, 23 Aug →

Across the last 100 tracked matches.

Highlights

7Longest win streak
W7Current streak
8–9In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 83% over 6infernoWeakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
mirageA2918–1162%-0.02
dust2B2111–1052%-0.01
ancientS139–469%-0.00
infernoD122–1017%-0.03
nukeS107–370%-0.01
anubisS65–183%0.01
overpassC52–340%0.00
cache—20–20%-0.03
train—22–0100%-0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

74Matches
46%Win rate
0.83Avg K/D
70.9ADR
38%Headshot %

Clutches & streaks

20%1v1 clutch win
10%1v2 clutch win
4Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Dust21759%0.9814.3
Mirage1346%1.0116.9
Inferno450%0.9413.5
Anubis425%0.9014.3
Ancient425%0.8012.5
Nuke250%0.9820.0
Overpass2100%1.2819.5
Train10%0.9018.0

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.

12.9%Headshot accuracy
29.2%Accuracy (enemy spotted)
35.2%Spray accuracy
72.2%Counter-strafing
10.1°Preaim
649msReaction time
31.2%T opening success
50.1%CT opening success
0.46Enemies flashed / flash
3.8%Flash assists
5.07HE damage / grenade
2.40Flashes / 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 12.9462% — 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 0.4551 — 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 31.1833% — below the 40% mark we flag

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.

17% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–11-0.0118%28 Oct →
mirage13–10-0.0116%28 Oct →
ancient13–10-0.0116%16 Sept →
mirage16–13-0.0516%16 Sept →
inferno13–10-0.089%16 Sept →
ancient13–5-0.014%27 Aug →
mirage13–9-0.038%27 Aug →
cache8–13-0.0017%27 Aug →
inferno11–13-0.0214%25 Aug →
mirage13–11-0.0710%25 Aug →
mirage14–16-0.0416%23 Aug →
anubis13–10.076%23 Aug →
dust213–90.0011%23 Aug →
ancient7–130.0117%19 Aug →
mirage13–100.1121%19 Aug →
dust213–10-0.0121%26 Jul →
cache11–13-0.066%23 Jul →
mirage7–13-0.066%23 Jul →
mirage6–13-0.0317%23 Jul →
dust28–130.0516%23 Jul →
dust210–130.0516%29 Jun →
mirage15–15-0.0412%26 Jun →
overpass13–100.0210%26 Jun →
ancient13–80.0617%26 Jun →
ancient13–7-0.000%26 Jun →
dust213–3-0.056%26 Jun →
ancient13–5-0.0319%26 Jun →
mirage13–100.0113%26 Jun →
inferno6–130.0321%26 Jun →
inferno6–13-0.074%25 Jun →
anubis16–14-0.0221%25 Jun →
mirage13–70.0337%25 Jun →
ancient13–90.0615%25 Jun →
dust212–16-0.047%25 Jun →
mirage13–10-0.079%25 Jun →
dust28–130.0019%25 Jun →
dust213–70.0819%25 Jun →
ancient11–13-0.068%24 Jun →
ancient13–16-0.0214%24 Jun →
dust29–13-0.0316%24 Jun →
mirage13–10-0.0320%24 Jun →
nuke13–11-0.0612%21 Jun →
mirage11–13-0.0411%21 Jun →
train13–8-0.0416%21 Jun →
train13–4-0.0823%21 Jun →
mirage7–13-0.0812%21 Jun →
nuke7–130.0315%20 Jun →
nuke13–5-0.0021%20 Jun →
dust215–15-0.0315%19 Jun →
mirage6–13-0.0315%19 Jun →
anubis13–11-0.0014%19 Jun →
dust25–13-0.0210%19 Jun →
mirage6–130.0614%17 Jun →
inferno2–13-0.0619%17 Jun →
mirage13–30.0217%16 Jun →
anubis13–16-0.017%15 Jun →
inferno11–13-0.0319%12 Jun →
mirage13–8-0.0118%12 Jun →
dust213–3-0.0132%12 Jun →
inferno6–13-0.0128%24 May →
mirage14–16-0.0718%24 May →
inferno6–13-0.0318%15 May →
mirage13–4-0.0027%15 May →
ancient13–30.0128%15 May →
mirage13–50.0224%15 May →
ancient13–90.0421%9 May →
dust213–9-0.0120%9 May →
inferno13–4-0.0219%9 May →
overpass13–50.0413%9 May →
dust210–130.0223%28 Apr →
mirage4–13-0.0420%27 Apr →
overpass11–13-0.0320%27 Apr →
anubis13–80.0222%13 Apr →
anubis13–8-0.0127%13 Apr →
dust215–15-0.0224%31 Mar →
inferno4–13-0.0628%31 Mar →
overpass8–13-0.0030%31 Mar →
mirage13–9-0.0413%31 Mar →
nuke12–12-0.0119%23 Mar →
nuke13–3-0.0410%23 Mar →
mirage13–80.0925%19 Mar →
nuke11–130.0018%9 Mar →
ancient6–13-0.0718%2 Mar →
dust213–7-0.0624%1 Mar →
dust23–13-0.0132%1 Mar →
mirage13–6-0.0314%28 Feb →
mirage2–13-0.106%26 Feb →
overpass10–13-0.0323%25 Feb →
dust213–100.0039%25 Feb →
nuke13–7-0.0021%22 Feb →
mirage13–110.0129%22 Feb →
nuke13–8-0.0220%19 Feb →
ancient13–8-0.0015%6 Feb →
inferno3–130.0023%6 Feb →
mirage16–140.0314%5 Feb →
nuke13–11-0.0115%5 Feb →
dust213–10-0.0823%5 Feb →
dust213–10.0619%1 Feb →
dust213–4-0.0323%31 Jan →
inferno10–13-0.0224%31 Jan →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.