Gadjet

Gadjet — CS2 Stats

AU76561197994691108[U:1:34425380]Steam profile ↗✓ No bans

616Tracked matches43%Win rate2020Tracked since
1,923Hours in CS
CSDB Rating2.7 LearningPositional Player
Premier CS Rating2,822Grey band · top ~88% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 14 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: 2,822 +1,198 20 May – 14 Oct · 18 days played
1,6242,822peak 2,82220 May14 Oct
2,822Peak Premier in tracked matches
24Days played since 2026-05-20

Premier CS Rating

  • At peak — 2,822
  • +224 over 30 days · steady
  • Next: Light Blue band at 5,000 — 2,178 to go

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate40.7%38.2%39.9%meets
Shot accuracy11.1%3.6%7.0%above
Kill/death ratio1.140.830.92above
Match win rate38.9%40.2%42.3%3.3% short

This profile matches the typical Light Blue band player on 3 of 4 comparable metrics.

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

Share this profile

CSDB.GGGadjetPREMIER2,822 · Grey bandcsdb.gg/stats

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Performance scores

Aim26
Positioning40
Utility8

0–100 skill scores via Leetify.

Recent form

STEADY42–56–2Last 10042%Win rateWTWLLLLLWW

Last 10 vs previous 10: +10pp win rate · −0.00 avg rating · −2.4pp headshot accuracy · +43ms 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 758ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 753ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 731ms

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 (+2.2 against its own average).

Aim2.6
Utility0.8
Positioning4.0
Opening Duels0.6

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

donk

Plays most like donk 80% playstyle similarity

Most alike: positioning profile, utility contribution.

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

CT openings. Opening success drops from 46% on T to 29% on CT — first contacts on the defending side are being lost.

Reaction time. 722ms 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

Aim2.6
Positioning4.0
Utility0.8
Mechanics5.5
Opening Duels2.0
Win Impact2.6

Composite 2.7/10 (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-0.03−0.02
first ⅓ avg -0.01 → last ⅓ avg -0.03
Reaction time710ms−43ms
first ⅓ avg 754ms → last ⅓ avg 710ms
Headshot accuracy14.6%−0.8%
first ⅓ avg 15.4% → last ⅓ avg 14.6%

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

0.10Best match rating · 16–14 · nuke, 17 Jun →
50%Best headshot accuracy · 2–5 · inferno, 30 Sept →
523msFastest reaction time · 2–13 · italy, 7 Oct →
13–0Biggest win · mirage, 9 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
12–7In matches decided by ≤2 rounds
14Overtime games

Map breakdown

nukeBest map · 50% over 24infernoWeakest map · 13% over 8
MapGradePlayedRecordWin rateAvg rating
nukeB2412–1250%-0.00
ancientC208–1240%-0.03
mirageB168–850%-0.02
dust2B105–550%-0.02
cacheD92–722%-0.03
infernoD81–713%-0.03
vertigo—41–325%-0.02
overpass—43–175%-0.02
anubis—32–167%-0.03
italy—10–10%-0.06
fachwerk—10–10%-0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

110,915Lifetime kills
1.14K/D · Top 10% of Grey band
9,128Matches
38.9%Match win rate
40.7%Headshot % · Top 50% of Grey band
11.1%Shot accuracy · Top 25% of Grey band
12,440MVPs
1,923Hours (in match)
6,090Bombs planted
876Bombs defused

Most-used weapons

AK-4715,752
P9013,258
XM10144,810
AWP4,508
MP73,363
Nova3,076
Negev2,945

Lifetime map wins

5,934office
3,216safehouse
2,650lake
2,175stmarc
1,960nuke
1,641dust2
1,597bank
1,532inferno

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.

14.0%Headshot accuracy
30.4%Accuracy (enemy spotted)
30.3%Spray accuracy
74.5%Counter-strafing
13.0°Preaim
722msReaction time
46.1%T opening success
29.1%CT opening success
0.12Enemies flashed / flash
0.0%Flash assists
8.60HE damage / grenade
0.87Flashes / 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 13.0473° — above the 12° mark we flag

    Aim Training →
  2. 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 14.0065% — below the 15% mark we flag

    Aim Training →
  3. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 721.7242ms — above the 700ms mark we flag

    Aim Training →
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.

13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage16–140.0013%14 Oct →
mirage15–15-0.0110%14 Oct →
cache13–6-0.0413%14 Oct →
italy2–13-0.0611%7 Oct →
nuke5–130.0318%7 Oct →
vertigo5–13-0.0715%7 Oct →
cache9–13-0.0217%7 Oct →
mirage6–13-0.0813%7 Oct →
dust213–10.015%7 Oct →
dust213–11-0.0820%30 Sept →
nuke7–13-0.0213%30 Sept →
inferno2–5-0.0550%30 Sept →
nuke1–130.019%30 Sept →
nuke13–11-0.056%30 Sept →
dust25–13-0.0413%30 Sept →
cache10–13-0.019%30 Sept →
mirage13–10-0.0221%23 Sept →
dust213–16-0.0213%23 Sept →
vertigo7–13-0.0514%23 Sept →
nuke13–9-0.0210%16 Sept →
nuke13–80.0012%16 Sept →
anubis13–70.0418%16 Sept →
nuke15–15-0.0321%9 Sept →
ancient7–13-0.0310%9 Sept →
mirage13–00.0723%9 Sept →
nuke16–12-0.0111%9 Sept →
mirage13–11-0.058%2 Sept →
cache7–13-0.0311%2 Sept →
mirage10–13-0.099%2 Sept →
ancient10–13-0.0629%2 Sept →
mirage7–13-0.073%26 Aug →
nuke11–13-0.0321%26 Aug →
inferno8–13-0.0714%26 Aug →
anubis13–9-0.0920%26 Aug →
ancient13–11-0.018%19 Aug →
dust27–2-0.0117%19 Aug →
ancient13–9-0.0416%19 Aug →
nuke13–50.0421%19 Aug →
dust213–100.0613%12 Aug →
nuke14–16-0.0614%12 Aug →
ancient14–160.0215%12 Aug →
cache3–13-0.1014%12 Aug →
dust26–13-0.098%5 Aug →
ancient13–8-0.0513%5 Aug →
cache7–130.0123%5 Aug →
anubis5–13-0.0513%5 Aug →
ancient13–40.089%5 Aug →
inferno0–13-0.1114%5 Aug →
dust213–100.0719%29 Jul →
mirage6–13-0.0513%29 Jul →
ancient3–13-0.0713%29 Jul →
nuke11–13-0.0015%29 Jul →
cache10–13-0.049%29 Jul →
nuke16–140.0517%22 Jul →
nuke2–13-0.0711%22 Jul →
mirage1–130.0217%22 Jul →
ancient8–13-0.0418%22 Jul →
cache5–13-0.0228%22 Jul →
fachwerk7–13-0.008%16 Jul →
dust22–13-0.0512%16 Jul →
nuke6–13-0.0126%16 Jul →
mirage8–13-0.0411%15 Jul →
nuke13–80.006%15 Jul →
ancient7–13-0.029%15 Jul →
mirage13–50.0712%15 Jul →
ancient5–13-0.0713%15 Jul →
nuke13–50.0418%15 Jul →
overpass13–60.0514%1 Jul →
ancient4–13-0.0818%1 Jul →
mirage9–13-0.015%1 Jul →
ancient5–13-0.0114%1 Jul →
mirage13–110.0125%24 Jun →
overpass16–12-0.0412%24 Jun →
inferno8–13-0.0418%24 Jun →
nuke13–5-0.0420%17 Jun →
ancient9–13-0.0412%17 Jun →
nuke16–140.1012%17 Jun →
mirage13–9-0.0719%12 Jun →
inferno13–160.038%12 Jun →
overpass6–13-0.088%12 Jun →
ancient13–16-0.0410%10 Jun →
inferno10–130.0221%10 Jun →
nuke9–130.0213%10 Jun →
cache13–8-0.0311%10 Jun →
vertigo13–11-0.0117%5 Jun →
vertigo11–130.038%5 Jun →
ancient13–20.005%5 Jun →
mirage16–14-0.0017%5 Jun →
ancient13–100.0117%5 Jun →
dust25–13-0.0733%5 Jun →
inferno16–14-0.0213%5 Jun →
ancient13–6-0.0013%3 Jun →
nuke13–2-0.0117%3 Jun →
inferno11–13-0.0023%3 Jun →
ancient11–13-0.0415%3 Jun →
nuke4–130.0019%3 Jun →
ancient13–11-0.0113%27 May →
overpass13–3-0.0014%27 May →
nuke13–70.037%27 May →
nuke7–13-0.0539%20 May →

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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