X(0_o)f

X(0_o)f — CS2 Stats

FR76561199685472397[U:1:1725206669]Steam profile ↗✓ No bans

484Tracked matches40%Win rate2025Tracked since
519Hours in CS24Hrs last 2 wks
CSDB Rating3.1 LearningSupport
Premier CS Rating1,744Grey band · top ~92.6% of ranked players (population est.)
WingmanSilver II
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Nov 2026 (3 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: 1,744 +134 19 Sept – 2 Nov · 18 days played
1,5072,236peak 2,23619 Sept2 Nov
2,333Peak Premier in tracked matches
29Days played since 2026-09-16

Premier CS Rating

  • 492 below peak (2,236)
  • -235 over 30 days · steady
  • Next: Light Blue band at 5,000 — 3,256 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 rate34.4%38.2%39.9%5.6% short
Shot accuracy0.0%3.6%7.0%7.0% short
Kill/death ratio0.510.830.920.41 short
Match win rate27.4%40.2%42.3%14.8% short

This profile sits below the typical Light Blue band player on every metric we can compare.

Widest gap: Shot accuracy. 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.GGX(0_o)fPREMIER1,744 · Grey bandcsdb.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

Aim16
Positioning42
Utility42

0–100 skill scores via Leetify.

Recent form

COLD37–56–7Last 10037%Win rateLLLLLLLLLW

Last 10 vs previous 10: −50pp win rate · −0.06 avg rating · −0.6pp headshot accuracy · +55ms reaction

Win rate down 50pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 0–5 · 0% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 7%
  • Avg reaction 817ms

Last 10

  • 1–9 · 10% win rate
  • Avg rating -0.09
  • Avg headshot accuracy 8%
  • Avg reaction 803ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 9%
  • Avg reaction 776ms

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).

Aim1.6
Utility4.2
Positioning4.2
Opening Duels1.2

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 55% 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

CT openings. Opening success drops from 58% on T to 32% on CT — first contacts on the defending side are being lost.

Reaction time. 788ms 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

Aim1.6
Positioning4.2
Utility4.2
Mechanics6.6
Opening Duels3.7
Win Impact1.7

Composite 3.1/10 (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-0.05+0.01
first ⅓ avg -0.06 → last ⅓ avg -0.05
Reaction time772ms−18ms
first ⅓ avg 790ms → last ⅓ avg 772ms
Headshot accuracy10.6%−1.2%
first ⅓ avg 11.8% → last ⅓ avg 10.6%

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

0.14Best match rating · 9–5 · inferno, 22 Oct →
50%Best headshot accuracy · 9–1 · inferno, 26 Oct →
438msFastest reaction time · 9–1 · inferno, 26 Oct →
11–0Biggest win · cache, 28 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L9Current streak
6–10In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 45% over 22infernoWeakest map · 29% over 49
MapGradePlayedRecordWin rateAvg rating
infernoD4914–3529%-0.06
nukeB2210–1245%-0.07
dust2D103–730%-0.05
mirageC73–443%-0.03
cache—44–0100%-0.00
ancient—31–233%-0.04
anubis—31–233%-0.00
vertigo—10–10%-0.15
poseidon—11–0100%-0.14

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 49). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

10,224Lifetime kills
0.51K/D
1,123Matches
27.4%Match win rate
34.4%Headshot %
0.0%Shot accuracy
1,290MVPs
261Hours (in match)
548Bombs planted
105Bombs defused

Most-used weapons

Lifetime map wins

2,010inferno
1,301dust2
1,053nuke
157vertigo
41train
4lake
1ar_shoots
1ar_baggage

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.

9.7%Headshot accuracy
26.5%Accuracy (enemy spotted)
27.7%Spray accuracy
79.6%Counter-strafing
12.0°Preaim
788msReaction time
57.8%T opening success
32.0%CT opening success
0.57Enemies flashed / flash
2.6%Flash assists
7.26HE damage / grenade
4.69Flashes / 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 12.034° — 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 9.6547% — 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 788.1467ms — 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.

29% win rate across 49 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient9–13-0.022%2 Nov →
inferno6–9-0.146%2 Nov →
ancient6–13-0.068%31 Oct →
inferno5–13-0.027%31 Oct →
inferno6–9-0.1612%31 Oct →
inferno3–9-0.1914%31 Oct →
inferno3–9-0.2213%31 Oct →
dust26–13-0.0212%30 Oct →
vertigo2–9-0.155%29 Oct →
inferno9–60.107%29 Oct →
nuke7–9-0.096%29 Oct →
mirage0–13-0.067%29 Oct →
inferno9–70.0310%29 Oct →
mirage10–130.008%28 Oct →
nuke13–8-0.056%28 Oct →
nuke8–8-0.096%28 Oct →
inferno9–1-0.0121%28 Oct →
cache11–0-0.057%28 Oct →
inferno13–8-0.0412%28 Oct →
nuke9–50.058%28 Oct →
dust213–9-0.055%27 Oct →
inferno10–130.0214%27 Oct →
inferno5–9-0.084%27 Oct →
poseidon9–7-0.1413%27 Oct →
cache13–70.0117%27 Oct →
dust213–7-0.0117%27 Oct →
cache13–40.0110%26 Oct →
mirage13–20.018%26 Oct →
mirage9–13-0.035%26 Oct →
dust213–40.0112%26 Oct →
dust22–13-0.0710%26 Oct →
inferno2–9-0.2213%26 Oct →
inferno9–10.0550%26 Oct →
nuke10–13-0.044%25 Oct →
inferno7–90.037%25 Oct →
ancient11–3-0.0412%25 Oct →
inferno3–9-0.116%25 Oct →
anubis5–13-0.0516%24 Oct →
nuke9–7-0.0232%24 Oct →
nuke3–13-0.0911%22 Oct →
nuke3–9-0.216%22 Oct →
inferno9–50.1415%22 Oct →
dust28–130.0020%21 Oct →
anubis11–13-0.047%21 Oct →
inferno9–7-0.0913%21 Oct →
inferno1–9-0.227%21 Oct →
inferno6–9-0.099%21 Oct →
inferno11–13-0.0511%20 Oct →
nuke9–50.0514%20 Oct →
anubis13–90.075%13 Oct →
inferno9–00.1015%13 Oct →
nuke6–9-0.218%12 Oct →
inferno4–9-0.230%11 Oct →
nuke9–5-0.0310%11 Oct →
nuke7–13-0.1211%10 Oct →
nuke9–5-0.016%10 Oct →
nuke7–9-0.148%10 Oct →
nuke8–80.0917%8 Oct →
nuke9–5-0.185%8 Oct →
nuke5–9-0.1013%8 Oct →
inferno6–9-0.0618%8 Oct →
dust25–13-0.150%7 Oct →
inferno5–9-0.0322%7 Oct →
inferno9–60.026%5 Oct →
inferno6–9-0.035%4 Oct →
inferno11–13-0.088%3 Oct →
cache13–20.0016%3 Oct →
nuke3–13-0.076%3 Oct →
mirage11–13-0.067%3 Oct →
inferno2–9-0.1911%3 Oct →
dust212–12-0.0314%1 Oct →
inferno2–9-0.174%1 Oct →
inferno4–9-0.126%30 Sept →
inferno6–90.0918%30 Sept →
inferno2–13-0.0912%25 Sept →
inferno6–9-0.1222%25 Sept →
nuke9–60.0810%25 Sept →
nuke9–6-0.079%25 Sept →
inferno13–80.0313%25 Sept →
inferno8–8-0.1113%24 Sept →
mirage13–5-0.0713%24 Sept →
inferno7–9-0.049%24 Sept →
inferno8–8-0.094%24 Sept →
inferno2–9-0.0913%24 Sept →
dust24–13-0.0810%23 Sept →
inferno9–40.1315%23 Sept →
inferno9–7-0.153%23 Sept →
inferno7–9-0.056%20 Sept →
inferno9–60.006%20 Sept →
mirage13–40.0411%19 Sept →
nuke3–9-0.1525%19 Sept →
inferno8–8-0.0912%19 Sept →
nuke13–7-0.0314%17 Sept →
inferno6–9-0.168%17 Sept →
inferno9–7-0.1219%17 Sept →
dust23–13-0.0717%17 Sept →
inferno8–80.0113%17 Sept →
inferno5–90.0215%17 Sept →
inferno7–9-0.087%17 Sept →
inferno1–9-0.1423%17 Sept →

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.