ToxicPossum

ToxicPossum — CS2 Stats

US76561198071420746[U:1:111155018]Steam profile ↗✓ No bans

313Tracked matches45%Win rate2020Tracked since
228Hours in CS
CSDB Rating4.5 DevelopingAll-Rounder
Premier CS Rating3,824Grey band · top ~83.8% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Sep 2026 (41 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: 3,824 +840 31 Aug – 1 Sept · 2 days played
2,9843,824peak 3,82431 Aug1 Sept
3,824Peak Premier in tracked matches
35Days played since 2026-07-24

Premier CS Rating

  • At peak — 3,824
  • Next: Light Blue band at 5,000 — 1,176 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 rate36.3%38.2%39.9%3.7% short
Shot accuracy6.0%3.6%7.0%1.0% short
Kill/death ratio1.060.830.92above
Match win rate47.1%40.2%42.3%above

This profile matches the typical Light Blue band player on 2 of 4 comparable metrics.

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.GGToxicPossumPREMIER3,824 · 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

Aim58
Positioning42
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY42–50–8Last 10042%Win rateWLLLLWWWLW

Last 10 vs previous 10: +30pp win rate · +0.05 avg rating · +1.1pp headshot accuracy · +3ms reaction

Win rate up 30pp 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

  • 1–4 · 20% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 15%
  • Avg reaction 652ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 15%
  • Avg reaction 639ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 638ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim5.8
Utility4.5
Positioning4.2
Opening Duels3.6

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

device

Plays most like device 86% playstyle similarity

Most alike: opening-duel success, positioning profile.

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 51% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 648ms 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

Aim5.8
Positioning4.2
Utility4.5
Mechanics7.5
Opening Duels2.7
Win Impact3.3

Composite 4.5/10 (Developing), 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-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time654ms−8ms
first ⅓ avg 662ms → last ⅓ avg 654ms
Headshot accuracy13.5%+1.5%
first ⅓ avg 12.0% → last ⅓ avg 13.5%

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

0.15Best match rating · 12–12 · cache, 12 Aug →
34%Best headshot accuracy · 13–4 · cache, 26 Aug →
438msFastest reaction time · 7–13 · nuke, 9 Aug →
13–0Biggest win · inferno, 11 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–5In matches decided by ≤2 rounds
1Overtime games

Map breakdown

anubisBest map · 67% over 9mirageWeakest map · 0% over 7
MapGradePlayedRecordWin rateAvg rating
cacheB2210–1245%-0.00
ancientB136–746%0.00
infernoA116–555%-0.00
vertigoA116–555%-0.01
nukeD92–722%-0.03
anubisS96–367%0.01
mirageD70–70%-0.02
trainD62–433%-0.01
officeD62–433%-0.01
dust2—41–325%-0.02
shelter—21–150%0.00

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (0% over 7). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

11,202Lifetime kills
1.06K/D · Top 25% of Grey band
700Matches
47.1%Match win rate · Top 10% of Grey band
36.3%Headshot %
6.0%Shot accuracy · Top 50% of Grey band
1,667MVPs
228Hours (in match)
880Bombs planted
198Bombs defused

Most-used weapons

Lifetime map wins

1,187dust2
901nuke
683inferno
403vertigo
265train
168office
58bank
49safehouse

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.

13.0%Headshot accuracy
33.5%Accuracy (enemy spotted)
37.5%Spray accuracy
83.7%Counter-strafing
10.0°Preaim
648msReaction time
29.7%T opening success
51.3%CT opening success
0.51Enemies flashed / flash
3.6%Flash assists
6.61HE damage / grenade
5.78Flashes / 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 12.9831% — below the 15% mark we flag

    Aim Training →
  2. 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 29.7025% — below the 40% mark we flag

Spend your practice time on Mirage

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

0% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–10-0.0212%7 Sept →
cache3–130.0111%7 Sept →
inferno8–13-0.0316%2 Sept →
cache6–13-0.0018%1 Sept →
mirage9–130.0720%1 Sept →
ancient13–4-0.0110%1 Sept →
inferno13–5-0.0113%1 Sept →
ancient13–80.0414%31 Aug →
nuke10–13-0.0213%31 Aug →
cache13–40.1019%31 Aug →
cache10–13-0.0210%29 Aug →
dust26–13-0.059%29 Aug →
nuke2–13-0.0414%29 Aug →
ancient5–13-0.0221%29 Aug →
nuke13–4-0.0410%26 Aug →
inferno4–13-0.067%26 Aug →
inferno10–13-0.046%26 Aug →
cache13–4-0.0234%26 Aug →
vertigo10–13-0.0415%26 Aug →
ancient9–13-0.069%26 Aug →
cache9–13-0.0310%25 Aug →
ancient13–90.0114%24 Aug →
vertigo13–60.0211%24 Aug →
cache8–13-0.0219%24 Aug →
vertigo13–60.045%23 Aug →
anubis6–13-0.0312%23 Aug →
anubis5–10.036%23 Aug →
ancient15–150.0112%23 Aug →
cache13–8-0.078%22 Aug →
cache7–20.0512%22 Aug →
vertigo4–13-0.0519%19 Aug →
train6–13-0.1125%18 Aug →
vertigo13–70.0314%18 Aug →
train8–13-0.0411%17 Aug →
cache5–2-0.0720%17 Aug →
vertigo11–13-0.029%17 Aug →
office11–13-0.0225%17 Aug →
train11–130.0710%16 Aug →
dust213–9-0.0213%16 Aug →
ancient9–130.018%15 Aug →
mirage1–13-0.0610%15 Aug →
cache13–110.0113%14 Aug →
anubis11–13-0.016%14 Aug →
inferno8–130.0422%14 Aug →
office6–13-0.077%14 Aug →
vertigo13–9-0.0414%14 Aug →
nuke7–13-0.087%13 Aug →
mirage5–13-0.0414%13 Aug →
cache13–10-0.0313%12 Aug →
inferno13–6-0.0012%12 Aug →
cache12–120.1510%12 Aug →
nuke10–13-0.029%11 Aug →
mirage2–13-0.0513%11 Aug →
inferno13–00.0614%11 Aug →
nuke7–130.0115%9 Aug →
anubis13–50.148%9 Aug →
cache1–13-0.085%9 Aug →
nuke4–130.004%9 Aug →
ancient2–130.018%8 Aug →
inferno13–10-0.058%8 Aug →
mirage7–13-0.076%8 Aug →
cache12–120.0214%7 Aug →
nuke2–13-0.076%7 Aug →
office4–13-0.0411%7 Aug →
shelter13–110.0214%6 Aug →
ancient12–120.0216%5 Aug →
vertigo2–13-0.0121%5 Aug →
vertigo12–12-0.0713%5 Aug →
office12–12-0.0210%5 Aug →
office13–40.0010%4 Aug →
cache13–70.029%4 Aug →
anubis13–11-0.0024%4 Aug →
dust29–13-0.0110%4 Aug →
ancient4–130.0111%3 Aug →
train13–50.048%2 Aug →
inferno13–110.0210%2 Aug →
train13–11-0.004%2 Aug →
cache8–130.0124%2 Aug →
cache13–110.0612%1 Aug →
cache2–13-0.0413%1 Aug →
anubis3–13-0.052%1 Aug →
vertigo13–80.0612%31 Jul →
vertigo13–60.025%31 Jul →
mirage12–120.1016%30 Jul →
cache13–9-0.0015%30 Jul →
office13–80.1112%30 Jul →
cache6–13-0.0611%30 Jul →
train8–13-0.0216%30 Jul →
dust211–130.018%30 Jul →
inferno9–130.0117%28 Jul →
shelter8–13-0.0116%28 Jul →
anubis13–11-0.0314%28 Jul →
nuke13–7-0.064%27 Jul →
cache12–12-0.0210%26 Jul →
mirage6–13-0.0812%26 Jul →
ancient13–100.0410%26 Jul →
ancient13–6-0.020%26 Jul →
anubis13–30.0331%25 Jul →
anubis13–70.0417%24 Jul →
inferno13–90.0311%24 Jul →

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.