possumi

possumi — CS2 Stats

76561198077145384[U:1:116879656]Steam profile ↗✓ No bans

1,645Tracked matches53%Win rate2020Tracked since
CSDB Rating5.3 DevelopingClutch Specialist
Premier CS Rating13,227Blue band · top ~37.8% of ranked players (population est.)
FaceitLevel 6Top 54.0% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGpossumiFACEITLevel 6STANDINGTop 54.0% of rankedPREMIER13,227 · Blue bandcsdb.gg/stats

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Performance scores

Aim58
Positioning64
Utility50

0–100 skill scores via Leetify.

Recent form

STEADY40–55–5Last 10040%Win rateLWLLWWWLWW

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · +0.8pp headshot accuracy · +3ms reaction

Win rate 0pp 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

  • 2–3 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 10%
  • Avg reaction 544ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 565ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 563ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+1.2 against its own average).

Aim5.8
Utility5.0
Positioning6.4
Opening Duels3.7
Clutch6.6

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

jL

Plays most like jL 79% 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

Reaction time. 564ms 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
Positioning6.4
Utility5.0
Mechanics4.7
Opening Duels5.2
Win Impact6.1

Composite 5.3/10 (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-0.00+0.02
first ⅓ avg -0.02 → last ⅓ avg -0.00
Reaction time584ms−36ms
first ⅓ avg 620ms → last ⅓ avg 584ms
Headshot accuracy11.3%−1.7%
first ⅓ avg 13.0% → last ⅓ avg 11.3%

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

0.17Best match rating · 13–7 · inferno, 24 Jun →
33%Best headshot accuracy · 3–8 · inferno, 24 Jun →
406msFastest reaction time · 5–13 · inferno, 8 Jun →
13–0Biggest win · inferno, 16 Jan →

Across the last 100 tracked matches.

Highlights

5Longest win streak
6–7In matches decided by ≤2 rounds
8Overtime games

Map breakdown

cacheBest map · 80% over 10ancientWeakest map · 28% over 18
MapGradePlayedRecordWin rateAvg rating
infernoC207–1335%0.00
ancientD185–1328%-0.01
mirageD134–931%-0.01
cacheS108–280%-0.00
dust2B105–550%-0.00
anubisD93–633%-0.02
overpassC94–544%0.01
nukeB84–450%-0.02
train—20–20%-0.09
vertigo—10–10%0.06

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (28% over 18). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

94Matches
54%Win rate
1.15Avg K/D
78.6ADR
34%Headshot %

Clutches & streaks

53%1v1 clutch win
14%1v2 clutch win
5Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Anubis2080%1.2014.4
Inferno1567%1.2417.5
Ancient1436%1.2515.4
Vertigo1369%1.1814.7
Mirage1127%0.9813.4
Nuke633%1.2017.8
Overpass450%1.5220.0
Dust2425%0.607.8

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.

11.3%Headshot accuracy
34.8%Accuracy (enemy spotted)
38.4%Spray accuracy
71.3%Counter-strafing
9.7°Preaim
564msReaction time
57.1%T opening success
44.4%CT opening success
0.56Enemies flashed / flash
7.2%Flash assists
6.63HE damage / grenade
13.00Flashes / 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 11.2862% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Ancient

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

28% win rate across 18 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient10–130.0216%9 Nov →
cache13–70.0513%9 Nov →
nuke10–130.045%1 Nov →
ancient13–160.027%1 Nov →
cache13–9-0.0710%1 Nov →
dust213–90.0511%1 Nov →
anubis8–10.0910%1 Nov →
mirage9–130.0116%1 Nov →
dust213–11-0.0316%1 Nov →
cache13–7-0.068%30 Oct →
ancient13–5-0.039%30 Oct →
anubis13–40.019%30 Oct →
cache13–2-0.058%30 Oct →
mirage8–13-0.0412%30 Oct →
mirage16–140.0515%30 Oct →
inferno13–100.085%30 Oct →
mirage8–13-0.058%30 Oct →
cache7–130.0421%29 Oct →
dust213–110.018%29 Oct →
nuke9–13-0.028%29 Oct →
inferno13–20.046%9 Oct →
dust211–13-0.0320%9 Oct →
cache13–60.074%9 Oct →
nuke11–13-0.046%9 Oct →
ancient13–2-0.0215%9 Oct →
anubis10–13-0.049%9 Oct →
cache13–100.0110%6 Oct →
mirage10–13-0.0221%6 Oct →
ancient11–13-0.0715%5 Oct →
dust24–13-0.0415%5 Oct →
dust213–110.0115%5 Oct →
cache13–8-0.0011%3 Oct →
dust25–130.0113%3 Oct →
anubis8–130.047%11 Sept →
cache4–13-0.0016%9 Sept →
overpass13–11-0.0110%25 Jun →
mirage13–5-0.044%25 Jun →
inferno7–130.0111%25 Jun →
dust23–13-0.0410%25 Jun →
dust213–90.038%24 Jun →
inferno13–10-0.0112%24 Jun →
anubis10–130.0014%24 Jun →
inferno6–13-0.0210%24 Jun →
inferno13–70.1711%24 Jun →
mirage4–13-0.027%24 Jun →
inferno3–8-0.0733%24 Jun →
mirage0–13-0.040%24 Jun →
ancient10–13-0.027%24 Jun →
ancient11–13-0.076%24 Jun →
inferno5–13-0.0114%23 Jun →
ancient8–13-0.0614%23 Jun →
inferno3–13-0.069%22 Jun →
anubis13–9-0.085%22 Jun →
ancient15–150.029%22 Jun →
overpass8–130.0113%10 Jun →
nuke13–7-0.0014%10 Jun →
mirage11–50.0120%10 Jun →
cache13–110.0114%9 Jun →
inferno13–5-0.0023%9 Jun →
ancient15–150.0312%9 Jun →
mirage13–100.0915%9 Jun →
inferno5–13-0.0217%8 Jun →
anubis9–13-0.0517%8 Jun →
vertigo9–130.069%8 Jun →
mirage7–13-0.0316%5 Jun →
ancient13–20.047%5 Jun →
ancient8–13-0.0314%4 Jun →
dust24–13-0.0126%4 Jun →
ancient1–13-0.1010%4 Jun →
nuke5–13-0.0332%4 Jun →
overpass0–2-0.060%4 Jun →
ancient13–60.0412%25 Apr →
inferno15–150.0320%18 Apr →
mirage9–130.0314%18 Apr →
overpass13–70.0912%18 Apr →
nuke13–10-0.0312%18 Apr →
ancient10–130.046%18 Apr →
anubis11–13-0.0710%18 Apr →
anubis3–13-0.0511%16 Apr →
inferno3–13-0.025%16 Apr →
overpass14–160.019%16 Jan →
inferno13–00.0213%16 Jan →
train10–13-0.0619%16 Jan →
nuke13–7-0.0414%16 Jan →
inferno15–150.007%16 Jan →
overpass13–20.0614%16 Jan →
mirage8–13-0.1014%16 Jan →
overpass15–15-0.0216%14 Jan →
overpass13–50.0011%10 Jan →
nuke13–8-0.0510%10 Jan →
inferno10–130.0015%10 Jan →
overpass10–130.0015%10 Jan →
inferno5–13-0.0621%10 Jan →
inferno13–7-0.0011%10 Jan →
inferno8–13-0.0018%10 Jan →
ancient13–80.0211%28 Sept →
ancient6–13-0.0113%28 Sept →
ancient8–13-0.036%28 Sept →
train2–13-0.1114%28 Sept →
inferno8–13-0.0210%28 Sept →

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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