Pupple

Pupple — CS2 Stats

76561198337385211[U:1:377119483]Steam profile ↗✓ No bans

169Tracked matches67%Win rate2025Tracked since
123Hours in CS4Hrs last 2 wks
CSDB Rating6.1 SolidPositional Player
Ladder ranks via Leetify

Performance scores

Aim77
Positioning60
Utility20

0–100 skill scores via Leetify.

Recent form

HOT59–30–11Last 10059%Win rateWWWTWTWWWW

Last 10 vs previous 10: +30pp win rate · −0.01 avg rating · −0.0pp headshot accuracy · −86ms reaction

Win rate up 30pp 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 (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 4–0–1 · 80% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 19%
  • Avg reaction 456ms

Last 10

  • 8–0–2 · 80% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 19%
  • Avg reaction 473ms

Last 20

  • 13–5–2 · 65% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 19%
  • Avg reaction 516ms

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).

Aim7.7
Utility2.0
Positioning6.0
Opening Duels3.3

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 86% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower opening-duel success; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim7.7
Positioning6.0
Utility2.0
Mechanics5.9
Opening Duels3.8
Win Impact10.0

Composite 6.1/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.02
first ⅓ avg 0.01 → last ⅓ avg 0.02
Reaction time539ms−26ms
first ⅓ avg 565ms → last ⅓ avg 539ms
Headshot accuracy19.6%+0.9%
first ⅓ avg 18.7% → last ⅓ avg 19.6%

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

0.15Best match rating · 16–12 · inferno, 1 Jul →
43%Best headshot accuracy · 4–0 · mirage, 3 Feb →
375msFastest reaction time · 6–2 · mirage, 28 Oct →
13–0Biggest win · mirage, 17 Feb →

Across the last 100 tracked matches.

Highlights

4Longest win streak
W3Current streak
5–4In matches decided by ≤2 rounds
2Overtime games

Map breakdown

mirageBest map · 88% over 17overpassWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
infernoA3118–1358%0.00
mirageS1715–288%0.04
nukeB157–847%0.02
ancientB147–750%0.01
dust2S118–373%0.03
overpassD72–529%0.01
cache—42–250%0.00
anubis—10–10%0.10

Across the last 100 tracked matches.

Overpass is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Overpass lineups, review the callouts, then spin up a practice server.

Lifetime stats

2,887Lifetime kills
1.20K/D · Top 25% of tracked players
193Matches
62.7%Match win rate · Top 5% of tracked players
52.1%Headshot % · Top 25% of tracked players
0.2%Shot accuracy
463MVPs
64Hours (in match)
316Bombs planted
53Bombs defused

Most-used weapons

Lifetime map wins

505inferno
261nuke
221dust2
4vertigo

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.

18.9%Headshot accuracy
36.3%Accuracy (enemy spotted)
35.1%Spray accuracy
76.5%Counter-strafing
8.1°Preaim
548msReaction time
42.0%T opening success
48.5%CT opening success
0.39Enemies flashed / flash
2.5%Flash assists
7.70HE damage / grenade
1.99Flashes / 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. 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 0.389 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Overpass

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 7 tracked games — your weakest map with enough games to be worth reading into.

Overpass callouts & strategy →Overpass grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage6–20.0627%28 Oct →
cache13–2-0.0217%28 Oct →
mirage13–80.0915%28 Oct →
nuke12–120.0112%20 Oct →
dust213–100.1124%14 Oct →
nuke12–120.0323%13 Oct →
cache13–20.0323%12 Oct →
mirage13–5-0.039%12 Oct →
nuke13–10.0419%12 Oct →
nuke13–8-0.0323%5 Oct →
ancient3–11-0.0526%5 Oct →
dust29–13-0.0723%29 Sept →
mirage13–11-0.0423%29 Sept →
nuke13–50.0818%28 Jul →
ancient13–70.0614%8 Jul →
anubis11–130.1014%6 Jul →
mirage8–130.1221%3 Jul →
dust213–90.0913%2 Jul →
inferno16–120.1519%1 Jul →
inferno6–13-0.0320%1 Jul →
nuke13–30.1212%29 Jun →
inferno4–13-0.0522%29 Jun →
nuke8–13-0.0112%29 Jun →
inferno13–9-0.0323%15 Jun →
nuke8–80.0138%1 Jun →
inferno9–30.1128%1 Jun →
cache8–130.0220%31 May →
cache12–12-0.0112%12 May →
nuke10–13-0.077%22 Apr →
overpass8–80.0121%11 Apr →
inferno9–40.0731%11 Apr →
inferno5–9-0.1417%4 Apr →
dust213–110.0925%3 Apr →
mirage13–100.0432%3 Apr →
mirage13–80.0329%26 Mar →
dust213–10.0129%25 Mar →
ancient11–130.0228%25 Mar →
inferno13–30.0130%24 Mar →
dust213–70.0413%24 Mar →
inferno13–8-0.0214%23 Mar →
inferno13–11-0.059%19 Mar →
nuke10–130.0127%18 Mar →
inferno13–30.0933%18 Mar →
mirage13–60.0115%17 Mar →
inferno12–12-0.0517%17 Mar →
overpass13–60.0817%16 Mar →
nuke13–10.1316%13 Mar →
dust213–80.0524%12 Mar →
overpass3–13-0.0925%2 Mar →
dust213–6-0.0127%2 Mar →
inferno0–13-0.0827%1 Mar →
nuke12–12-0.0321%28 Feb →
mirage13–100.0316%24 Feb →
inferno12–12-0.0524%23 Feb →
nuke13–100.0028%22 Feb →
mirage13–50.1225%21 Feb →
ancient7–13-0.0121%20 Feb →
ancient13–50.0819%18 Feb →
nuke12–12-0.0229%18 Feb →
mirage13–00.0526%17 Feb →
inferno11–130.0319%17 Feb →
overpass13–10.1326%17 Feb →
ancient10–13-0.0314%17 Feb →
inferno13–70.1021%16 Feb →
inferno3–13-0.0915%10 Feb →
ancient13–90.0121%10 Feb →
mirage13–100.1015%8 Feb →
overpass4–13-0.0511%8 Feb →
mirage16–14-0.0220%8 Feb →
inferno7–13-0.0334%8 Feb →
inferno12–12-0.0818%6 Feb →
dust22–13-0.0835%6 Feb →
inferno12–120.0820%6 Feb →
ancient13–8-0.0219%6 Feb →
inferno11–130.0624%6 Feb →
overpass5–130.0122%6 Feb →
inferno13–60.0314%5 Feb →
ancient6–13-0.0321%5 Feb →
mirage4–00.1443%3 Feb →
ancient13–50.1318%3 Feb →
mirage1–13-0.0615%3 Feb →
dust210–130.1125%2 Feb →
inferno13–30.0311%31 Jan →
overpass9–13-0.0221%31 Jan →
inferno13–10-0.058%31 Jan →
inferno13–2-0.073%30 Jan →
inferno9–40.1017%30 Jan →
nuke13–7-0.0318%30 Jan →
ancient7–130.0314%30 Jan →
mirage13–50.0013%30 Jan →
inferno13–2-0.004%30 Jan →
inferno13–60.0923%30 Jan →
mirage13–50.0519%29 Jan →
inferno10–13-0.0231%29 Jan →
ancient13–10-0.0416%29 Jan →
dust213–20.027%29 Jan →
inferno13–11-0.0619%29 Jan →
ancient9–13-0.0116%29 Jan →
inferno13–50.0315%29 Jan →
ancient13–80.0223%28 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 →

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