Purtsi

Purtsi — CS2 Stats

76561198044302601[U:1:84036873]Steam profile ↗✓ No bans

763Tracked matches60%Win rate2020Tracked since
5,002Hours in CS14Hrs last 2 wks
CSDB Rating6.3 SolidPositional Player
WingmanLegendary Eagle Master
Ladder ranks via Leetify

Performance scores

Aim70
Positioning61
Utility48

0–100 skill scores via Leetify.

Recent form

HOT55–40–5Last 10055%Win rateWWWWWWLLWL

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating · +0.7pp headshot accuracy · −52ms reaction

Win rate up 20pp 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

  • 5–0 · 100% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 17%
  • Avg reaction 513ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 19%
  • Avg reaction 533ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 18%
  • Avg reaction 559ms

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 (+1.5 against its own average).

Aim7.0
Utility4.8
Positioning6.1
Opening Duels3.6
Clutch3.8

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

iM

Plays most like iM 91% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: 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

Reaction time. 576ms 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

Aim7.0
Positioning6.1
Utility4.8
Mechanics6.6
Opening Duels4.0
Win Impact8.3

Composite 6.3/10 (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 rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time581ms−33ms
first ⅓ avg 614ms → last ⅓ avg 581ms
Headshot accuracy19.7%+3.2%
first ⅓ avg 16.4% → last ⅓ avg 19.7%

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

0.35Best match rating · 9–2 · eldorado, 10 Jul →
34%Best headshot accuracy · 13–8 · anubis, 28 Jan →
414msFastest reaction time · 13–10 · anubis, 25 Mar →
13–0Biggest win · ancient, 28 Oct →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W6Current streak
7–10In matches decided by ≤2 rounds
3Overtime games

Map breakdown

dust2Best map · 80% over 5infernoWeakest map · 24% over 17
MapGradePlayedRecordWin rateAvg rating
infernoD174–1324%-0.02
ancientS1310–377%0.01
nukeS107–370%0.01
anubisS96–367%-0.03
sanctumS97–278%0.06
mirageC52–340%-0.03
dust2S54–180%0.04
poseidonC52–340%-0.00
trainC52–340%-0.01
eldorado—42–250%0.07
rooftop—42–250%0.05
cache—32–167%0.03
debris—31–233%-0.02
vertigo—21–150%0.03
overpass—21–150%0.05
dogtown—20–20%-0.03
brewery—11–0100%0.00
palais—11–0100%0.18

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (24% over 17). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

329,875Lifetime kills
1.44K/D · Top 5% of tracked players
16,553Matches
44.3%Match win rate
41.9%Headshot %
20.1%Shot accuracy · Top 5% of tracked players
23,407MVPs
3,429Hours (in match)
5,927Bombs planted
1,769Bombs defused

Most-used weapons

AK-47113,167
AWP65,133
P2507,976
FAMAS5,082
SSG 084,610

Lifetime map wins

8,537dust2
7,166inferno
5,290train
5,071nuke
2,499cbble
1,100vertigo
1,065lake
901safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

650Matches
50%Win rate
1.15Avg K/D
67.5ADR
41%Headshot %

Clutches & streaks

39%1v1 clutch win
23%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Ancient3047%0.9813.8
Anubis2264%0.9111.7
Mirage1631%0.9413.3
Nuke1362%1.1413.9
Inferno1346%0.9114.8
Dust2850%1.1812.9
Overpass875%1.3814.9
Train667%0.9819.0

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.

18.2%Headshot accuracy
34.9%Accuracy (enemy spotted)
37.3%Spray accuracy
79.7%Counter-strafing
10.3°Preaim
576msReaction time
45.6%T opening success
46.8%CT opening success
0.53Enemies flashed / flash
10.4%Flash assists
6.78HE damage / grenade
6.43Flashes / match

Recommended for you

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.

24% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–4-0.0313%30 Oct →
inferno13–70.0017%30 Oct →
ancient13–10.0414%30 Oct →
dust213–20.0523%30 Oct →
ancient13–00.0719%28 Oct →
cache13–11-0.0020%28 Oct →
inferno8–13-0.0613%20 Oct →
anubis8–13-0.078%20 Oct →
dust213–110.0726%9 Oct →
inferno10–130.0531%9 Oct →
nuke13–10-0.0713%9 Oct →
dust28–130.0824%18 Sept →
cache13–80.0616%18 Sept →
nuke13–70.0615%18 Sept →
anubis5–13-0.085%18 Sept →
nuke13–8-0.0417%9 Sept →
inferno9–60.0631%29 Aug →
cache8–130.0219%20 Aug →
poseidon5–9-0.1313%7 Aug →
debris4–9-0.0426%18 Jul →
eldorado9–40.0231%16 Jul →
eldorado7–9-0.0619%16 Jul →
debris3–9-0.0733%10 Jul →
eldorado4–9-0.0526%10 Jul →
eldorado9–20.3523%10 Jul →
debris9–60.0512%10 Jul →
sanctum9–60.0225%27 Jun →
inferno8–80.0520%27 Jun →
poseidon9–50.0117%27 Jun →
nuke9–30.1022%21 Jun →
inferno8–8-0.0219%21 Jun →
sanctum9–60.0218%16 May →
inferno8–80.0120%1 May →
inferno3–9-0.0917%25 Apr →
sanctum3–9-0.175%25 Apr →
nuke8–80.0420%15 Mar →
poseidon9–50.0817%15 Mar →
sanctum9–10.2218%7 Mar →
poseidon8–80.0424%7 Mar →
inferno11–13-0.025%22 Feb →
sanctum9–30.055%7 Feb →
sanctum9–5-0.0331%1 Feb →
poseidon5–9-0.0215%1 Feb →
anubis13–80.0334%28 Jan →
mirage8–130.0017%28 Jan →
ancient16–120.0028%28 Jan →
nuke13–10.0218%28 Jan →
sanctum4–9-0.038%27 Jan →
sanctum9–20.2413%22 Jan →
sanctum9–00.2633%22 Jan →
rooftop7–9-0.0214%17 Jan →
rooftop9–30.0210%17 Jan →
vertigo5–9-0.1213%17 Jan →
inferno3–9-0.0533%17 Jan →
rooftop4–9-0.0116%30 Nov →
rooftop9–40.2232%5 Oct →
inferno4–90.0124%5 Oct →
inferno14–16-0.028%4 Oct →
overpass11–130.0214%4 Oct →
train7–13-0.0316%4 Oct →
ancient13–110.0120%4 Oct →
ancient13–80.0319%1 Oct →
overpass13–40.0814%22 Sept →
train10–13-0.0327%8 Sept →
ancient13–50.1229%8 Sept →
ancient13–11-0.0413%3 Sept →
inferno3–9-0.176%29 Aug →
inferno1–9-0.2218%12 Jul →
vertigo9–30.1829%4 Jul →
dogtown7–9-0.0722%22 Jun →
dogtown7–90.0124%14 Jun →
nuke7–9-0.0116%17 May →
brewery9–50.0021%17 May →
nuke4–9-0.0311%2 May →
inferno13–90.0320%28 Apr →
ancient13–5-0.0313%28 Apr →
anubis13–10-0.0311%24 Apr →
dust213–8-0.0222%24 Apr →
mirage13–90.0019%14 Apr →
ancient11–130.0417%3 Apr →
inferno6–13-0.0614%3 Apr →
anubis13–11-0.0410%3 Apr →
palais9–40.1816%1 Apr →
ancient13–110.0212%26 Mar →
nuke13–40.0119%25 Mar →
ancient13–9-0.0415%25 Mar →
anubis13–10-0.0216%25 Mar →
train13–11-0.0323%25 Mar →
nuke13–80.0514%26 Feb →
anubis11–13-0.075%26 Feb →
ancient9–130.0012%26 Feb →
train16–190.0110%25 Feb →
mirage10–13-0.0716%25 Feb →
anubis13–6-0.0121%11 Feb →
mirage10–13-0.057%10 Feb →
train13–50.0029%10 Feb →
dust213–30.037%10 Feb →
anubis13–8-0.0217%4 Feb →
inferno13–70.1124%4 Feb →
ancient8–13-0.0513%4 Feb →

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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