Jotupure

Jotupure — CS2 Stats

76561199370976609[U:1:1410710881]Steam profile ↗✓ No bans

1,554Tracked matches47%Win rate2022Tracked since
CSDB Rating5.5 SolidSupport
Premier CS Rating19,564Top 50% of 213,399 CSDB-tracked playersPurple band · top ~10.2% of ranked players (population est.)
CSDB Leaderboard#92165 of 259986 tracked
FaceitLevel 6 · 1,515 ELOTop 54.0% of ranked FACEIT players
WingmanSupreme Master First Class
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Nov 2026 (2 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: 19,564 -2,038 29 Jul – 3 Nov · 18 days played
19,37422,230peak 22,23029 Jul3 Nov
Faceit ELO: 1,515 +0 31 Aug – 1 Nov · 4 observations
1,5151,515peak 1,51531 Aug1 Nov
22,230Peak Premier in tracked matches
1,515Highest Faceit ELO seen on CSDB
41Days played since 2026-07-28

Faceit ELO

  • At peak — 1,515
  • Next: Level 8 at 1,531 — 16 to go
  • Reached: Level 7 · Level 6 · Level 5 · Level 4
  • Level 7 first seen 2026-08-31
  • Level 6 first seen 2026-08-31

Premier CS Rating

  • 2,666 below peak (22,230)
  • -539 over 30 days · declining
  • -2,666 over 90 days
  • Next: Pink band at 20,000 — 436 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Pink band first seen 2026-08-31
  • Purple band first seen 2026-08-31

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGJotupureFACEITLevel 6 · 1,515 ELOSTANDINGTop 54.0% of rankedPREMIER19,564 · Purple bandPEAK ELO1,515csdb.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

Aim60
Positioning62
Utility63

0–100 skill scores via Leetify.

Recent form

STEADY43–55–2Last 10043%Win rateWWLLLWLWWW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −0.1pp headshot accuracy · −24ms 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

  • 2–3 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 11%
  • Avg reaction 553ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 13%
  • Avg reaction 538ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 550ms

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 (+1.5 against its own average).

Aim6.0
Utility6.3
Positioning6.2
Opening Duels2.8
Clutch3.8

Strong CT-side openerEffective flashesLimited 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

iM

Plays most like iM 77% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Strengths

Flashes. 0.84 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 51% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 552ms 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

Aim6.0
Positioning6.2
Utility6.3
Mechanics5.6
Opening Duels3.2
Win Impact3.9

Composite 5.5/10 (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 rating-0.01−0.01
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time555ms−56ms
first ⅓ avg 611ms → last ⅓ avg 555ms
Headshot accuracy13.1%−1.6%
first ⅓ avg 14.7% → last ⅓ avg 13.1%

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

0.16Best match rating · 13–2 · anubis, 3 Nov →
27%Best headshot accuracy · 13–4 · cache, 10 Aug →
391msFastest reaction time · 13–2 · anubis, 3 Nov →
13–2Biggest win · anubis, 3 Nov →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W2Current streak
6–4In matches decided by ≤2 rounds
11Overtime games

Map breakdown

trainBest map · 60% over 5infernoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
ancientA2313–1057%0.01
anubisD186–1233%-0.01
cacheC188–1044%0.01
nukeD124–833%-0.01
dust2C83–538%0.00
infernoD61–517%-0.01
trainA53–260%0.01
office—42–250%-0.02
vertigo—42–250%0.02
mirage—21–150%0.03

Across the last 100 tracked matches.

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

Faceit stats

Combat

510Matches
50%Win rate
1.14Avg K/D
79.5ADR
35%Headshot %

Clutches & streaks

39%1v1 clutch win
21%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWWLW

MapMatchesWin rateAvg K/DAvg kills
Ancient11163%1.2116.2
Nuke9052%1.2217.0
Dust25536%1.0214.6
Mirage5040%1.0114.1
Anubis4347%1.1615.5
Inferno3549%1.1415.2
Overpass2839%1.0214.1
Train2365%1.1414.3

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.

13.0%Headshot accuracy
34.5%Accuracy (enemy spotted)
34.8%Spray accuracy
75.0%Counter-strafing
10.1°Preaim
552msReaction time
34.6%T opening success
50.6%CT opening success
0.84Enemies flashed / flash
10.0%Flash assists
13.01HE damage / grenade
4.42Flashes / 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 12.9627% — 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 34.5964% — below the 40% mark we flag

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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis13–20.1616%3 Nov →
cache6–00.0410%3 Nov →
nuke11–130.0211%3 Nov →
mirage2–130.0110%30 Oct →
office6–13-0.089%30 Oct →
anubis13–10-0.0612%29 Oct →
ancient6–13-0.0313%29 Oct →
cache22–19-0.0212%29 Oct →
office13–7-0.0520%28 Oct →
cache13–20.0118%26 Oct →
ancient19–15-0.0123%25 Oct →
ancient13–80.048%25 Oct →
cache6–13-0.077%25 Oct →
nuke5–13-0.017%24 Oct →
cache5–13-0.0425%24 Oct →
dust28–13-0.0114%19 Oct →
ancient5–13-0.0316%19 Oct →
dust213–4-0.027%18 Oct →
cache8–13-0.057%18 Oct →
cache13–40.1017%18 Oct →
ancient4–13-0.078%18 Oct →
ancient9–130.0314%15 Oct →
cache13–80.058%15 Oct →
ancient13–50.0218%15 Oct →
dust28–13-0.048%11 Oct →
cache13–110.0219%11 Oct →
cache11–13-0.0010%8 Oct →
nuke7–13-0.046%8 Oct →
inferno6–13-0.0415%8 Oct →
train13–70.0514%8 Oct →
train6–13-0.0222%8 Oct →
train7–13-0.0313%7 Oct →
dust213–80.0015%5 Oct →
ancient13–20.0919%5 Oct →
anubis13–40.039%5 Oct →
dust213–90.0316%4 Oct →
nuke5–13-0.109%4 Oct →
anubis6–13-0.0111%27 Sept →
nuke11–130.0116%27 Sept →
inferno7–130.0417%24 Sept →
vertigo9–130.0216%24 Sept →
vertigo13–4-0.027%24 Sept →
anubis8–13-0.0320%22 Sept →
anubis10–13-0.078%22 Sept →
cache5–13-0.0314%20 Sept →
ancient8–13-0.0311%20 Sept →
cache7–130.0919%20 Sept →
anubis13–50.0116%15 Sept →
nuke8–130.0111%15 Sept →
nuke13–50.1213%15 Sept →
inferno13–90.0112%15 Sept →
ancient16–140.0314%6 Sept →
anubis10–13-0.0210%6 Sept →
office13–70.0314%4 Sept →
anubis15–150.0117%3 Sept →
ancient16–140.0316%2 Sept →
inferno12–16-0.027%2 Sept →
dust25–130.029%2 Sept →
office10–130.0115%2 Sept →
ancient10–130.0214%30 Aug →
anubis9–13-0.0015%30 Aug →
nuke12–16-0.0615%24 Aug →
ancient2–13-0.0411%24 Aug →
cache8–13-0.0111%23 Aug →
ancient9–13-0.0612%20 Aug →
cache8–130.0213%20 Aug →
ancient13–5-0.007%20 Aug →
train13–9-0.0316%17 Aug →
dust29–130.0516%16 Aug →
ancient22–190.0012%16 Aug →
cache13–50.0714%16 Aug →
cache10–13-0.008%15 Aug →
ancient13–90.0117%15 Aug →
nuke13–100.0318%15 Aug →
train13–50.0911%13 Aug →
cache13–40.0527%10 Aug →
anubis8–13-0.1019%10 Aug →
cache11–130.0216%6 Aug →
anubis6–130.0112%6 Aug →
ancient4–13-0.0317%6 Aug →
nuke13–11-0.0016%4 Aug →
inferno4–130.0412%4 Aug →
ancient13–110.037%4 Aug →
dust25–13-0.0319%4 Aug →
vertigo13–70.057%3 Aug →
ancient13–40.1016%2 Aug →
anubis6–13-0.0318%2 Aug →
ancient13–160.0516%1 Aug →
anubis7–13-0.0523%1 Aug →
mirage13–100.0412%1 Aug →
anubis8–13-0.0821%31 Jul →
inferno3–13-0.0814%31 Jul →
anubis8–13-0.0113%31 Jul →
nuke16–19-0.0810%31 Jul →
anubis13–9-0.0811%31 Jul →
vertigo12–120.0113%31 Jul →
ancient13–7-0.0220%29 Jul →
nuke16–14-0.037%29 Jul →
ancient13–20.0510%29 Jul →
anubis13–90.0917%28 Jul →

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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