Pyxenity <3

Pyxenity <3 — CS2 Stats

76561199270760907[U:1:1310495179]Steam profile ↗1 game ban

1,790Tracked matches44%Win rate2024Tracked since
669Hours in CS
CSDB Rating3.5 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim25
Positioning48
Utility37

0–100 skill scores via Leetify.

Recent form

STEADY40–51–9Last 10040%Win rateLTWLWLLWLW

Last 10 vs previous 10: −10pp win rate · −0.08 avg rating · −1.2pp headshot accuracy · +74ms reaction

Win rate −10pp 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

  • 2–2–1 · 40% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 12%
  • Avg reaction 753ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 12%
  • Avg reaction 738ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 701ms

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 (+1.8 against its own average).

Aim2.5
Utility3.7
Positioning4.8
Opening Duels0.5

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

iM

Plays most like iM 67% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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. 709ms 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

Aim2.5
Positioning4.8
Utility3.7
Mechanics5.1
Opening Duels1.4
Win Impact3.1

Composite 3.5/10 (Learning), 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-0.02+0.02
first ⅓ avg -0.04 → last ⅓ avg -0.02
Reaction time714ms+15ms
first ⅓ avg 699ms → last ⅓ avg 714ms
Headshot accuracy13.5%−3.2%
first ⅓ avg 16.7% → 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

0.21Best match rating · 13–0 · nuke, 31 Oct →
100%Best headshot accuracy · 4–7 · nuke, 15 Oct →
422msFastest reaction time · 2–11 · nuke, 15 Oct →
13–0Biggest win · nuke, 31 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–6In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 43% over 70vertigoWeakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
nukeC7030–4043%-0.02
mirageD103–730%-0.03
vertigoD60–60%-0.07
ancient—31–233%-0.04
dust2—31–233%-0.09
cache—21–150%-0.01
office—21–150%-0.07
inferno—21–150%0.00
overpass—11–0100%-0.15
train—11–0100%-0.07

Across the last 100 tracked matches.

Vertigo is currently your weakest sufficiently-sampled map (0% over 6). Start with the 6 essential Vertigo lineups, review the callouts, then spin up a practice server.

Lifetime stats

20,061Lifetime kills
0.62K/D
1,948Matches
39.7%Match win rate
35.1%Headshot %
0.0%Shot accuracy
2,622MVPs
669Hours (in match)
1,824Bombs planted
203Bombs defused

Most-used weapons

MAG-72,549
MAC-101,992
AWP1,935
AK-471,694
SSG 081,182
MP91,118

Lifetime map wins

9,508nuke
885office
838inferno
749vertigo
670dust2
578train
90italy
6ar_baggage

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.

12.8%Headshot accuracy
34.2%Accuracy (enemy spotted)
35.9%Spray accuracy
73.0%Counter-strafing
16.4°Preaim
709msReaction time
36.0%T opening success
35.4%CT opening success
0.39Enemies flashed / flash
8.6%Flash assists
7.34HE damage / grenade
1.68Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 16.3885° — above the 12° mark we flag

    Aim Training →
  2. 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 12.8102% — below the 15% mark we flag

    Aim Training →
  3. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 708.6157ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Vertigo

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

Vertigo callouts & strategy →Vertigo grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage2–13-0.0515%1 Nov →
nuke12–12-0.0928%1 Nov →
nuke5–7-0.067%1 Nov →
nuke4–13-0.047%1 Nov →
nuke13–5-0.046%1 Nov →
nuke10–13-0.0310%1 Nov →
mirage10–13-0.096%1 Nov →
mirage7–0-0.0220%1 Nov →
nuke7–13-0.0424%1 Nov →
nuke9–7-0.050%1 Nov →
mirage4–130.037%31 Oct →
nuke13–90.0215%31 Oct →
nuke9–130.0715%31 Oct →
nuke13–00.218%31 Oct →
nuke11–13-0.019%31 Oct →
nuke11–13-0.0613%31 Oct →
cache13–8-0.0220%31 Oct →
nuke8–130.0823%30 Oct →
mirage13–10.0819%29 Oct →
ancient13–9-0.115%29 Oct →
nuke3–130.0314%29 Oct →
mirage8–13-0.089%29 Oct →
office11–13-0.0719%28 Oct →
mirage13–8-0.028%28 Oct →
ancient12–120.0014%27 Oct →
vertigo12–12-0.0518%27 Oct →
nuke13–10-0.048%27 Oct →
nuke5–13-0.1123%25 Oct →
inferno13–7-0.049%25 Oct →
nuke6–13-0.066%25 Oct →
nuke13–70.0513%24 Oct →
nuke4–13-0.0214%24 Oct →
nuke4–130.0233%24 Oct →
nuke6–130.0318%24 Oct →
nuke13–11-0.0111%24 Oct →
nuke13–9-0.016%23 Oct →
mirage7–13-0.0713%23 Oct →
nuke7–13-0.0214%23 Oct →
nuke13–50.0110%23 Oct →
overpass13–11-0.1511%23 Oct →
nuke13–10-0.059%22 Oct →
nuke13–7-0.0225%22 Oct →
vertigo4–13-0.108%22 Oct →
nuke12–12-0.0219%22 Oct →
nuke13–8-0.088%22 Oct →
nuke13–6-0.0540%22 Oct →
nuke7–13-0.0414%21 Oct →
nuke6–13-0.0829%21 Oct →
nuke13–9-0.047%21 Oct →
nuke13–110.0024%20 Oct →
inferno11–130.0512%20 Oct →
vertigo5–13-0.0726%20 Oct →
nuke3–13-0.0833%20 Oct →
nuke5–13-0.079%20 Oct →
nuke8–13-0.0718%20 Oct →
nuke6–13-0.109%20 Oct →
nuke11–13-0.0820%20 Oct →
nuke6–130.0322%20 Oct →
nuke12–120.0313%20 Oct →
nuke12–12-0.016%18 Oct →
nuke9–13-0.0321%18 Oct →
nuke13–70.0315%18 Oct →
nuke13–9-0.0518%18 Oct →
nuke11–130.015%18 Oct →
office13–5-0.0623%18 Oct →
dust27–13-0.0712%18 Oct →
nuke7–13-0.026%17 Oct →
nuke13–11-0.0419%17 Oct →
nuke9–13-0.0520%17 Oct →
nuke9–13-0.0821%17 Oct →
nuke13–5-0.0137%17 Oct →
nuke12–12-0.0115%17 Oct →
nuke12–12-0.0118%17 Oct →
nuke9–20.010%17 Oct →
dust24–13-0.118%17 Oct →
dust28–2-0.0912%17 Oct →
ancient7–13-0.024%17 Oct →
nuke12–12-0.019%16 Oct →
vertigo10–13-0.0916%16 Oct →
vertigo6–13-0.0523%16 Oct →
nuke5–13-0.0820%16 Oct →
mirage6–13-0.0418%16 Oct →
mirage1–13-0.0814%16 Oct →
train13–8-0.0723%16 Oct →
nuke13–1-0.0617%15 Oct →
nuke4–70.03100%15 Oct →
nuke2–11-0.060%15 Oct →
nuke13–7-0.0925%15 Oct →
vertigo1–8-0.0310%15 Oct →
nuke13–10-0.064%15 Oct →
nuke13–10-0.047%14 Oct →
nuke13–9-0.066%14 Oct →
nuke3–13-0.0714%14 Oct →
nuke13–80.0322%14 Oct →
nuke13–9-0.115%13 Oct →
nuke11–3-0.0111%13 Oct →
nuke8–13-0.029%12 Oct →
cache9–13-0.0012%12 Oct →
nuke13–50.0112%12 Oct →
nuke10–130.0021%12 Oct →

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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