✪ Panda`

✪ Panda` — CS2 Stats

CA76561197991567327[U:1:31301599]Steam profile ↗✓ No bans

198Tracked matches52%Win rate2021Tracked since
CSDB Rating4.2 Developing
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

1Days observed since 2026-08-28

CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.

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CSDB.GG✪ Panda`FACEITLevel 3STANDINGTop 90.6% of rankedcsdb.gg/stats

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Performance scores

Aim41
Positioning39
Utility53

0–100 skill scores via Leetify.

Recent form

STEADY52435Last 10052%Win rateLWLLLWWLWW

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

Aim4.1
Aggression1.2
Utility5.3
Positioning3.9
Opening Duels0.0

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 68% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-fight frequency; 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

T-side openings. Opening success drops from 36% on CT to 12% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 556ms 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

Aim4.1
Positioning3.9
Utility5.3
Mechanics5.1
Opening Duels0.7
Win Impact5.6

Composite 4.2/10 (Developing), 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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time571ms−51ms
first ⅓ avg 622ms → last ⅓ avg 571ms
Headshot accuracy15.0%+0.6%
first ⅓ avg 14.4% → last ⅓ avg 15.0%

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.

Highlights

0.11Best rating — dust2 13–3
131Biggest win — inferno
7Longest win streak
89In matches decided by ≤2 rounds
16Overtime games

Map breakdown

nukeBest map · 67% over 18dust2Weakest map · 35% over 26
MapGradePlayedRecordWin rateAvg rating
dust2C2691735%-0.02
infernoB25131252%-0.04
nukeS1812667%-0.02
mirageA117464%0.00
overpassA85363%-0.01
ancientS64267%-0.03
cache32167%-0.01
anubis2020%-0.05
train1010%0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (35% over 26). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.8%Headshot accuracy
29.2%Accuracy (enemy spotted)
31.5%Spray accuracy
73.0%Counter-strafing
12.6°Preaim
556msReaction time
12.1%T opening success
35.7%CT opening success
0.59Enemies flashed / flash
5.8%Flash assists
10.12HE damage / grenade
5.41Flashes / 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 12.5877° — 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 14.7677% — below the 15% mark we flag

    Aim Training
Spend your practice time on Dust 2

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

35% win rate across 26 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategyDust 2 grenade lineups

Recent matches

MapScoreRatingHS%Date
mirage14–16-0.0714%29 Aug
inferno13–6-0.0815%29 Aug
nuke6–13-0.0610%29 Aug
mirage9–13-0.0419%8 Aug
dust27–13-0.0415%8 Aug
inferno13–4-0.0229%2 Aug
nuke13–5-0.0311%2 Aug
cache7–13-0.0515%1 Aug
nuke13–90.0121%28 Jul
mirage13–90.0018%28 Jul
dust210–10.1032%28 Jul
inferno10–13-0.0324%24 Jul
cache13–100.0116%24 Jul
nuke10–13-0.0215%24 Jul
dust216–12-0.0113%14 Jul
ancient4–13-0.146%10 Jul
dust210–13-0.0717%3 Jul
inferno15–15-0.0514%2 Jul
dust213–90.0111%2 Jul
nuke13–30.0513%2 Jul
nuke11–13-0.085%17 Jun
dust211–13-0.0418%15 Jun
inferno13–11-0.0514%15 Jun
dust26–130.0017%5 Jun
inferno13–30.009%5 Jun
dust23–13-0.0217%5 Jun
dust216–14-0.0315%23 May
nuke13–7-0.0215%22 May
mirage13–10-0.0110%22 May
inferno8–13-0.086%19 May
anubis2–13-0.0521%19 May
dust210–13-0.0511%19 May
dust213–70.0112%19 May
nuke13–60.0320%16 May
nuke9–13-0.0415%11 May
nuke16–120.0120%10 May
ancient13–20.029%10 May
inferno5–13-0.119%9 May
overpass13–5-0.0622%9 May
inferno8–13-0.0815%7 May
overpass13–60.0316%1 May
ancient13–80.0318%1 May
dust213–16-0.0327%1 May
cache13–4-0.0026%29 Apr
anubis3–13-0.047%10 Apr
nuke13–5-0.0413%10 Apr
dust215–15-0.013%10 Apr
inferno13–11-0.037%9 Apr
dust27–13-0.059%9 Apr
dust29–13-0.0530%6 Apr
dust27–13-0.0517%6 Apr
nuke12–16-0.0018%3 Apr
overpass13–8-0.039%3 Apr
overpass9–130.0113%3 Apr
inferno13–1-0.006%3 Apr
inferno13–11-0.0517%2 Apr
inferno13–90.0132%29 Mar
mirage13–10-0.046%29 Mar
dust213–30.048%29 Mar
inferno14–16-0.0219%28 Mar
overpass13–10-0.0115%28 Mar
inferno11–13-0.0617%23 Mar
dust211–13-0.0114%22 Mar
inferno13–11-0.0621%22 Mar
nuke15–15-0.0018%10 Mar
overpass13–70.0518%8 Mar
nuke16–12-0.057%8 Mar
nuke13–10-0.0411%8 Mar
inferno13–3-0.0410%8 Mar
nuke16–14-0.0221%23 Feb
dust213–80.0215%23 Feb
ancient13–110.0215%22 Feb
inferno15–150.0715%22 Feb
dust24–13-0.0410%22 Feb
dust29–13-0.048%22 Feb
dust211–13-0.0419%22 Feb
nuke13–8-0.043%22 Feb
ancient13–110.0112%22 Feb
inferno1–13-0.0822%21 Feb
inferno6–13-0.058%15 Feb
inferno11–13-0.0717%12 Feb
overpass2–13-0.0615%7 Feb
nuke13–7-0.0113%7 Feb
inferno13–7-0.0113%7 Feb
dust213–9-0.0224%7 Feb
mirage13–60.0216%17 Jan
train11–130.0418%17 Jan
inferno13–10-0.0321%17 Jan
mirage8–13-0.0119%16 Jan
ancient1–13-0.1010%16 Jan
dust213–30.1123%16 Jan
mirage3–70.0813%16 Jan
dust213–16-0.0619%16 Jan
dust212–16-0.0718%15 Jan
inferno13–9-0.0712%15 Jan
overpass9–13-0.0214%15 Jan
mirage13–8-0.065%15 Jan
inferno15–15-0.0210%14 Jan
mirage13–70.0414%14 Jan
mirage13–70.1016%14 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 →