PandaMonium — CS2 Stats

76561197960421801[U:1:156073]

116Tracked matches36%Win rate2023Tracked since
CSDB Rating5.7 SolidPositional Player
Ladder ranks via Leetify

Rating over time

6,664Peak Premier in tracked matches
37Days played since 2023-12-18

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim72
Positioning62
Utility42

0–100 skill scores via Leetify.

Recent form

STEADY38–55–7Last 10038%Win rateWLLWLWWLWW

Last 10 vs previous 10: +20pp win rate · +0.02 avg rating · +2.5pp headshot accuracy · −17ms 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 0.01
  • Avg headshot accuracy 24%
  • Avg reaction 494ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 18%
  • Avg reaction 554ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 17%
  • Avg reaction 562ms

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 (+1.7 against its own average).

Aim7.2
Utility4.2
Positioning6.2
Opening Duels3.1

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 93% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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

T openings. 66% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 66% on T to 46% on CT — first contacts on the defending side are being lost.

Reaction time. 579ms 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

Aim7.2
Positioning6.2
Utility4.2
Mechanics6.7
Opening Duels6.5
Win Impact0.2

Composite 5.7/10 (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 -0.02 → last ⅓ avg -0.01
Reaction time579ms−96ms
first ⅓ avg 675ms → last ⅓ avg 579ms
Headshot accuracy16.0%−2.8%
first ⅓ avg 18.7% → last ⅓ avg 16.0%

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.

Personal bests

0.14Best match rating · 13–5 · mirage, 20 Jul →
100%Best headshot accuracy · 0–5 · mirage, 28 Jul →
125msFastest reaction time · 0–2 · mirage, 5 Oct →
13–1Biggest win · inferno, 7 Sept →

Across the last 100 tracked matches.

Highlights

3Longest win streak
5–11In matches decided by ≤2 rounds
7Overtime games

Map breakdown

nukeBest map · 54% over 13dust2Weakest map · 32% over 25
MapGradePlayedRecordWin rateAvg rating
mirageC3313–2039%-0.01
dust2D258–1732%-0.01
nukeB137–654%-0.00
infernoC114–736%0.01
overpassB63–350%-0.02
ancient—30–30%-0.02
anubis—31–233%-0.02
vertigo—30–30%-0.01
cache—11–0100%-0.05
italy—11–0100%-0.06
train—10–10%0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (32% over 25). 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.

15.0%Headshot accuracy
36.0%Accuracy (enemy spotted)
32.0%Spray accuracy
80.2%Counter-strafing
7.7°Preaim
579msReaction time
65.7%T opening success
46.0%CT opening success
0.69Enemies flashed / flash
1.8%Flash assists
9.31HE damage / grenade
5.76Flashes / match

Recommended for you

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.

32% win rate across 25 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–30.0226%5 Oct →
nuke11–130.0116%5 Oct →
dust23–13-0.0023%5 Oct →
mirage13–70.0420%5 Oct →
mirage0–2-0.0233%5 Oct →
dust213–80.0216%1 Oct →
nuke16–140.0211%1 Oct →
nuke8–13-0.0413%1 Oct →
dust213–80.0013%1 Oct →
nuke13–30.0211%29 Sept →
dust213–90.1313%29 Sept →
dust25–130.0015%28 Sept →
ancient2–13-0.0111%27 Sept →
mirage6–13-0.0723%26 Sept →
dust27–13-0.0518%26 Sept →
dust26–130.008%26 Sept →
dust213–9-0.0212%26 Sept →
dust26–13-0.0623%26 Sept →
mirage13–11-0.047%26 Sept →
dust213–80.0327%25 Sept →
inferno3–13-0.0010%22 Sept →
mirage5–13-0.0613%21 Sept →
inferno10–130.0421%21 Sept →
nuke11–13-0.0216%20 Sept →
nuke8–13-0.059%18 Sept →
dust210–13-0.0116%18 Sept →
dust212–12-0.0411%18 Sept →
dust210–13-0.075%18 Sept →
mirage4–12-0.0511%14 Sept →
mirage12–12-0.0220%14 Sept →
inferno13–10-0.0126%14 Sept →
mirage9–13-0.115%14 Sept →
nuke7–13-0.0024%10 Sept →
mirage3–13-0.0425%10 Sept →
nuke9–13-0.0610%7 Sept →
inferno8–130.0216%7 Sept →
overpass4–13-0.0321%7 Sept →
inferno13–10.0214%7 Sept →
inferno9–130.0228%7 Sept →
dust213–40.1122%7 Sept →
nuke13–30.0629%4 Sept →
mirage13–110.0018%4 Sept →
dust210–130.0417%4 Sept →
dust210–130.0513%4 Sept →
overpass13–90.0132%4 Sept →
mirage11–13-0.0617%3 Sept →
mirage13–9-0.0014%3 Sept →
dust24–13-0.0618%3 Sept →
inferno13–80.0120%31 Aug →
mirage11–130.0020%31 Aug →
inferno14–160.0118%31 Aug →
nuke13–100.0218%31 Aug →
anubis15–15-0.0223%6 Aug →
cache13–6-0.059%6 Aug →
inferno5–13-0.0126%20 Feb →
dust213–8-0.0418%19 Feb →
mirage14–160.0921%19 Feb →
mirage6–130.038%19 Feb →
nuke13–80.0111%17 Feb →
dust212–12-0.029%16 Feb →
dust212–12-0.0129%16 Feb →
mirage13–10-0.0410%16 Feb →
anubis4–13-0.0022%16 Feb →
overpass6–130.0622%16 Feb →
overpass13–5-0.073%14 Feb →
inferno13–11-0.029%14 Feb →
mirage6–13-0.0215%11 Feb →
dust27–13-0.0010%11 Feb →
italy13–7-0.0612%11 Feb →
mirage7–13-0.0215%23 Jan →
inferno12–160.0121%23 Jan →
mirage3–13-0.0211%23 Jan →
dust210–13-0.068%22 Jan →
dust23–13-0.063%17 Jan →
train6–130.0422%17 Jan →
overpass13–80.025%17 Jan →
mirage13–7-0.0113%17 Jan →
mirage0–5-0.12100%28 Jul →
mirage12–120.0218%24 Jul →
mirage13–7-0.0316%23 Jul →
dust214–16-0.0619%23 Jul →
ancient7–13-0.0214%23 Jul →
vertigo6–13-0.0727%23 Jul →
mirage12–12-0.0111%21 Jul →
mirage13–4-0.0015%21 Jul →
mirage13–90.0328%21 Jul →
mirage13–50.1414%20 Jul →
mirage11–13-0.0427%27 May →
mirage6–13-0.0426%27 May →
mirage12–4-0.0116%19 Feb →
vertigo9–130.0124%18 Feb →
mirage13–50.0414%18 Feb →
vertigo14–160.0316%18 Feb →
mirage13–100.0520%18 Feb →
mirage6–13-0.1116%18 Feb →
nuke13–110.0321%18 Feb →
overpass4–13-0.1114%22 Dec →
anubis13–9-0.0514%22 Dec →
nuke13–10-0.0614%18 Dec →
ancient11–13-0.0516%18 Dec →

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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