unclepoon — CS2 Stats

76561198048232756[U:1:87967028]

630Tracked matches52%Win rate2020Tracked since
CSDB Rating4.6 Developing
WingmanGold Nova Master
Ladder ranks via Leetify

Performance scores

Aim45
Positioning45
Utility54

0–100 skill scores via Leetify.

Recent form

STEADY48466Last 10048%Win rateLWWLLWWLLW

Last 10 vs previous 10: +0pp win rate · +0.00 avg rating

Player DNA

Aim4.5
Aggression4.8
Utility5.4
Positioning4.5
Opening Duels1.4

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 81% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower positioning profile; 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 47% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 606ms 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

Aim4.5
Positioning4.5
Utility5.4
Mechanics5.3
Opening Duels2.2
Win Impact5.6

Composite 4.6/10 (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-0.03−0.00
first ⅓ avg -0.03 → last ⅓ avg -0.03
Reaction time625ms−36ms
first ⅓ avg 661ms → last ⅓ avg 625ms
Headshot accuracy11.9%+2.2%
first ⅓ avg 9.8% → last ⅓ avg 11.9%

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

0.12Best rating — inferno 13–5
131Biggest win — dust2
6Longest win streak
115In matches decided by ≤2 rounds
10Overtime games

Map breakdown

infernoBest map · 71% over 28ancientWeakest map · 32% over 31
MapGradePlayedRecordWin rateAvg rating
ancientD31102132%-0.04
infernoS2820871%-0.01
overpassC1871139%-0.04
trainB84450%-0.05
anubisA53260%-0.04
nuke42250%-0.04
cache3030%-0.06
vertigo21150%-0.02
dust2110100%-0.04

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (32% over 31). Start with the 6 essential Ancient 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.

12.1%Headshot accuracy
32.0%Accuracy (enemy spotted)
44.0%Spray accuracy
73.9%Counter-strafing
13.4°Preaim
606msReaction time
24.2%T opening success
47.3%CT opening success
0.62Enemies flashed / flash
3.5%Flash assists
9.12HE damage / grenade
6.53Flashes / 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 13.3997° — 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 12.0709% — below the 15% mark we flag

    Aim Training
Spend your practice time on Ancient

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

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
cache8–13-0.0625%16 Aug
ancient13–5-0.0115%13 Aug
inferno13–90.0227%13 Aug
anubis13–16-0.0417%13 Aug
cache11–13-0.0613%1 Aug
inferno13–100.0013%14 Jul
ancient13–9-0.0117%12 Jul
ancient10–130.0111%12 Jul
cache0–11-0.0620%12 Jul
anubis13–9-0.063%12 Jul
inferno16–14-0.055%1 Jul
anubis13–5-0.0211%1 Jul
overpass13–2-0.036%1 Jul
inferno13–70.1115%30 Jun
ancient7–13-0.0312%30 Jun
ancient9–13-0.035%19 Apr
overpass13–7-0.0213%19 Apr
ancient4–13-0.0811%19 Apr
overpass10–13-0.077%19 Apr
anubis3–13-0.0829%12 Apr
inferno13–11-0.0614%12 Apr
inferno13–5-0.019%12 Apr
inferno7–13-0.0519%12 Apr
inferno13–10-0.037%12 Apr
overpass7–13-0.062%2 Feb
ancient13–10-0.0311%2 Feb
ancient11–13-0.0517%29 Jan
anubis13–10-0.014%29 Jan
inferno12–12-0.015%5 Jan
ancient9–13-0.038%5 Jan
ancient5–13-0.110%5 Jan
overpass3–13-0.0614%13 Dec
ancient10–13-0.0610%13 Dec
inferno16–12-0.0114%30 Nov
ancient4–13-0.030%30 Nov
overpass13–80.000%30 Nov
vertigo4–90.0116%27 Oct
inferno8–8-0.0517%27 Oct
train1–80.0150%13 Oct
ancient13–3-0.0513%13 Oct
ancient6–13-0.0530%13 Oct
inferno13–6-0.058%19 Sept
inferno13–10-0.0211%19 Sept
train13–11-0.0524%19 Sept
train13–6-0.0213%18 Sept
train5–13-0.0915%16 Sept
ancient11–13-0.0418%16 Sept
overpass13–11-0.0120%16 Sept
inferno8–80.0832%15 Sept
dust213–1-0.0410%12 Sept
ancient10–13-0.0417%12 Sept
ancient4–13-0.0667%7 Sept
ancient5–13-0.074%7 Sept
overpass7–13-0.0013%7 Sept
ancient13–11-0.066%6 Sept
ancient13–11-0.0417%6 Sept
ancient5–13-0.060%3 Sept
ancient5–13-0.034%3 Sept
inferno7–9-0.0511%31 Aug
inferno9–30.1013%28 Aug
inferno4–9-0.0816%28 Aug
ancient15–150.017%28 Aug
inferno13–10-0.036%28 Aug
nuke14–16-0.0217%25 Aug
overpass13–10-0.0629%24 Aug
ancient1–13-0.0922%24 Aug
inferno13–11-0.024%20 Aug
ancient13–70.018%20 Aug
ancient13–160.0116%20 Aug
inferno13–8-0.0314%20 Aug
inferno9–4-0.020%19 Aug
inferno13–9-0.055%18 Aug
overpass13–3-0.042%18 Aug
inferno9–70.0324%13 Aug
train13–6-0.075%13 Aug
overpass7–13-0.093%13 Aug
inferno13–11-0.030%11 Aug
ancient15–15-0.052%11 Aug
ancient13–160.0014%9 Aug
ancient13–50.0131%9 Aug
train15–15-0.0411%6 Aug
train13–3-0.0814%6 Aug
overpass5–13-0.070%6 Aug
train13–16-0.059%4 Aug
overpass5–13-0.086%4 Aug
overpass13–40.0026%4 Aug
nuke5–13-0.0624%4 Aug
inferno13–11-0.087%3 Aug
overpass8–13-0.046%3 Aug
nuke13–9-0.0113%3 Aug
ancient11–50.0513%3 Aug
ancient13–9-0.093%2 Aug
overpass6–13-0.020%1 Aug
overpass2–13-0.029%1 Aug
vertigo13–6-0.044%27 Jul
inferno4–13-0.0212%27 Jul
overpass6–13-0.0816%21 Jul
inferno8–13-0.059%21 Jul
nuke13–11-0.055%21 Jul
inferno13–50.1213%7 Jul

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 →