nopampa

nopampa — CS2 Stats

76561198077149862[U:1:116884134]Steam profile ↗✓ No bans

2,133Tracked matches55%Win rate2020Tracked since
CSDB Rating5.2 DevelopingSupport
WingmanLegendary Eagle Master
Ladder ranks via Leetify

Performance scores

Aim47
Positioning55
Utility73

0–100 skill scores via Leetify.

Recent form

STEADY49–50–1Last 10049%Win rateLLWLWLLWWL

Last 10 vs previous 10: −10pp win rate · −0.03 avg rating · +2.5pp headshot accuracy · +10ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 559ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 18%
  • Avg reaction 560ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 555ms

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 (+2.6 against its own average).

Aim4.7
Utility7.3
Positioning5.5
Opening Duels1.9
Clutch4.2

Strong CT-side openerEffective flashes

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 64% 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

Strengths

Flashes. 0.79 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 50% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 562ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.7
Positioning5.5
Utility7.3
Mechanics4.3
Opening Duels2.5
Win Impact6.7

Composite 5.2/10 (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-0.01−0.00
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time572ms+33ms
first ⅓ avg 539ms → last ⅓ avg 572ms
Headshot accuracy15.1%−0.7%
first ⅓ avg 15.9% → last ⅓ avg 15.1%

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

0.14Best match rating · 4–1 · dust2, 19 Apr →
41%Best headshot accuracy · 13–6 · dust2, 26 Oct →
391msFastest reaction time · 6–13 · ancient, 4 Feb →
13–2Biggest win · inferno, 8 Apr →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L2Current streak
11–7In matches decided by ≤2 rounds
14Overtime games

Map breakdown

dust2Best map · 68% over 28ancientWeakest map · 19% over 16
MapGradePlayedRecordWin rateAvg rating
nukeA2817–1161%-0.02
dust2S2819–968%0.01
ancientD163–1319%-0.00
anubisC94–544%-0.01
trainD93–633%-0.01
infernoC73–443%0.01
cache—10–10%-0.06
overpass—10–10%-0.04
mirage—10–10%-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (19% over 16). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,872Matches
51%Win rate
1.03Avg K/D
81.8ADR
39%Headshot %

Clutches & streaks

41%1v1 clutch win
18%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLWLL

MapMatchesWin rateAvg K/DAvg kills
Dust229054%1.0916.2
Nuke19162%0.9815.7
Ancient15346%1.0216.0
Anubis8643%0.9315.4
Inferno7832%0.8914.3
Train5650%1.0515.4
Mirage1217%0.7511.5
Overpass757%0.8612.0

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.

14.8%Headshot accuracy
32.6%Accuracy (enemy spotted)
34.3%Spray accuracy
69.3%Counter-strafing
12.0°Preaim
562msReaction time
25.8%T opening success
49.7%CT opening success
0.79Enemies flashed / flash
7.7%Flash assists
17.03HE damage / grenade
12.84Flashes / 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 12.0018° — 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 14.8147% — 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.

19% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke2–13-0.1218%1 Nov →
inferno9–13-0.0311%3 Oct →
dust216–14-0.0017%21 Aug →
dust28–13-0.0313%6 Jun →
dust213–50.0122%6 Jun →
cache9–13-0.0629%6 Jun →
dust26–13-0.0120%6 Jun →
dust213–80.0113%19 May →
dust213–90.0012%9 May →
anubis10–13-0.0122%8 May →
nuke8–13-0.0729%5 May →
anubis5–13-0.0115%4 May →
nuke13–160.0419%24 Apr →
dust24–10.1419%19 Apr →
inferno13–110.024%3 Apr →
dust213–7-0.0321%9 Mar →
ancient4–13-0.016%8 Mar →
anubis22–250.0110%4 Mar →
nuke16–13-0.0211%2 Mar →
nuke13–11-0.0419%9 Feb →
dust212–120.0312%4 Feb →
inferno19–160.0717%1 Feb →
anubis13–3-0.0414%18 Jan →
dust213–60.0316%18 Jan →
nuke13–11-0.047%10 Jan →
anubis13–8-0.0217%10 Jan →
inferno6–13-0.037%6 Jan →
nuke8–13-0.038%6 Jan →
nuke16–13-0.039%5 Jan →
dust213–10-0.0219%4 Jan →
nuke13–9-0.0014%29 Dec →
nuke11–130.0421%14 Dec →
train8–130.029%14 Dec →
ancient13–160.0316%13 Dec →
train1–13-0.0115%13 Dec →
overpass3–4-0.0423%1 Dec →
nuke13–10-0.0215%1 Dec →
ancient8–130.008%25 Nov →
dust213–70.0524%16 Nov →
dust213–60.0641%26 Oct →
nuke13–80.0215%26 Oct →
dust216–140.0411%26 Oct →
nuke13–110.0118%20 Oct →
dust213–7-0.0416%11 Oct →
inferno5–12-0.0314%5 Oct →
nuke8–13-0.0611%24 Sept →
nuke13–60.056%12 Sept →
ancient4–13-0.0718%30 Aug →
train8–13-0.069%20 Aug →
ancient9–130.0222%12 Aug →
dust216–140.0126%5 Jul →
inferno7–130.0223%8 May →
train10–130.0315%7 May →
dust211–130.0426%5 May →
nuke9–13-0.0316%17 Apr →
ancient7–13-0.0511%9 Apr →
anubis13–90.0110%8 Apr →
inferno13–20.058%8 Apr →
ancient2–130.0115%8 Apr →
nuke7–9-0.0016%8 Apr →
anubis8–13-0.0215%30 Mar →
dust213–100.0413%22 Mar →
ancient7–13-0.0223%16 Mar →
dust213–90.0216%16 Mar →
ancient14–16-0.0115%9 Mar →
nuke4–13-0.0511%9 Mar →
nuke13–8-0.0215%8 Mar →
ancient13–80.0019%4 Mar →
nuke16–140.0222%25 Feb →
ancient9–13-0.0916%18 Feb →
nuke6–13-0.0621%5 Feb →
anubis13–6-0.0014%5 Feb →
ancient6–130.0114%4 Feb →
dust213–15-0.049%1 Feb →
train13–11-0.039%1 Feb →
train10–13-0.0819%28 Jan →
train13–100.0517%25 Jan →
ancient13–70.0622%22 Jan →
dust213–110.0018%17 Jan →
dust29–13-0.0523%27 Dec →
anubis9–13-0.008%26 Dec →
dust27–130.0213%18 Dec →
nuke8–13-0.0813%13 Dec →
nuke13–11-0.0119%12 Dec →
nuke13–100.0110%10 Dec →
ancient13–50.037%6 Dec →
ancient7–120.0819%25 Nov →
train17–190.0421%19 Nov →
dust210–13-0.0521%18 Nov →
nuke13–8-0.047%15 Nov →
train16–13-0.0112%14 Nov →
nuke13–80.0411%14 Nov →
nuke13–3-0.0319%8 Nov →
nuke13–6-0.065%21 Oct →
dust213–70.0514%18 Oct →
dust29–13-0.0736%15 Oct →
mirage7–13-0.0211%21 Sept →
dust213–90.1120%20 Sept →
ancient4–130.0117%15 Sept →
dust213–40.0820%23 Aug →

Match data via Leetify.

Recent teammates

Milestones

2K ELO1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.