jamppa

jamppa — CS2 Stats

76561198435703204[U:1:475437476]Steam profile ↗✓ No bans

1,387Tracked matches48%Win rate2021Tracked since
1,955Hours in CS3Hrs last 2 wks
CSDB Rating5.4 DevelopingSupport
Premier CS Rating16,582Purple band · top ~22.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 4 Oct 2026 (7 days ago). Ranks are recorded once per day this page is viewed.

−229Premier CS Rating · 16,811 → 16,582

Rating over time

Premier CS Rating: 16,582 +1,866 13 Jun – 11 Oct · 23 days played
13,36119,599peak 19,59913 Jun11 Oct
19,812Peak Premier in tracked matches
47Days played since 2026-06-13

Premier CS Rating

  • 3,017 below peak (19,599)
  • -2,163 over 90 days
  • Next: Pink band at 20,000 — 3,418 to go
  • Reached: Purple band · Blue band · Light Blue band

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

Compare periods

Last 30 days vs previous 30

MetricLast 30Previous 30Change
Matches9——
Win rate33%——
K/D0.84——
Headshot %33%——

Measured 8 Sep 2026 → 11 Oct 2026; no observation near 60 days ago, so there is no previous window yet.

Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.

How this compares with the same rank

Median values for Purple band among CSDB-tracked players (n=37,767), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerPurple band medianPink band medianvs Pink band
Headshot rate24.8%44.3%46.9%22.1% short
Shot accuracy9.7%11.9%13.0%3.3% short
Kill/death ratio0.561.031.080.52 short
Match win rate46.0%45.2%46.7%meets

This profile matches the typical Pink band player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGjamppaPREMIER16,582 · Purple bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim75
Positioning48
Utility50

0–100 skill scores via Leetify.

Recent form

COLD45–49–6Last 10045%Win rateLWLLLWLWLL

Last 10 vs previous 10: −10pp win rate · −0.04 avg rating · +0.2pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 478ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 18%
  • Avg reaction 525ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 530ms

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 (+1.5 against its own average).

Aim7.5
Utility5.0
Positioning4.8
Opening Duels3.0
Clutch1.2

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

NiKo

Plays most like NiKo 95% playstyle similarity

Most alike: utility contribution, aim profile.

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

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

CSDB Rating breakdown

Aim7.5
Positioning4.8
Utility5.0
Mechanics5.5
Opening Duels1.8
Win Impact4.4

Composite 5.4/10 (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 rating0.01+0.01
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time534ms−2ms
first ⅓ avg 536ms → last ⅓ avg 534ms
Headshot accuracy15.0%+0.8%
first ⅓ avg 14.3% → 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.

Personal bests

0.16Best match rating · 13–3 · nuke, 31 Jul →
37%Best headshot accuracy · 5–13 · nuke, 8 Aug →
391msFastest reaction time · 10–13 · nuke, 27 Sept →
13–2Biggest win · nuke, 25 Aug →

Across the last 100 tracked matches.

Highlights

6Longest win streak
10–3In matches decided by ≤2 rounds
8Overtime games

Map breakdown

mirageBest map · 67% over 9infernoWeakest map · 33% over 12
MapGradePlayedRecordWin rateAvg rating
nukeB3216–1650%0.00
cacheC198–1142%-0.01
infernoD124–833%0.01
dust2A106–460%0.00
ancientD93–633%0.00
mirageS96–367%-0.03
anubis—30–30%-0.04
train—31–233%-0.00
vertigo—20–20%-0.01
shelter—11–0100%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

25,901Lifetime kills
0.56K/D
2,434Matches
46.0%Match win rate · Top 50% of Purple band
24.8%Headshot %
9.7%Shot accuracy
4,713MVPs
979Hours (in match)
1,066Bombs planted
277Bombs defused

Most-used weapons

Lifetime map wins

2,748vertigo
2,361nuke
1,182inferno
1,146dust2
479cbble
471train
116office
100italy

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

73Matches
47%Win rate
0.95Avg K/D
82.1ADR
34%Headshot %

Clutches & streaks

26%1v1 clutch win
17%1v2 clutch win
5Longest win streak

Recent Faceit resultsLWWLW

MapMatchesWin rateAvg K/DAvg kills
Mirage1354%0.9814.8
Nuke850%0.9714.1
Inferno667%1.2519.0
Ancient667%1.1015.2
Dust2520%0.8113.0
Vertigo40%0.9916.5
Cache20%0.9215.5

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.

15.0%Headshot accuracy
35.2%Accuracy (enemy spotted)
37.7%Spray accuracy
74.6%Counter-strafing
7.7°Preaim
529msReaction time
31.1%T opening success
43.4%CT opening success
0.56Enemies flashed / flash
5.1%Flash assists
8.24HE damage / grenade
9.30Flashes / 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. 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 14.9911% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 31.1117% — below the 40% mark we flag

Spend your practice time on Inferno

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

33% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust23–13-0.0713%11 Oct →
ancient13–100.0010%4 Oct →
nuke1–13-0.019%3 Oct →
mirage3–13-0.0214%30 Sept →
nuke10–13-0.0626%27 Sept →
dust213–11-0.0012%27 Sept →
inferno9–130.0010%26 Sept →
nuke13–2-0.0321%25 Aug →
nuke5–13-0.0329%25 Aug →
nuke5–13-0.0837%8 Aug →
nuke8–13-0.0518%7 Aug →
nuke5–130.0216%1 Aug →
nuke13–30.1617%31 Jul →
cache13–9-0.0314%30 Jul →
nuke11–13-0.0026%30 Jul →
nuke13–80.0721%29 Jul →
nuke12–120.0217%28 Jul →
nuke13–40.0520%28 Jul →
vertigo3–9-0.1222%28 Jul →
ancient10–13-0.009%26 Jul →
inferno8–130.0812%26 Jul →
cache13–30.079%26 Jul →
cache13–60.059%24 Jul →
nuke13–5-0.0510%24 Jul →
nuke13–6-0.0210%23 Jul →
inferno3–130.019%23 Jul →
nuke13–110.0316%22 Jul →
cache12–120.0112%22 Jul →
mirage15–15-0.009%19 Jul →
vertigo6–130.0911%18 Jul →
cache13–80.026%18 Jul →
shelter13–50.046%18 Jul →
nuke13–100.0816%18 Jul →
cache13–8-0.0316%18 Jul →
mirage16–14-0.0411%17 Jul →
ancient13–110.029%16 Jul →
anubis8–13-0.0411%16 Jul →
ancient10–13-0.032%16 Jul →
mirage13–10-0.026%16 Jul →
ancient3–7-0.1014%16 Jul →
nuke7–13-0.0117%15 Jul →
cache2–13-0.079%15 Jul →
nuke13–8-0.0117%15 Jul →
inferno11–130.019%15 Jul →
mirage13–9-0.0616%14 Jul →
cache7–13-0.0715%14 Jul →
inferno10–13-0.0221%13 Jul →
cache8–130.0524%12 Jul →
nuke15–15-0.066%12 Jul →
mirage13–10-0.0410%12 Jul →
inferno16–130.0321%10 Jul →
nuke4–00.000%10 Jul →
inferno13–11-0.0110%9 Jul →
nuke13–60.0730%9 Jul →
cache13–50.0110%8 Jul →
cache10–130.0210%7 Jul →
nuke11–130.0015%6 Jul →
cache4–13-0.108%6 Jul →
dust216–140.0211%5 Jul →
dust213–50.0711%5 Jul →
anubis6–13-0.009%5 Jul →
dust27–130.0516%3 Jul →
anubis9–13-0.0826%3 Jul →
nuke7–13-0.0316%2 Jul →
nuke13–90.0518%28 Jun →
cache6–13-0.0422%28 Jun →
inferno3–13-0.0221%28 Jun →
inferno10–13-0.0314%28 Jun →
mirage16–14-0.0411%28 Jun →
mirage13–11-0.0325%27 Jun →
nuke12–12-0.0116%26 Jun →
train10–13-0.028%26 Jun →
mirage3–13-0.024%26 Jun →
cache7–13-0.0519%26 Jun →
dust213–20.0416%26 Jun →
dust24–13-0.0822%26 Jun →
cache6–13-0.0417%25 Jun →
nuke10–13-0.0215%25 Jun →
nuke13–9-0.0113%25 Jun →
nuke13–60.025%25 Jun →
cache10–13-0.0315%24 Jun →
dust213–4-0.0010%24 Jun →
inferno16–140.0711%24 Jun →
nuke7–13-0.0118%23 Jun →
ancient8–130.0512%21 Jun →
inferno0–13-0.057%20 Jun →
cache9–13-0.0214%19 Jun →
nuke7–2-0.0517%18 Jun →
ancient13–70.0510%18 Jun →
ancient10–130.0020%16 Jun →
nuke13–70.0314%16 Jun →
train13–70.0216%15 Jun →
cache13–5-0.005%15 Jun →
nuke5–13-0.0113%13 Jun →
inferno13–80.0316%13 Jun →
ancient13–160.0423%13 Jun →
dust213–11-0.0116%13 Jun →
dust29–13-0.0113%13 Jun →
cache13–90.0021%13 Jun →
train12–12-0.0115%13 Jun →

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 →

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