Kong harald

Kong harald — CS2 Stats

76561199702808473[U:1:1742542745]Steam profile ↗✓ No bans

148Tracked matches52%Win rate2024Tracked since
576Hours in CS21Hrs last 2 wks
CSDB Rating5.3 DevelopingPositional Player
Premier CS Rating16,231Purple band · top ~23.5% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 27 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

+551Premier CS Rating · 15,680 → 16,231

Rating over time

Premier CS Rating: 16,231 +4,976 25 Apr – 28 Sept · 26 days played
11,25518,207peak 18,20725 Apr28 Sept
18,581Peak Premier in tracked matches
33Days played since 2026-04-25

Premier CS Rating

  • 1,976 below peak (18,207)
  • +1,919 over 30 days · improving
  • Next: Pink band at 20,000 — 3,769 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.

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 rate43.7%44.3%46.9%3.3% short
Shot accuracy0.0%11.9%13.0%13.0% short
Kill/death ratio0.971.031.080.11 short
Match win rate53.5%45.2%46.7%above

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

Widest gap: Shot accuracy. 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.

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CSDB.GGKong haraldPREMIER16,231 · Purple bandcsdb.gg/stats

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Performance scores

Aim63
Positioning52
Utility31

0–100 skill scores via Leetify.

Recent form

STEADY53–43–4Last 10053%Win rateLWLWLLLWWL

Last 10 vs previous 10: −30pp win rate · +0.00 avg rating · −1.0pp headshot accuracy · −38ms reaction

Win rate down 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 603ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 15%
  • Avg reaction 573ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 15%
  • Avg reaction 592ms

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 (+1.3 against its own average).

Aim6.3
Utility3.1
Positioning5.2
Opening Duels2.0
Clutch5.2

Limited utility dependence

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 90% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; 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

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 613ms 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

Aim6.3
Positioning5.2
Utility3.1
Mechanics6.9
Opening Duels3.0
Win Impact5.6

Composite 5.3/10 (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-0.01−0.02
first ⅓ avg 0.00 → last ⅓ avg -0.01
Reaction time616ms+9ms
first ⅓ avg 607ms → last ⅓ avg 616ms
Headshot accuracy15.7%+1.1%
first ⅓ avg 14.5% → last ⅓ avg 15.7%

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

0.13Best match rating · 13–4 · nuke, 26 Jul →
50%Best headshot accuracy · 13–1 · cache, 29 Apr →
406msFastest reaction time · 13–11 · anubis, 12 Aug →
13–0Biggest win · inferno, 11 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
8–7In matches decided by ≤2 rounds
8Overtime games

Map breakdown

mirageBest map · 69% over 13anubisWeakest map · 45% over 11
MapGradePlayedRecordWin rateAvg rating
infernoB2211–1150%-0.01
dust2B199–1047%-0.02
cacheB178–947%-0.00
mirageS139–469%0.00
anubisB115–645%-0.03
nukeB84–450%0.02
ancient—43–175%0.02
vertigo—22–0100%0.09
train—10–10%-0.03
boulder—11–0100%-0.08
fachwerk—11–0100%-0.06
overpass—10–10%0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (45% over 11). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

6,504Lifetime kills
0.97K/D
419Matches
53.5%Match win rate · Top 10% of Purple band
43.7%Headshot %
0.0%Shot accuracy
896MVPs
160Hours (in match)
357Bombs planted
75Bombs defused

Most-used weapons

Lifetime map wins

1,035dust2
601inferno
344nuke
82vertigo
12train
3office
2italy
1ar_baggage

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

Faceit stats

Combat

42Matches
50%Win rate
1.05Avg K/D
77.5ADR
43%Headshot %

Clutches & streaks

46%1v1 clutch win
44%1v2 clutch win
4Longest win streak

Recent Faceit resultsLLWLW

MapMatchesWin rateAvg K/DAvg kills
Mirage1443%0.8012.0
Dust21040%1.1112.2
Ancient580%1.1418.2
Inferno425%0.8312.8
Cache367%1.1315.3
Nuke3100%1.5922.0
Anubis250%1.8622.0
Vertigo10%0.7814.0

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.

16.5%Headshot accuracy
30.7%Accuracy (enemy spotted)
32.0%Spray accuracy
81.1%Counter-strafing
7.6°Preaim
613msReaction time
41.9%T opening success
41.9%CT opening success
0.50Enemies flashed / flash
1.4%Flash assists
5.72HE damage / grenade
4.52Flashes / 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. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4995 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Anubis

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

45% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke10–13-0.049%28 Sept →
nuke13–20.0820%28 Sept →
dust211–130.0021%28 Sept →
mirage13–10-0.0413%28 Sept →
anubis3–13-0.0815%27 Sept →
cache9–130.0212%27 Sept →
inferno5–13-0.0213%27 Sept →
vertigo13–90.0615%27 Sept →
vertigo13–80.1213%27 Sept →
inferno5–13-0.0914%23 Sept →
dust213–100.0321%22 Sept →
dust29–13-0.0521%22 Sept →
ancient13–2-0.0115%22 Sept →
inferno13–60.016%22 Sept →
dust213–5-0.0418%22 Sept →
mirage16–12-0.0417%22 Sept →
dust216–14-0.0124%21 Sept →
anubis10–130.0512%21 Sept →
mirage4–120.0112%21 Sept →
inferno13–90.0410%21 Sept →
inferno13–9-0.0310%21 Sept →
inferno13–0-0.0345%11 Sept →
anubis4–13-0.1216%28 Aug →
cache9–13-0.0529%28 Aug →
dust213–3-0.0314%27 Aug →
inferno3–6-0.0019%27 Aug →
dust215–15-0.0221%27 Aug →
inferno5–13-0.0219%20 Aug →
dust214–16-0.019%16 Aug →
dust213–40.0222%14 Aug →
mirage6–13-0.064%14 Aug →
train12–12-0.036%13 Aug →
mirage3–13-0.040%13 Aug →
nuke8–13-0.042%13 Aug →
dust27–13-0.010%13 Aug →
anubis9–13-0.0912%13 Aug →
dust29–130.0219%13 Aug →
ancient13–100.0711%13 Aug →
cache16–14-0.0216%12 Aug →
anubis13–11-0.0116%12 Aug →
dust216–130.027%12 Aug →
nuke13–80.0610%12 Aug →
inferno9–13-0.058%12 Aug →
nuke13–70.0211%12 Aug →
inferno13–7-0.0522%11 Aug →
cache13–5-0.0314%11 Aug →
cache13–50.0233%8 Aug →
cache13–20.0512%8 Aug →
cache13–110.099%7 Aug →
dust210–13-0.0914%7 Aug →
dust29–13-0.037%7 Aug →
inferno13–50.0819%6 Aug →
inferno11–13-0.0119%6 Aug →
dust213–50.0212%3 Aug →
nuke8–13-0.0415%2 Aug →
dust213–11-0.0510%2 Aug →
anubis4–13-0.049%2 Aug →
cache4–13-0.0319%30 Jul →
boulder13–11-0.082%29 Jul →
cache2–13-0.043%29 Jul →
anubis13–40.0510%29 Jul →
dust27–13-0.0527%29 Jul →
anubis11–10.040%29 Jul →
inferno13–90.0414%29 Jul →
dust213–40.0329%28 Jul →
fachwerk13–10-0.0617%27 Jul →
ancient11–13-0.0210%26 Jul →
nuke13–40.1316%26 Jul →
mirage9–130.0418%26 Jul →
inferno11–13-0.0020%26 Jul →
dust29–13-0.0614%26 Jul →
inferno13–60.0114%26 Jul →
ancient13–70.049%26 Jul →
nuke11–13-0.0210%26 Jul →
anubis13–70.0118%26 Jul →
mirage13–70.0116%26 Jul →
mirage13–110.028%26 Jul →
anubis13–9-0.066%26 Jul →
inferno15–15-0.058%25 Jul →
inferno13–50.039%25 Jul →
inferno14–16-0.0017%22 Jul →
inferno13–7-0.0316%21 Jul →
inferno8–13-0.0213%21 Jul →
mirage13–4-0.0510%21 Jul →
inferno4–0-0.010%20 Jul →
cache13–90.0311%20 Jul →
overpass12–120.0412%20 Jul →
mirage13–60.1326%20 Jul →
inferno8–13-0.0119%19 Jul →
mirage13–20.118%19 Jul →
anubis4–13-0.0514%19 Jul →
cache10–130.0215%11 May →
cache13–9-0.048%30 Apr →
mirage13–11-0.0219%29 Apr →
cache9–130.0214%29 Apr →
cache8–13-0.0121%29 Apr →
cache9–13-0.0517%29 Apr →
cache8–13-0.084%29 Apr →
cache13–10.0550%29 Apr →
mirage13–7-0.0319%25 Apr →

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 →

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