Fogs

Fogs — CS2 Stats

DK76561197974470288[U:1:14204560]Steam profile ↗✓ No bans

565Tracked matches47%Win rate2020Tracked since
CSDB Rating5.4 DevelopingSupport
Premier CS Rating9,170Light Blue band · top ~58.9% of ranked players (population est.)
FaceitLevel 3Top 90.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 20 Oct 2026 (6 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 9,170 -2,642 13 Feb – 20 Oct · 27 days played
7,19312,555peak 12,55513 Feb20 Oct
12,732Peak Premier in tracked matches
37Days played since 2026-02-13

Premier CS Rating

  • 3,385 below peak (12,555)
  • Next: Blue band at 10,000 — 830 to go
  • Reached: Blue band · Light Blue band

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

Share this profile

CSDB.GGFogsFACEITLevel 3STANDINGTop 90.6% of rankedPREMIER9,170 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim70
Positioning55
Utility61

0–100 skill scores via Leetify.

Recent form

COLD36–61–3Last 10036%Win rateLWLWLLLLWL

Last 10 vs previous 10: −20pp win rate · −0.03 avg rating · +1.8pp headshot accuracy · +45ms reaction

Win rate down 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 -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 597ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 14%
  • Avg reaction 589ms

Last 20

  • 8–12 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 567ms

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 against its own average).

Aim7.0
Utility6.1
Positioning5.5
Opening Duels3.8

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

Twistzz

Plays most like Twistzz 91% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Reaction time. 565ms 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

Aim7.0
Positioning5.5
Utility6.1
Mechanics5.7
Opening Duels6.2
Win Impact3.9

Composite 5.4/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time565ms−60ms
first ⅓ avg 625ms → last ⅓ avg 565ms
Headshot accuracy13.9%+2.2%
first ⅓ avg 11.7% → last ⅓ avg 13.9%

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.

Personal bests

0.14Best match rating · 13–3 · inferno, 6 Oct →
29%Best headshot accuracy · 7–13 · dust2, 28 Sept →
422msFastest reaction time · 2–13 · nuke, 5 Oct →
13–1Biggest win · inferno, 29 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
7–8In matches decided by ≤2 rounds
9Overtime games

Map breakdown

nukeBest map · 50% over 24mirageWeakest map · 0% over 5
MapGradePlayedRecordWin rateAvg rating
infernoC3013–1743%0.01
nukeB2412–1250%-0.00
ancientD174–1324%-0.02
anubisB105–550%-0.01
mirageD50–50%-0.04
dust2D50–50%0.01
cacheC52–340%-0.00
overpass—40–40%-0.03

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (0% over 5). Start with the 5 essential Mirage 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.

13.9%Headshot accuracy
36.8%Accuracy (enemy spotted)
35.9%Spray accuracy
75.5%Counter-strafing
8.3°Preaim
565msReaction time
58.2%T opening success
51.2%CT opening success
0.67Enemies flashed / flash
3.7%Flash assists
12.74HE damage / grenade
9.86Flashes / 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 13.8804% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Mirage

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

0% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage10–13-0.0212%20 Oct →
nuke16–13-0.0222%19 Oct →
mirage8–13-0.0622%11 Oct →
nuke13–90.0314%11 Oct →
inferno3–13-0.077%11 Oct →
dust24–13-0.0114%11 Oct →
mirage8–130.0215%10 Oct →
cache7–130.0313%10 Oct →
nuke13–90.006%10 Oct →
dust24–130.0517%10 Oct →
cache6–130.0312%7 Oct →
inferno4–13-0.014%7 Oct →
inferno13–70.1218%7 Oct →
inferno11–13-0.0411%6 Oct →
nuke13–100.0311%6 Oct →
inferno13–30.1413%6 Oct →
nuke2–13-0.080%5 Oct →
inferno13–40.0919%5 Oct →
cache13–11-0.0022%3 Oct →
ancient8–13-0.0614%3 Oct →
mirage9–13-0.0315%2 Oct →
anubis13–4-0.004%2 Oct →
inferno13–110.0615%2 Oct →
inferno13–10.0311%29 Sept →
nuke13–100.0815%29 Sept →
nuke13–40.036%28 Sept →
nuke13–7-0.0117%28 Sept →
dust27–130.0329%28 Sept →
inferno11–130.0019%26 Sept →
inferno6–13-0.028%26 Sept →
inferno9–130.0613%26 Sept →
dust27–13-0.0228%26 Sept →
ancient13–110.0416%26 Sept →
mirage6–13-0.1210%26 Sept →
nuke10–13-0.0411%24 Sept →
ancient5–13-0.085%24 Sept →
dust28–13-0.0018%24 Sept →
ancient7–13-0.0516%19 Sept →
inferno15–15-0.028%19 Sept →
cache11–13-0.019%19 Sept →
anubis13–7-0.029%19 Sept →
inferno9–130.017%18 Sept →
ancient9–13-0.0911%16 Sept →
inferno13–3-0.0410%15 Sept →
nuke13–60.059%15 Sept →
ancient6–130.0222%13 Sept →
inferno16–13-0.0210%12 Sept →
ancient13–90.0313%12 Sept →
nuke10–130.0116%12 Sept →
inferno3–13-0.064%12 Sept →
nuke9–130.0613%12 Sept →
ancient4–13-0.090%10 Aug →
anubis7–130.0213%10 Aug →
anubis7–13-0.017%10 Aug →
nuke5–13-0.1012%7 Aug →
inferno13–4-0.0111%7 Aug →
ancient13–160.0411%7 Aug →
cache13–9-0.0513%7 Aug →
nuke3–13-0.0311%7 Aug →
nuke13–40.0413%7 Aug →
overpass7–130.0614%28 May →
ancient8–13-0.0219%12 May →
inferno11–13-0.0212%12 May →
inferno13–8-0.0614%11 May →
nuke9–13-0.0316%11 May →
ancient7–13-0.0515%22 Apr →
nuke15–150.0512%22 Apr →
inferno8–13-0.018%21 Apr →
anubis13–5-0.0113%21 Apr →
inferno15–15-0.0115%15 Apr →
nuke13–6-0.0211%15 Apr →
overpass8–13-0.0213%15 Apr →
nuke4–13-0.088%12 Apr →
inferno10–130.0614%12 Apr →
ancient13–8-0.054%12 Apr →
inferno13–110.0311%1 Apr →
ancient13–110.0513%1 Apr →
nuke13–60.0519%1 Apr →
nuke3–13-0.079%24 Mar →
overpass1–13-0.0717%24 Mar →
anubis13–90.0312%21 Mar →
ancient11–130.0115%21 Mar →
inferno13–50.0413%21 Mar →
nuke13–50.057%21 Mar →
inferno5–13-0.0711%21 Mar →
ancient14–160.0313%14 Mar →
anubis13–5-0.0613%14 Mar →
anubis10–13-0.0312%24 Feb →
inferno16–140.0818%24 Feb →
ancient8–13-0.0614%22 Feb →
inferno4–13-0.0410%22 Feb →
nuke8–13-0.017%17 Feb →
anubis9–13-0.037%17 Feb →
ancient4–13-0.0110%17 Feb →
nuke11–13-0.029%14 Feb →
inferno14–16-0.035%14 Feb →
anubis7–130.0118%14 Feb →
inferno2–13-0.0512%13 Feb →
overpass6–13-0.105%13 Feb →
inferno13–110.0420%13 Feb →

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 →

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