SÄKKI-SAKKE

SÄKKI-SAKKE — CS2 Stats

76561198158695417[U:1:198429689]Steam profile ↗✓ No bans

1,114Tracked matches40%Win rate2020Tracked since
CSDB Rating3.3 LearningSupport
FaceitLevel 5 · 1,028 ELOTop 67.6% of ranked FACEIT players
WingmanMaster Guardian Elite
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 18 Sep 2026 (24 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 1,028 → 1,028
+7Tracked matches · now 1,114
0.0ppWin rate · 40.0% → 40.0%

Rating over time

Premier CS Rating: 15,852 +237 7 Nov – 22 May · 37 days played
13,16118,269peak 18,2697 Nov22 May
18,269Peak Premier in tracked matches
1,028Highest Faceit ELO seen on CSDB
67Days played since 2025-11-07

Faceit ELO

  • At peak — 1,028
  • Next: Level 5 at 1,051 — 23 to go
  • Reached: Level 4 · Level 3 · Level 2
  • Level 4 first seen 2026-09-18
  • Level 3 first seen 2026-09-18

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

Share this profile

CSDB.GGSÄKKI-SAKKEFACEITLevel 5 · 1,028 ELOSTANDINGTop 67.6% of rankedPEAK ELO1,028csdb.gg/stats

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Performance scores

Aim39
Positioning40
Utility51

0–100 skill scores via Leetify.

Recent form

STEADY37–60–3Last 10037%Win rateLWWLLWLLWW

Last 10 vs previous 10: +40pp win rate · +0.00 avg rating · −2.2pp headshot accuracy · +28ms reaction

Win rate up 40pp 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 -0.02
  • Avg headshot accuracy 15%
  • Avg reaction 578ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 15%
  • Avg reaction 597ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 16%
  • Avg reaction 583ms

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 against its own average).

Aim3.9
Utility5.1
Positioning4.0
Opening Duels0.0
Clutch3.2

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

Twistzz

Plays most like Twistzz 73% playstyle similarity

Most alike: positioning profile, utility contribution.

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

Areas to improve

Reaction time. 592ms 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

Aim3.9
Positioning4.0
Utility5.1
Mechanics4.5
Opening Duels0.8
Win Impact1.7

Composite 3.3/10 (Learning), 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 rating-0.04−0.01
first ⅓ avg -0.03 → last ⅓ avg -0.04
Reaction time599ms−17ms
first ⅓ avg 616ms → last ⅓ avg 599ms
Headshot accuracy15.4%+0.3%
first ⅓ avg 15.1% → last ⅓ avg 15.4%

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

0.12Best match rating · 6–13 · nuke, 7 Mar →
32%Best headshot accuracy · 4–13 · dust2, 4 Sept →
406msFastest reaction time · 0–13 · nuke, 22 Aug →
13–1Biggest win · nuke, 19 May →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–6In matches decided by ≤2 rounds
11Overtime games

Map breakdown

nukeBest map · 55% over 22trainWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
nukeA2212–1055%-0.02
dust2D216–1529%-0.04
ancientD185–1328%-0.04
infernoC135–838%-0.02
anubisD93–633%-0.01
overpassC73–443%-0.03
trainD51–420%0.00
mirage—31–233%-0.04
cache—21–150%-0.01

Across the last 100 tracked matches.

Faceit stats

Combat

544Matches
47%Win rate
0.97Avg K/D
67.6ADR
33%Headshot %

Clutches & streaks

36%1v1 clutch win
16%1v2 clutch win
8Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient4443%0.8012.9
Nuke3850%0.8613.6
Anubis1414%0.589.1
Dust21346%0.8511.9
Train1164%1.0213.6
Mirage825%0.7413.1
Inferno729%0.7914.3
Vertigo475%0.9413.8

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.

15.9%Headshot accuracy
27.8%Accuracy (enemy spotted)
29.7%Spray accuracy
70.4%Counter-strafing
11.1°Preaim
592msReaction time
30.6%T opening success
35.4%CT opening success
0.55Enemies flashed / flash
8.9%Flash assists
9.26HE damage / grenade
4.99Flashes / 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

    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 30.5858% — below the 40% mark we flag

Spend your practice time on Train

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
inferno14–16-0.0517%10 Oct →
inferno13–30.0112%1 Oct →
nuke13–6-0.0018%1 Oct →
cache4–13-0.0214%23 Sept →
ancient9–13-0.0315%21 Sept →
anubis13–2-0.014%15 Sept →
dust24–13-0.0432%4 Sept →
dust24–13-0.0916%30 Aug →
cache13–90.0115%27 Aug →
dust213–9-0.087%26 Aug →
nuke0–13-0.0925%22 Aug →
dust213–110.0123%12 Aug →
dust25–13-0.079%7 Aug →
nuke6–13-0.0916%7 Aug →
anubis9–13-0.0515%24 Jul →
anubis7–130.0226%27 Jun →
dust23–13-0.0210%27 Jun →
anubis8–13-0.0711%15 Jun →
ancient13–160.0421%22 May →
dust27–13-0.0418%20 May →
overpass13–9-0.0412%19 May →
nuke13–1-0.039%19 May →
ancient14–16-0.0415%16 May →
nuke13–100.0126%16 May →
ancient13–11-0.0318%13 May →
inferno9–13-0.093%13 May →
nuke7–13-0.068%8 May →
anubis13–80.0421%8 May →
ancient13–11-0.0719%8 May →
mirage8–13-0.0617%6 May →
nuke9–13-0.056%6 May →
dust213–16-0.0414%29 Apr →
inferno10–13-0.0717%28 Apr →
nuke13–10-0.026%22 Apr →
dust213–11-0.068%21 Apr →
ancient9–13-0.0512%21 Apr →
inferno6–13-0.0515%19 Apr →
nuke11–130.0017%19 Apr →
anubis9–13-0.048%15 Apr →
inferno10–13-0.0216%9 Apr →
dust210–13-0.0315%9 Apr →
anubis13–90.0914%8 Apr →
overpass4–13-0.088%8 Apr →
nuke13–10-0.0210%7 Apr →
dust210–130.0217%7 Apr →
nuke6–13-0.050%2 Apr →
ancient13–80.048%2 Apr →
dust211–13-0.0115%1 Apr →
inferno9–13-0.0526%1 Apr →
overpass7–13-0.0128%31 Mar →
nuke13–7-0.0216%29 Mar →
nuke16–140.0114%29 Mar →
inferno16–12-0.0620%28 Mar →
overpass6–13-0.0525%24 Mar →
ancient11–130.0113%24 Mar →
dust25–13-0.077%23 Mar →
nuke13–80.0414%23 Mar →
ancient8–13-0.036%22 Mar →
nuke4–13-0.0620%20 Mar →
ancient13–8-0.0121%20 Mar →
inferno9–60.0821%20 Mar →
mirage4–13-0.0017%20 Mar →
ancient6–13-0.0410%15 Mar →
dust213–90.0010%14 Mar →
overpass13–9-0.0611%11 Mar →
mirage13–11-0.055%11 Mar →
inferno13–90.0423%11 Mar →
anubis4–13-0.0714%10 Mar →
anubis6–13-0.038%7 Mar →
nuke6–130.1222%7 Mar →
inferno8–13-0.0216%6 Mar →
ancient13–10-0.0514%6 Mar →
ancient8–13-0.0614%1 Mar →
ancient3–13-0.1513%1 Mar →
ancient15–15-0.0510%25 Feb →
nuke13–20.0511%25 Feb →
overpass14–16-0.0015%19 Feb →
nuke13–10-0.0610%19 Feb →
dust20–13-0.090%17 Feb →
nuke15–15-0.0115%8 Feb →
dust216–13-0.059%6 Feb →
inferno13–90.0016%28 Jan →
train8–13-0.0019%16 Jan →
train13–70.0119%14 Jan →
nuke13–7-0.023%8 Jan →
nuke13–90.0624%2 Jan →
inferno10–13-0.0426%1 Jan →
dust213–5-0.0221%28 Dec →
train5–13-0.0121%25 Dec →
ancient8–13-0.0315%10 Dec →
ancient8–13-0.0524%27 Nov →
dust28–13-0.0612%27 Nov →
train8–13-0.015%18 Nov →
train8–130.0224%15 Nov →
dust28–13-0.0718%15 Nov →
dust25–13-0.0513%11 Nov →
nuke9–13-0.0521%11 Nov →
ancient7–13-0.108%8 Nov →
dust215–15-0.0123%8 Nov →
overpass13–10.0515%7 Nov →

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 →

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