Lasse Öysä

Lasse Öysä — CS2 Stats

FI76561199697846220[U:1:1737580492]Steam profile ↗✓ No bans

136Tracked matches41%Win rate2024Tracked since
CSDB Rating4.5 DevelopingAll-Rounder
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 10,810 +1,234 8 Jul – 22 Dec · 14 days played
9,32310,961peak 10,9618 Jul22 Dec
11,454Peak Premier in tracked matches
36Days played since 2024-07-08

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

Performance scores

Aim50
Positioning47
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY45–53–2Last 10045%Win rateLLLLWWLWLW

Last 10 vs previous 10: −20pp win rate · +0.00 avg rating · −3.3pp headshot accuracy · −39ms reaction

Win rate down 20pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 18%
  • Avg reaction 670ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 18%
  • Avg reaction 630ms

Last 20

  • 10–9–1 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 20%
  • Avg reaction 649ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim5.0
Utility4.5
Positioning4.7
Opening Duels4.3

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

device

Plays most like device 85% 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

T-side openings. Opening success drops from 53% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 639ms 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

Aim5.0
Positioning4.7
Utility4.5
Mechanics5.4
Opening Duels3.6
Win Impact2.1

Composite 4.5/10 (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 time636ms−13ms
first ⅓ avg 648ms → last ⅓ avg 636ms
Headshot accuracy20.7%+4.9%
first ⅓ avg 15.8% → last ⅓ avg 20.7%

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

0.16Best match rating · 13–6 · ancient, 13 Mar →
48%Best headshot accuracy · 13–8 · train, 22 Mar →
422msFastest reaction time · 13–11 · nuke, 12 Feb →
13–1Biggest win · nuke, 21 Feb →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L4Current streak
6–2In matches decided by ≤2 rounds
8Overtime games

Map breakdown

overpassBest map · 80% over 5mirageWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
infernoB168–850%0.02
nukeA169–756%0.00
mirageD144–1029%-0.04
ancientD134–931%0.02
anubisA138–562%0.03
dust2C114–736%-0.03
trainD72–529%-0.01
overpassS54–180%0.02
vertigo—21–150%-0.01
italy—11–0100%-0.05
grail—10–10%-0.01
office—10–10%-0.02

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (29% over 14). 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.

20.9%Headshot accuracy
29.3%Accuracy (enemy spotted)
34.3%Spray accuracy
74.2%Counter-strafing
11.1°Preaim
639msReaction time
35.7%T opening success
53.4%CT opening success
0.57Enemies flashed / flash
10.0%Flash assists
8.32HE damage / grenade
8.57Flashes / 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 35.6795% — below the 40% mark we flag

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.

29% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno9–110.0122%17 Apr →
nuke9–130.0017%17 Apr →
mirage3–13-0.1018%17 Apr →
dust213–16-0.0517%17 Apr →
dust213–8-0.0117%22 Dec →
dust213–9-0.0710%19 Dec →
nuke8–130.0618%30 Oct →
mirage13–70.0618%30 Oct →
dust210–130.0219%30 Oct →
nuke13–60.0125%30 Oct →
overpass13–11-0.0314%30 Oct →
train15–15-0.0525%29 Oct →
nuke13–11-0.0139%29 Oct →
train5–130.0220%27 Sept →
inferno7–130.0813%27 Sept →
nuke7–20.0720%27 Sept →
italy13–10-0.0526%23 Sept →
nuke13–70.0121%23 Sept →
overpass13–8-0.0514%23 Sept →
dust26–13-0.0823%23 Sept →
ancient4–13-0.0234%23 Sept →
grail3–13-0.0130%11 Sept →
inferno13–60.0017%11 Sept →
ancient9–130.0516%11 Sept →
train5–130.0132%11 Sept →
mirage3–13-0.0513%11 Sept →
inferno7–13-0.0614%20 Aug →
nuke0–13-0.060%20 Aug →
dust213–9-0.0647%16 Aug →
ancient11–130.0324%9 Aug →
inferno10–00.0319%26 Jul →
overpass13–50.1427%26 Jul →
dust26–13-0.0316%23 Jul →
overpass3–130.0019%23 Jul →
mirage3–13-0.1025%23 Jul →
nuke13–40.1233%23 Jul →
ancient6–130.0827%23 Jul →
inferno15–150.0923%23 Jul →
overpass13–80.0312%23 Jul →
ancient6–13-0.0638%22 Jul →
mirage4–13-0.0824%22 Jul →
ancient13–80.0216%25 Mar →
train13–80.0248%22 Mar →
nuke4–13-0.0625%22 Mar →
anubis13–40.0820%22 Mar →
mirage4–13-0.0112%22 Mar →
ancient13–60.1633%13 Mar →
mirage3–13-0.1033%13 Mar →
office7–13-0.0229%13 Mar →
train10–130.0018%4 Mar →
anubis13–40.0616%4 Mar →
mirage13–50.0219%27 Feb →
train8–13-0.1118%27 Feb →
mirage13–11-0.190%25 Feb →
anubis13–20.0716%25 Feb →
mirage9–13-0.0626%21 Feb →
nuke13–10.0319%21 Feb →
train13–90.0331%20 Feb →
nuke13–110.0114%12 Feb →
mirage10–130.0116%12 Feb →
dust213–3-0.0121%12 Feb →
vertigo13–60.1015%2 Jan →
anubis10–130.0919%2 Jan →
anubis13–80.0520%1 Jan →
inferno13–60.0110%1 Jan →
anubis4–130.0015%21 Dec →
dust21–13-0.0515%21 Dec →
mirage4–13-0.0311%21 Dec →
ancient6–13-0.027%19 Dec →
dust27–130.0316%19 Dec →
anubis13–100.0213%18 Dec →
ancient12–16-0.0610%15 Dec →
inferno13–7-0.0137%15 Dec →
inferno13–60.0510%15 Dec →
mirage2–13-0.0312%15 Aug →
inferno5–130.0027%15 Aug →
anubis4–130.0317%15 Aug →
ancient13–60.0814%15 Aug →
mirage13–30.0428%15 Aug →
nuke6–130.0220%15 Aug →
anubis13–16-0.0520%15 Aug →
nuke13–80.0111%13 Aug →
anubis13–80.0410%13 Aug →
inferno3–13-0.0326%13 Aug →
anubis13–11-0.042%4 Aug →
dust210–13-0.0315%4 Aug →
ancient13–110.0314%4 Aug →
inferno13–9-0.049%4 Aug →
nuke16–13-0.0619%3 Aug →
ancient8–13-0.0423%3 Aug →
inferno6–130.0013%3 Aug →
anubis13–16-0.069%3 Aug →
nuke0–13-0.118%3 Aug →
inferno13–50.099%3 Aug →
inferno6–13-0.0721%1 Aug →
vertigo2–13-0.1122%1 Aug →
anubis13–40.0713%1 Aug →
ancient13–16-0.0117%1 Aug →
nuke5–13-0.0421%9 Jul →
inferno13–50.1519%8 Jul →

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 →

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