Olav 0.5

Olav 0.5 — CS2 Stats

76561198149996885[U:1:189731157]Steam profile ↗✓ No bans

168Tracked matches65%Win rate2024Tracked since
105Hours in CS
CSDB Rating6.3 SolidPositional Player
Premier CS Rating12,556Blue band · top ~41.4% of ranked players (population est.)
WingmanSilver IV
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 2 Oct 2026 (15 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: 12,556 +3,305 30 Apr – 2 Oct · 22 days played
9,25114,797peak 14,79730 Apr2 Oct
14,999Peak Premier in tracked matches
41Days played since 2025-04-30

Premier CS Rating

  • 2,241 below peak (14,797)
  • -1,755 over 90 days
  • Next: Purple band at 15,000 — 2,444 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.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate45.0%42.0%44.3%meets
Shot accuracy0.0%9.6%11.9%11.9% short
Kill/death ratio1.330.981.03above
Match win rate51.6%43.8%45.2%above

This profile matches the typical Purple band player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGOlav 0.5PREMIER12,556 · Blue bandcsdb.gg/stats

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Performance scores

Aim68
Positioning71
Utility50

0–100 skill scores via Leetify.

Recent form

STEADY58–35–7Last 10058%Win rateWTLTWWWLLT

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · +0.9pp 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

  • 2–1–2 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 20%
  • Avg reaction 559ms

Last 10

  • 4–3–3 · 40% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 20%
  • Avg reaction 553ms

Last 20

  • 9–7–4 · 45% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 20%
  • Avg reaction 548ms

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 (+1.1 against its own average).

Aim6.8
Utility5.0
Positioning7.1
Opening Duels6.0

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

s1mple

Plays most like s1mple 84% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Strengths

T openings. 62% T opening-duel success — entries that actually open the round.

Areas to improve

Reaction time. 551ms 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

Aim6.8
Positioning7.1
Utility5.0
Mechanics5.1
Opening Duels7.0
Win Impact10.0

Composite 6.3/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.05+0.02
first ⅓ avg 0.03 → last ⅓ avg 0.05
Reaction time552ms−90ms
first ⅓ avg 642ms → last ⅓ avg 552ms
Headshot accuracy19.6%+2.1%
first ⅓ avg 17.5% → last ⅓ avg 19.6%

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

0.24Best match rating · 9–1 · inferno, 15 Mar →
46%Best headshot accuracy · 13–8 · mirage, 10 Sept →
391msFastest reaction time · 9–13 · mirage, 20 Mar →
13–0Biggest win · overpass, 4 Mar →

Across the last 100 tracked matches.

Highlights

13Longest win streak
5–7In matches decided by ≤2 rounds
16Overtime games

Map breakdown

overpassBest map · 75% over 8dust2Weakest map · 36% over 14
MapGradePlayedRecordWin rateAvg rating
mirageA2213–959%0.02
dust2C145–936%0.02
nukeA138–562%0.01
ancientA138–562%0.04
anubisB115–645%0.04
infernoS107–370%0.08
overpassS86–275%0.06
cache—42–250%0.15
office—11–0100%0.02
boulder—11–0100%0.09
fachwerk—11–0100%0.04
train—11–0100%0.13
palais—10–10%0.01

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (36% over 14). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

5,472Lifetime kills
1.33K/D · Top 10% of Blue band
281Matches
51.6%Match win rate · Top 10% of Blue band
45.0%Headshot % · Top 50% of Blue band
0.0%Shot accuracy
899MVPs
105Hours (in match)
237Bombs planted
70Bombs defused

Most-used weapons

Lifetime map wins

444dust2
415inferno
322nuke
39vertigo
26train
22office
16italy
2ar_baggage

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

19.8%Headshot accuracy
33.2%Accuracy (enemy spotted)
31.6%Spray accuracy
73.1%Counter-strafing
8.5°Preaim
551msReaction time
62.0%T opening success
54.3%CT opening success
0.53Enemies flashed / flash
2.8%Flash assists
8.96HE damage / grenade
7.49Flashes / match

Recommended for you

Spend your practice time on Dust 2

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

36% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
office13–80.0241%2 Oct →
cache12–120.109%2 Oct →
mirage11–13-0.039%2 Oct →
anubis15–150.0528%25 Sept →
nuke13–7-0.0015%25 Sept →
nuke13–90.0819%25 Sept →
cache13–30.1825%20 Sept →
ancient13–160.0923%20 Sept →
anubis8–13-0.0117%16 Sept →
mirage15–15-0.0220%15 Sept →
nuke13–60.089%15 Sept →
cache14–160.1014%14 Sept →
nuke8–13-0.0812%14 Sept →
mirage15–15-0.0422%14 Sept →
ancient13–70.0321%12 Sept →
ancient13–20.0913%12 Sept →
dust211–130.0223%12 Sept →
anubis13–50.0716%12 Sept →
mirage13–80.0346%10 Sept →
dust29–130.0120%10 Sept →
ancient13–90.0822%29 Aug →
mirage7–130.0214%29 Aug →
dust27–13-0.017%26 Aug →
dust213–80.0919%26 Aug →
ancient13–60.0517%21 Aug →
anubis13–80.0518%21 Aug →
dust213–80.0227%21 Aug →
boulder13–50.0930%21 Aug →
fachwerk13–50.0412%21 Aug →
cache7–00.2130%21 Aug →
inferno13–50.0716%21 Aug →
nuke13–40.0514%23 Jun →
overpass13–90.0120%23 Jun →
dust213–30.2218%21 Jun →
ancient16–140.0619%21 Jun →
anubis13–10.1625%13 Jun →
dust211–13-0.0017%22 May →
mirage16–120.0718%22 May →
mirage9–130.0823%22 May →
overpass13–30.1417%15 Apr →
dust29–13-0.0123%15 Apr →
anubis10–13-0.0210%29 Mar →
nuke13–80.0117%29 Mar →
mirage13–50.0724%29 Mar →
dust213–10.0015%29 Mar →
ancient13–160.0415%28 Mar →
dust24–13-0.043%28 Mar →
ancient13–80.0610%28 Mar →
nuke13–7-0.0417%28 Mar →
mirage9–13-0.0419%20 Mar →
dust215–15-0.0123%20 Mar →
inferno13–50.0621%19 Mar →
nuke1–13-0.0014%19 Mar →
ancient13–40.0518%16 Mar →
dust26–130.0223%16 Mar →
overpass10–130.0514%16 Mar →
inferno9–10.2428%15 Mar →
inferno13–70.1119%12 Mar →
inferno13–30.0627%12 Mar →
nuke9–13-0.0118%11 Mar →
anubis13–90.0120%11 Mar →
nuke16–12-0.0119%4 Mar →
overpass13–00.1422%4 Mar →
anubis15–15-0.0522%3 Mar →
ancient9–130.0223%27 Feb →
ancient7–13-0.0116%27 Feb →
anubis13–11-0.0020%27 Feb →
inferno13–160.0118%11 Jan →
anubis11–130.0514%8 Aug →
overpass13–7-0.0410%8 Aug →
inferno11–130.0123%8 Aug →
overpass13–30.0520%6 Aug →
inferno9–50.0915%31 May →
mirage8–130.0427%31 May →
dust25–13-0.067%28 May →
mirage13–70.0221%21 May →
ancient13–4-0.0313%21 May →
dust213–10-0.0122%21 May →
mirage16–130.0217%21 May →
nuke6–13-0.0413%10 May →
train13–60.1323%10 May →
mirage13–100.0716%10 May →
mirage8–130.1416%7 May →
anubis6–130.0813%7 May →
palais3–90.0121%6 May →
nuke9–50.1916%6 May →
overpass9–40.140%6 May →
inferno9–70.1022%6 May →
mirage13–110.0024%6 May →
mirage16–13-0.0415%6 May →
mirage2–8-0.0317%6 May →
nuke4–13-0.0722%5 May →
overpass7–9-0.0311%5 May →
inferno8–80.0327%5 May →
mirage13–2-0.0211%3 May →
ancient13–16-0.0014%2 May →
mirage16–140.0615%2 May →
mirage13–50.0117%2 May →
mirage13–10-0.0126%1 May →
mirage13–70.1231%30 Apr →

Match data via Leetify.

Recent teammates

Milestones

100 Matches13-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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