novaignis_

novaignis_ — CS2 Stats

NL76561198782304031[U:1:822038303]Steam profile ↗✓ No bans

512Tracked matches71%Win rate2026Tracked since
651Hours in CS10Hrs last 2 wks
CSDB Rating4.5 DevelopingPositional Player
Premier CS Rating4,451Grey band · top ~81.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Oct 2026 (21 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: 4,451 -696 30 Aug – 11 Oct · 8 days played
4,4515,356peak 5,35630 Aug11 Oct
5,356Peak Premier in tracked matches
27Days played since 2026-08-30

Premier CS Rating

  • 905 below peak (5,356)
  • -549 over 30 days · declining
  • Next: Light Blue band at 5,000 — 549 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-08-30

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 Grey band among CSDB-tracked players (n=3,645), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate43.6%38.2%39.9%above
Shot accuracy0.0%3.6%7.0%7.0% short
Kill/death ratio0.700.830.920.22 short
Match win rate45.2%40.2%42.3%above

This profile matches the typical Light Blue band player on 2 of 4 comparable metrics.

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

Share this profile

CSDB.GGnovaignis_PREMIER4,451 · Grey bandcsdb.gg/stats

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Performance scores

Aim72
Positioning37
Utility16

0–100 skill scores via Leetify.

Recent form

STEADY56–39–5Last 10056%Win rateWTWLLWLWWT

Last 10 vs previous 10: −30pp win rate · +0.02 avg rating · +0.6pp headshot accuracy · +65ms 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 (+0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 2–2–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 630ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 11%
  • Avg reaction 671ms

Last 20

  • 13–5–2 · 65% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 639ms

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 (+1.9 against its own average).

Aim7.2
Utility1.6
Positioning3.7
Opening Duels0.0

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

ropz

Plays most like ropz 85% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower opening-duel success; lower utility contribution.

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

Positioning. Positioning trails aim by 34 points — deaths here waste a strong aim profile.

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

Reaction time. 641ms 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

Aim7.2
Positioning3.7
Utility1.6
Mechanics5.8
Opening Duels0.0
Win Impact10.0

Composite 4.5/10 (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 rating-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time649ms+45ms
first ⅓ avg 604ms → last ⅓ avg 649ms
Headshot accuracy13.0%−2.9%
first ⅓ avg 15.9% → last ⅓ avg 13.0%

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

0.10Best match rating · 13–5 · nuke, 17 Sept →
29%Best headshot accuracy · 8–13 · train, 20 Sept →
438msFastest reaction time · 13–7 · inferno, 14 Sept →
13–1Biggest win · nuke, 4 Oct →

Across the last 100 tracked matches.

Highlights

8Longest win streak
2–7In matches decided by ≤2 rounds
3Overtime games

Map breakdown

trainBest map · 71% over 7cacheWeakest map · 25% over 12
MapGradePlayedRecordWin rateAvg rating
infernoS1913–668%-0.03
nukeA148–657%-0.04
anubisB147–750%-0.03
ancientS139–469%-0.02
cacheD123–925%-0.04
trainS75–271%-0.01
boulderB63–350%-0.02
dust2—41–325%-0.03
fachwerk—43–175%-0.01
shelter—31–233%-0.02
mirage—21–150%-0.06
vertigo—22–0100%-0.04

Across the last 100 tracked matches.

Lifetime stats

9,782Lifetime kills
0.70K/D
960Matches
45.2%Match win rate · Top 25% of Grey band
43.6%Headshot % · Top 25% of Grey band
0.0%Shot accuracy
1,215MVPs
361Hours (in match)
1,030Bombs planted
170Bombs defused

Most-used weapons

Lifetime map wins

1,547dust2
1,388inferno
728nuke
377vertigo
226office
181train
16bank
13safehouse

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.

12.7%Headshot accuracy
40.6%Accuracy (enemy spotted)
41.4%Spray accuracy
76.2%Counter-strafing
8.4°Preaim
641msReaction time
29.7%T opening success
28.9%CT opening success
0.30Enemies flashed / flash
0.0%Flash assists
3.40HE damage / grenade
1.77Flashes / 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 12.7294% — below the 15% mark we flag

    Aim Training →
  2. 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 0.301 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 29.6552% — below the 40% mark we flag

Spend your practice time on Cache

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

25% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

MapScoreRatingHS%Date
train13–8-0.0214%23 Oct →
cache12–12-0.0213%23 Oct →
ancient13–60.0116%21 Oct →
cache7–13-0.093%21 Oct →
dust210–130.006%21 Oct →
ancient13–20.0116%11 Oct →
cache9–13-0.048%11 Oct →
boulder9–00.0313%10 Oct →
boulder6–1-0.0411%9 Oct →
ancient12–120.0413%9 Oct →
mirage13–9-0.0511%9 Oct →
ancient13–8-0.076%9 Oct →
train13–40.0112%9 Oct →
cache10–13-0.0710%7 Oct →
ancient13–7-0.106%7 Oct →
nuke10–13-0.0615%7 Oct →
inferno13–80.0119%6 Oct →
inferno13–7-0.0110%6 Oct →
anubis13–9-0.0310%4 Oct →
fachwerk13–6-0.0110%4 Oct →
shelter13–5-0.0217%4 Oct →
nuke13–1-0.0427%4 Oct →
dust211–13-0.0511%3 Oct →
cache13–5-0.0213%3 Oct →
nuke13–6-0.0622%3 Oct →
inferno11–13-0.0418%3 Oct →
nuke5–2-0.038%3 Oct →
inferno10–130.019%3 Oct →
anubis13–10-0.0717%3 Oct →
cache13–5-0.0523%3 Oct →
nuke13–3-0.098%3 Oct →
inferno13–8-0.0716%2 Oct →
fachwerk13–40.0618%2 Oct →
vertigo13–4-0.0612%2 Oct →
nuke13–6-0.0716%1 Oct →
anubis13–4-0.0015%1 Oct →
inferno6–13-0.0813%1 Oct →
inferno13–7-0.059%1 Oct →
inferno13–9-0.0417%30 Sept →
ancient13–100.0114%30 Sept →
anubis14–16-0.0318%27 Sept →
mirage6–13-0.0610%27 Sept →
train13–8-0.0214%25 Sept →
anubis7–130.0012%25 Sept →
inferno13–40.0211%24 Sept →
anubis13–4-0.108%24 Sept →
dust212–12-0.0711%24 Sept →
inferno9–13-0.022%23 Sept →
cache8–13-0.0511%23 Sept →
cache6–13-0.0122%23 Sept →
anubis13–9-0.0313%23 Sept →
inferno13–9-0.046%22 Sept →
shelter11–13-0.028%22 Sept →
anubis9–13-0.0619%22 Sept →
inferno4–13-0.0412%22 Sept →
cache3–13-0.0816%21 Sept →
train13–30.0316%21 Sept →
train6–130.0315%20 Sept →
train8–13-0.0129%20 Sept →
ancient13–9-0.0418%19 Sept →
boulder13–6-0.037%19 Sept →
ancient13–7-0.0117%19 Sept →
shelter6–13-0.0110%18 Sept →
fachwerk0–4-0.040%18 Sept →
boulder10–13-0.0617%18 Sept →
ancient10–13-0.0110%18 Sept →
nuke2–13-0.059%18 Sept →
inferno7–13-0.0020%18 Sept →
ancient13–7-0.0512%17 Sept →
nuke9–13-0.0213%17 Sept →
inferno13–9-0.0715%17 Sept →
anubis7–13-0.0410%17 Sept →
cache12–16-0.059%17 Sept →
nuke13–50.1019%17 Sept →
anubis13–5-0.0426%16 Sept →
inferno13–10.0423%16 Sept →
anubis11–130.0116%16 Sept →
cache13–2-0.0021%16 Sept →
ancient12–12-0.0110%15 Sept →
boulder2–13-0.0122%15 Sept →
anubis6–13-0.0513%15 Sept →
nuke3–13-0.0519%15 Sept →
inferno13–7-0.0517%14 Sept →
nuke4–13-0.047%14 Sept →
anubis11–13-0.0416%14 Sept →
nuke13–11-0.0022%14 Sept →
inferno13–8-0.054%13 Sept →
anubis13–6-0.0210%13 Sept →
inferno13–8-0.0323%13 Sept →
nuke5–13-0.029%13 Sept →
ancient14–16-0.0214%13 Sept →
cache5–13-0.0428%13 Sept →
vertigo13–5-0.0219%13 Sept →
fachwerk13–11-0.0310%13 Sept →
nuke13–4-0.0618%13 Sept →
boulder12–120.0229%13 Sept →
inferno13–9-0.0313%13 Sept →
train13–3-0.0713%13 Sept →
ancient13–3-0.0411%13 Sept →
dust213–70.0019%12 Sept →

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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