The Unibonger — CS2 Stats
US76561197962337526[U:1:2071798]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 3 among CSDB-tracked players (n=10,505), 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.
| Metric | This player | Level 3 median | Level 4 median | vs Level 4 |
|---|---|---|---|---|
| Headshot rate | 35.9% | 41.8% | 42.7% | 6.9% short |
| Shot accuracy | 9.0% | 12.2% | 11.2% | 2.3% short |
| Kill/death ratio | 0.98 | 0.98 | 0.99 | meets |
| Match win rate | 40.0% | 43.3% | 43.9% | 3.9% short |
This profile matches the typical Level 4 player on 1 of 4 comparable metrics.
Widest gap: Shot accuracy. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +10pp win rate · −0.00 avg rating · +5.2pp headshot accuracy · +63ms 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
- 3–2 · 60% win rate
- Avg rating 0.03
- Avg headshot accuracy 15%
- Avg reaction 541ms
Last 10
- 6–4 · 60% win rate
- Avg rating 0.01
- Avg headshot accuracy 19%
- Avg reaction 525ms
Last 20
- 11–6–3 · 55% win rate
- Avg rating 0.01
- Avg headshot accuracy 17%
- Avg reaction 494ms
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 (+1.7 against its own average).
Sharp aimerLimited 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
Plays most like donk 74% playstyle similarity
Most alike: aim profile, positioning 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
Strengths
Aim. Aim score of 85 — the mechanical foundation is a clear strength.
T openings. 61% T opening-duel success — entries that actually open the round.
Areas to improve
Preaim. Mechanical aim is strong but the crosshair sits 14.3° off target when enemies appear — placement, not flicking, is the bigger win available.
Positioning. Positioning trails aim by 35 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.
CT openings. Opening success drops from 61% on T to 42% on CT — first contacts on the defending side are being lost.
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
Composite 6.1/10 (Solid), 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
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
Across the last 100 tracked matches.
Highlights
Map breakdown
Strongest and weakest map need 5+ matches on two different maps — 1 of 8 maps qualify so far.
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 nuke | A | 89 | 51–38 | 57% | 0.02 |
 inferno | — | 3 | 1–2 | 33% | 0.07 |
 vertigo | — | 2 | 1–1 | 50% | -0.01 |
 mirage | — | 2 | 2–0 | 100% | 0.03 |
 dust2 | — | 1 | 1–0 | 100% | 0.10 |
| office | — | 1 | 1–0 | 100% | -0.03 |
 anubis | — | 1 | 0–1 | 0% | -0.08 |
 ancient | — | 1 | 0–1 | 0% | 0.03 |
Across the last 100 tracked matches.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLLLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 10 | 30% | 0.73 | 12.4 |
| Ancient | 5 | 0% | 0.58 | 9.8 |
| Dust2 | 4 | 25% | 0.91 | 17.3 |
| Nuke | 4 | 50% | 0.62 | 8.5 |
| Vertigo | 4 | 25% | 0.57 | 11.3 |
| Inferno | 3 | 67% | 1.02 | 11.3 |
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.
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.
- Advanced MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 14.2976° — above the 12° mark we flag
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3118 — below the 0.5 mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| nuke | 8–13 | -0.06 | 25% | 3 Nov → | |
| nuke | 4–13 | -0.03 | 0% | 3 Nov → | |
| dust2 | 13–3 | 0.10 | 14% | 3 Nov → | |
| nuke | 13–9 | 0.12 | 0% | 28 Oct → | |
| vertigo | 13–8 | 0.02 | 38% | 28 Oct → | |
| nuke | 6–13 | -0.05 | 50% | 28 Oct → | |
| nuke | 13–9 | 0.01 | 17% | 28 Oct → | |
| nuke | 5–13 | -0.06 | 0% | 28 Oct → | |
| nuke | 13–8 | 0.00 | 50% | 28 Oct → | |
| nuke | 13–11 | 0.03 | 0% | 27 Oct → | |
| nuke | 12–12 | -0.02 | 30% | 27 Oct → | |
| nuke | 5–13 | 0.03 | 0% | 27 Oct → | |
| nuke | 13–10 | -0.02 | 33% | 27 Oct → | |
| nuke | 9–13 | 0.01 | 0% | 27 Oct → | |
| nuke | 13–8 | -0.01 | 0% | 27 Oct → | |
| nuke | 12–12 | -0.00 | 0% | 27 Oct → | |
| nuke | 13–5 | 0.04 | 12% | 27 Oct → | |
| nuke | 13–3 | 0.01 | 50% | 27 Oct → | |
| nuke | 13–5 | 0.07 | 15% | 27 Oct → | |
| inferno | 8–8 | 0.02 | 0% | 26 Oct → | |
| inferno | 9–4 | 0.20 | 50% | 26 Oct → | |
| nuke | 8–8 | 0.01 | 0% | 26 Oct → | |
| nuke | 12–12 | 0.06 | 0% | 26 Oct → | |
| nuke | 13–8 | 0.01 | 0% | 26 Oct → | |
| nuke | 5–13 | 0.06 | 25% | 26 Oct → | |
| nuke | 4–1 | -0.02 | 0% | 26 Oct → | |
| nuke | 8–13 | -0.04 | 7% | 26 Oct → | |
| nuke | 10–13 | 0.05 | 0% | 26 Oct → | |
| nuke | 13–9 | 0.04 | 21% | 24 Oct → | |
| nuke | 13–4 | 0.10 | 0% | 24 Oct → | |
| nuke | 13–4 | 0.17 | 50% | 24 Oct → | |
| nuke | 13–10 | 0.03 | 0% | 24 Oct → | |
| nuke | 11–4 | 0.01 | 25% | 24 Oct → | |
| nuke | 13–3 | 0.08 | 33% | 24 Oct → | |
| nuke | 12–12 | -0.01 | 20% | 24 Oct → | |
| inferno | 6–9 | -0.01 | 44% | 23 Oct → | |
| vertigo | 6–13 | -0.04 | 17% | 23 Oct → | |
| nuke | 13–1 | 0.08 | 50% | 23 Oct → | |
| office | 8–3 | -0.03 | 0% | 23 Oct → | |
| mirage | 13–6 | 0.08 | 18% | 23 Oct → | |
| nuke | 13–2 | 0.01 | 50% | 23 Oct → | |
| nuke | 13–6 | 0.04 | 0% | 23 Oct → | |
| nuke | 12–12 | -0.00 | 33% | 23 Oct → | |
| nuke | 13–9 | 0.11 | 0% | 23 Oct → | |
| nuke | 11–13 | -0.03 | 100% | 23 Oct → | |
| nuke | 13–10 | -0.02 | 40% | 23 Oct → | |
| nuke | 13–8 | 0.08 | 15% | 23 Oct → | |
| anubis | 5–13 | -0.08 | 23% | 23 Oct → | |
| nuke | 10–13 | 0.03 | 14% | 22 Oct → | |
| nuke | 8–13 | -0.02 | 33% | 22 Oct → | |
| nuke | 12–12 | 0.03 | 6% | 22 Oct → | |
| nuke | 13–6 | 0.02 | 11% | 22 Oct → | |
| nuke | 13–7 | 0.05 | 13% | 22 Oct → | |
| nuke | 8–13 | 0.09 | 17% | 22 Oct → | |
| nuke | 13–9 | 0.19 | 13% | 22 Oct → | |
| nuke | 13–2 | 0.13 | 0% | 22 Oct → | |
| nuke | 13–5 | 0.12 | 9% | 22 Oct → | |
| nuke | 6–13 | -0.05 | 0% | 21 Oct → | |
| nuke | 6–13 | -0.07 | 7% | 21 Oct → | |
| nuke | 13–4 | 0.01 | 33% | 21 Oct → | |
| nuke | 13–7 | 0.01 | 0% | 21 Oct → | |
| nuke | 4–13 | 0.00 | 0% | 21 Oct → | |
| mirage | 13–8 | -0.03 | 10% | 18 Oct → | |
| nuke | 2–13 | -0.10 | 0% | 18 Oct → | |
| nuke | 13–7 | 0.04 | 0% | 18 Oct → | |
| nuke | 6–13 | -0.09 | 0% | 18 Oct → | |
| nuke | 13–4 | 0.09 | 11% | 18 Oct → | |
| nuke | 13–10 | 0.03 | 38% | 18 Oct → | |
| nuke | 12–12 | -0.08 | 33% | 18 Oct → | |
| nuke | 13–5 | 0.10 | 29% | 18 Oct → | |
| nuke | 13–2 | 0.06 | 56% | 18 Oct → | |
| nuke | 13–10 | 0.01 | 0% | 17 Oct → | |
| nuke | 13–11 | 0.07 | 5% | 17 Oct → | |
| nuke | 13–4 | 0.10 | 0% | 17 Oct → | |
| nuke | 13–8 | 0.10 | 29% | 17 Oct → | |
| nuke | 13–8 | 0.13 | 29% | 17 Oct → | |
| nuke | 12–12 | 0.08 | 0% | 17 Oct → | |
| nuke | 13–10 | 0.02 | 22% | 17 Oct → | |
| nuke | 6–13 | -0.09 | 0% | 16 Oct → | |
| nuke | 13–8 | 0.02 | 9% | 16 Oct → | |
| nuke | 12–12 | -0.01 | 20% | 16 Oct → | |
| nuke | 13–8 | -0.02 | 25% | 15 Oct → | |
| nuke | 13–6 | 0.06 | 67% | 15 Oct → | |
| nuke | 13–6 | 0.03 | 0% | 15 Oct → | |
| nuke | 13–2 | -0.05 | 67% | 14 Oct → | |
| nuke | 13–1 | 0.05 | 0% | 14 Oct → | |
| nuke | 6–13 | -0.03 | 20% | 14 Oct → | |
| nuke | 12–12 | 0.05 | 18% | 14 Oct → | |
| nuke | 13–7 | -0.07 | 25% | 14 Oct → | |
| nuke | 5–13 | -0.04 | 0% | 14 Oct → | |
| nuke | 13–8 | 0.09 | 17% | 13 Oct → | |
| nuke | 12–12 | 0.01 | 50% | 13 Oct → | |
| nuke | 5–13 | -0.06 | 50% | 13 Oct → | |
| nuke | 3–13 | -0.08 | 0% | 8 Oct → | |
| nuke | 10–10 | 0.01 | 25% | 8 Oct → | |
| nuke | 12–12 | 0.05 | 100% | 8 Oct → | |
| nuke | 13–6 | 0.05 | 25% | 8 Oct → | |
| nuke | 11–13 | 0.02 | 22% | 8 Oct → | |
| ancient | 11–13 | 0.03 | 33% | 7 Oct → | |
| nuke | 9–13 | 0.13 | 22% | 6 Oct → |
Match data via Leetify.
Recent teammates
Milestones
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