$tunna — CS2 Stats
CA76561199013669756[U:1:1053404028]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Light Blue band among CSDB-tracked players (n=404), 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 | Light Blue band median | Blue band median | vs Blue band |
|---|---|---|---|---|
| Headshot rate | 37.4% | 40.1% | 41.7% | 4.2% short |
| Shot accuracy | 5.4% | 7.6% | 8.8% | 3.4% short |
| Kill/death ratio | 0.86 | 0.92 | 0.97 | 0.11 short |
| Match win rate | 42.5% | 42.2% | 43.8% | 1.3% short |
This profile sits below the typical Blue band player on every metric we can compare.
Widest gap: Shot accuracy. That is the metric furthest from the Blue band 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: -20pp win rate · -0.02 avg rating
Player DNA
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
Your pro match

Plays most like NiKo 60% playstyle similarity
Most alike: opening-duel success, positioning profile.
Where you differ: lower utility contribution; 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 32% on CT to 12% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 659ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 63% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.
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 2.4/10 (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
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.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| C | 21 | 8–13 | 38% | -0.03 | |
| C | 21 | 8–13 | 38% | -0.03 | |
| B | 17 | 9–8 | 53% | -0.02 | |
| S | 12 | 8–4 | 67% | -0.02 | |
| A | 11 | 6–5 | 55% | -0.04 | |
| C | 10 | 4–6 | 40% | -0.02 | |
| B | 6 | 3–3 | 50% | -0.09 | |
| — | 2 | 1–1 | 50% | -0.04 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (38% over 21). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.
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.
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 12.0545° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 10.0261% — below the 15% 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 0.1288 — below the 0.5 mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
38% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–11 | -0.00 | 4% | 27 Aug → | ||
| 9–3 | -0.02 | 18% | 27 Aug → | ||
| 13–8 | -0.02 | 5% | 27 Aug → | ||
| 6–13 | -0.08 | 9% | 26 Aug → | ||
| 10–13 | -0.06 | 4% | 26 Aug → | ||
| 4–11 | -0.10 | 7% | 24 Aug → | ||
| 13–9 | -0.04 | 13% | 24 Aug → | ||
| 6–13 | -0.09 | 11% | 23 Aug → | ||
| 12–16 | -0.02 | 9% | 23 Aug → | ||
| 9–13 | -0.09 | 14% | 23 Aug → | ||
| 11–13 | -0.06 | 16% | 22 Aug → | ||
| 9–13 | -0.11 | 12% | 22 Aug → | ||
| 7–2 | -0.00 | 0% | 22 Aug → | ||
| 13–9 | 0.04 | 7% | 22 Aug → | ||
| 9–13 | -0.05 | 16% | 22 Aug → | ||
| 2–13 | -0.01 | 3% | 22 Aug → | ||
| 13–8 | -0.07 | 10% | 22 Aug → | ||
| 13–7 | -0.02 | 10% | 22 Aug → | ||
| 13–3 | 0.04 | 13% | 22 Aug → | ||
| 13–9 | -0.04 | 6% | 21 Aug → | ||
| 13–5 | 0.01 | 9% | 21 Aug → | ||
| 4–13 | -0.07 | 4% | 21 Aug → | ||
| 16–12 | -0.01 | 6% | 21 Aug → | ||
| 2–13 | -0.01 | 28% | 21 Aug → | ||
| 13–11 | -0.04 | 9% | 21 Aug → | ||
| 3–13 | 0.01 | 50% | 20 Aug → | ||
| 7–13 | -0.04 | 10% | 19 Aug → | ||
| 13–11 | -0.08 | 13% | 19 Aug → | ||
| 13–8 | -0.00 | 13% | 19 Aug → | ||
| 16–14 | -0.02 | 7% | 18 Aug → | ||
| 13–2 | 0.00 | 20% | 18 Aug → | ||
| 13–9 | -0.03 | 11% | 18 Aug → | ||
| 6–0 | -0.07 | 0% | 18 Aug → | ||
| 12–12 | -0.06 | 11% | 16 Aug → | ||
| 13–6 | 0.00 | 9% | 16 Aug → | ||
| 10–13 | -0.02 | 14% | 9 Aug → | ||
| 1–7 | -0.12 | 0% | 8 Aug → | ||
| 4–13 | -0.06 | 17% | 8 Aug → | ||
| 8–13 | -0.07 | 11% | 8 Aug → | ||
| 12–12 | -0.04 | 12% | 8 Aug → | ||
| 13–7 | 0.02 | 10% | 8 Aug → | ||
| 0–13 | -0.08 | 13% | 5 Aug → | ||
| 1–7 | -0.05 | 12% | 3 Aug → | ||
| 16–13 | 0.07 | 11% | 3 Aug → | ||
| 2–13 | -0.09 | 7% | 2 Aug → | ||
| 10–13 | -0.00 | 7% | 25 Jul → | ||
| 9–13 | -0.05 | 11% | 25 Jul → | ||
| 13–8 | -0.09 | 10% | 21 Jul → | ||
| 10–13 | -0.01 | 10% | 19 Jul → | ||
| 9–13 | 0.01 | 21% | 18 Jul → | ||
| 4–13 | -0.05 | 10% | 18 Jul → | ||
| 7–13 | -0.08 | 8% | 17 Jul → | ||
| 7–13 | -0.09 | 11% | 17 Jul → | ||
| 13–3 | 0.04 | 11% | 17 Jul → | ||
| 13–1 | -0.03 | 6% | 17 Jul → | ||
| 9–13 | -0.02 | 17% | 17 Jul → | ||
| 13–6 | -0.05 | 15% | 17 Jul → | ||
| 3–13 | -0.11 | 13% | 16 Jul → | ||
| 13–7 | -0.06 | 5% | 16 Jul → | ||
| 7–13 | 0.00 | 7% | 16 Jul → | ||
| 3–13 | -0.07 | 2% | 16 Jul → | ||
| 13–10 | -0.02 | 11% | 15 Jul → | ||
| 13–9 | -0.02 | 16% | 15 Jul → | ||
| 4–13 | -0.04 | 8% | 15 Jul → | ||
| 13–6 | -0.02 | 11% | 15 Jul → | ||
| 9–2 | -0.04 | 24% | 14 Jul → | ||
| 8–13 | 0.01 | 12% | 14 Jul → | ||
| 13–6 | 0.00 | 17% | 13 Jul → | ||
| 12–12 | -0.06 | 5% | 9 Jul → | ||
| 9–1 | 0.23 | 17% | 7 Jul → | ||
| 8–1 | 0.08 | 14% | 7 Jul → | ||
| 13–8 | -0.05 | 21% | 7 Jul → | ||
| 13–8 | -0.13 | 5% | 6 Jul → | ||
| 13–11 | -0.07 | 11% | 5 Jul → | ||
| 1–4 | -0.07 | 0% | 5 Jul → | ||
| 7–13 | -0.10 | 8% | 5 Jul → | ||
| 13–11 | -0.06 | 9% | 5 Jul → | ||
| 6–13 | -0.02 | 3% | 5 Jul → | ||
| 12–12 | -0.01 | 13% | 5 Jul → | ||
| 10–13 | -0.05 | 17% | 4 Jul → | ||
| 12–12 | -0.02 | 12% | 4 Jul → | ||
| 9–5 | 0.04 | 0% | 4 Jul → | ||
| 9–13 | 0.05 | 13% | 3 Jul → | ||
| 13–3 | -0.00 | 20% | 3 Jul → | ||
| 9–2 | 0.12 | 37% | 2 Jul → | ||
| 6–9 | -0.18 | 10% | 1 Jul → | ||
| 9–7 | 0.04 | 6% | 1 Jul → | ||
| 3–9 | -0.17 | 20% | 1 Jul → | ||
| 6–13 | -0.03 | 11% | 1 Jul → | ||
| 13–10 | -0.05 | 20% | 1 Jul → | ||
| 2–9 | -0.01 | 29% | 30 Jun → | ||
| 3–13 | -0.08 | 21% | 30 Jun → | ||
| 4–13 | -0.08 | 24% | 30 Jun → | ||
| 1–9 | -0.27 | 20% | 29 Jun → | ||
| 8–8 | -0.02 | 6% | 29 Jun → | ||
| 13–10 | 0.05 | 9% | 29 Jun → | ||
| 9–13 | 0.01 | 5% | 28 Jun → | ||
| 9–7 | 0.04 | 5% | 28 Jun → | ||
| 13–4 | -0.02 | 0% | 28 Jun → | ||
| 13–10 | -0.07 | 11% | 27 Jun → |
Match data via Leetify.