jac — CS2 Stats
76561198833765117[U:1:873499389]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +10pp win rate · -0.01 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 68% playstyle similarity
Most alike: positioning profile, opening-duel success.
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
Reaction time. 653ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 62% 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 2.7/10 (Learning), 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
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 |
|---|---|---|---|---|---|
| B | 17 | 9–8 | 53% | -0.01 | |
| D | 15 | 5–10 | 33% | 0.01 | |
| B | 15 | 7–8 | 47% | -0.02 | |
| B | 13 | 6–7 | 46% | 0.00 | |
| C | 13 | 5–8 | 38% | -0.02 | |
| C | 12 | 5–7 | 42% | -0.02 | |
| S | 6 | 4–2 | 67% | -0.02 | |
| — | 4 | 3–1 | 75% | -0.01 | |
| — | 1 | 0–1 | 0% | -0.04 | |
| golden | — | 1 | 1–0 | 100% | -0.04 |
| — | 1 | 1–0 | 100% | 0.03 | |
| palacio | — | 1 | 0–1 | 0% | -0.01 |
| office | — | 1 | 0–1 | 0% | -0.09 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Anubis | 84 | 62% | 1.08 | 16.2 |
| Ancient | 71 | 46% | 0.79 | 14.3 |
| Nuke | 63 | 54% | 0.91 | 15.4 |
| Mirage | 55 | 45% | 0.84 | 14.7 |
| Overpass | 33 | 39% | 0.88 | 13.2 |
| Inferno | 23 | 22% | 0.80 | 15.2 |
| Train | 15 | 60% | 1.07 | 17.3 |
| Vertigo | 12 | 58% | 0.93 | 19.2 |
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 12.5191° — 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 0.252 — 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.
33% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 6–13 | -0.04 | 25% | 22 May → | ||
| 13–6 | 0.10 | 21% | 21 May → | ||
| 13–9 | -0.04 | 13% | 18 May → | ||
| 11–13 | -0.01 | 15% | 18 May → | ||
| 16–14 | 0.08 | 19% | 8 May → | ||
| 13–10 | 0.00 | 26% | 4 May → | ||
| 2–13 | -0.04 | 23% | 4 May → | ||
| 8–13 | -0.05 | 13% | 2 May → | ||
| 2–13 | -0.09 | 13% | 21 Apr → | ||
| 13–11 | -0.00 | 16% | 18 Apr → | ||
| 13–6 | -0.02 | 20% | 12 Apr → | ||
| 5–13 | -0.02 | 13% | 9 Apr → | ||
| 1–13 | -0.06 | 19% | 9 Apr → | ||
| 3–13 | 0.01 | 19% | 7 Apr → | ||
| 5–13 | -0.05 | 12% | 30 Mar → | ||
| 10–13 | -0.01 | 21% | 25 Mar → | ||
| 13–9 | 0.07 | 18% | 25 Mar → | ||
| 13–10 | 0.06 | 22% | 25 Mar → | ||
| 13–11 | -0.03 | 19% | 25 Mar → | ||
| 6–13 | 0.00 | 12% | 18 Mar → | ||
| 13–11 | -0.01 | 37% | 18 Mar → | ||
| 13–6 | -0.01 | 13% | 18 Mar → | ||
| 8–13 | 0.02 | 23% | 14 Mar → | ||
| 2–13 | -0.06 | 12% | 26 Feb → | ||
| 2–13 | -0.05 | 36% | 17 Feb → | ||
| 16–14 | -0.02 | 26% | 14 Feb → | ||
| 5–13 | 0.04 | 24% | 11 Feb → | ||
| 10–13 | -0.06 | 24% | 5 Feb → | ||
| 13–7 | -0.02 | 18% | 5 Feb → | ||
| 8–13 | -0.04 | 26% | 1 Feb → | ||
| 8–13 | -0.03 | 22% | 29 Jan → | ||
| 9–13 | -0.01 | 23% | 20 Jan → | ||
| 13–6 | 0.04 | 22% | 17 Dec → | ||
| 7–13 | -0.02 | 20% | 3 Dec → | ||
| golden | 13–5 | -0.04 | 18% | 30 Nov → | |
| 13–7 | 0.03 | 28% | 30 Nov → | ||
| palacio | 10–13 | -0.01 | 14% | 30 Nov → | |
| 13–5 | 0.02 | 11% | 30 Nov → | ||
| 8–13 | 0.02 | 17% | 18 Nov → | ||
| 8–13 | -0.07 | 14% | 23 Oct → | ||
| 4–13 | -0.05 | 19% | 16 Oct → | ||
| 13–5 | -0.08 | 28% | 16 Oct → | ||
| 13–8 | 0.01 | 21% | 16 Oct → | ||
| 8–13 | -0.03 | 25% | 12 Oct → | ||
| 13–11 | -0.04 | 31% | 12 Oct → | ||
| 10–13 | -0.05 | 55% | 5 Oct → | ||
| 13–9 | 0.04 | 12% | 14 Sept → | ||
| 12–16 | -0.04 | 16% | 1 Sept → | ||
| 13–9 | 0.01 | 13% | 26 Aug → | ||
| 9–13 | 0.02 | 15% | 23 Aug → | ||
| 13–9 | -0.04 | 19% | 23 Aug → | ||
| 13–9 | 0.03 | 15% | 21 Aug → | ||
| 13–9 | -0.03 | 14% | 19 Aug → | ||
| 2–13 | -0.01 | 17% | 12 Aug → | ||
| 13–10 | -0.04 | 12% | 29 Jul → | ||
| 13–10 | -0.01 | 19% | 24 Jul → | ||
| 5–13 | -0.06 | 17% | 17 Jul → | ||
| 11–13 | -0.01 | 26% | 15 Jul → | ||
| 11–13 | -0.02 | 21% | 12 Jul → | ||
| 13–11 | 0.02 | 25% | 11 Jul → | ||
| 6–13 | -0.06 | 45% | 6 Jul → | ||
| 16–14 | 0.12 | 26% | 21 Jun → | ||
| 11–13 | 0.00 | 11% | 19 Jun → | ||
| 13–8 | -0.02 | 20% | 19 Jun → | ||
| 16–12 | -0.03 | 15% | 14 Jun → | ||
| 14–16 | -0.01 | 13% | 13 Jun → | ||
| 9–13 | 0.05 | 30% | 13 Jun → | ||
| 9–13 | 0.01 | 12% | 13 Jun → | ||
| 11–13 | 0.01 | 18% | 13 Jun → | ||
| 7–13 | 0.01 | 13% | 8 Jun → | ||
| 13–6 | -0.03 | 11% | 8 Jun → | ||
| 3–13 | -0.00 | 12% | 8 Jun → | ||
| 13–7 | 0.02 | 32% | 7 Jun → | ||
| 8–13 | -0.02 | 15% | 4 Jun → | ||
| 14–16 | -0.04 | 9% | 4 Jun → | ||
| 9–13 | -0.04 | 14% | 25 May → | ||
| 9–13 | -0.00 | 19% | 25 May → | ||
| 13–10 | -0.02 | 15% | 25 May → | ||
| 10–1 | 0.01 | 4% | 25 May → | ||
| 13–10 | -0.06 | 9% | 25 May → | ||
| 13–4 | 0.04 | 27% | 25 May → | ||
| 11–4 | -0.04 | 9% | 24 May → | ||
| 13–10 | -0.04 | 21% | 22 May → | ||
| 6–13 | -0.07 | 24% | 20 May → | ||
| 14–16 | -0.00 | 19% | 16 May → | ||
| 11–13 | -0.02 | 19% | 15 May → | ||
| 13–10 | -0.02 | 24% | 15 May → | ||
| 10–4 | 0.05 | 31% | 15 May → | ||
| 5–13 | 0.01 | 30% | 9 May → | ||
| 8–13 | -0.04 | 18% | 8 May → | ||
| 13–3 | -0.00 | 18% | 8 May → | ||
| 13–8 | -0.05 | 10% | 4 May → | ||
| 13–2 | 0.01 | 26% | 4 May → | ||
| 13–6 | 0.01 | 19% | 4 May → | ||
| 5–13 | -0.05 | 14% | 4 May → | ||
| office | 9–13 | -0.09 | 20% | 3 May → | |
| 4–13 | -0.05 | 13% | 3 May → | ||
| 13–8 | 0.01 | 26% | 3 May → | ||
| 11–13 | 0.00 | 12% | 3 May → | ||
| 11–13 | -0.06 | 23% | 2 May → |
Match data via Leetify.
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