Ronnie Bojangles — CS2 Stats
CA76561198238398482[U:1:278132754]Steam profile ↗✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -20pp win rate · -0.05 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Strong CT-side openerLimited 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.
Your pro match

Plays most like ropz 88% playstyle similarity
Most alike: positioning profile, utility contribution.
Where you differ: lower aim profile; higher opening-fight frequency.
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
CT openings. 69% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 69% on CT to 40% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 559ms 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
Composite 6.9/10 (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.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| D | 18 | 6–12 | 33% | -0.01 | |
| S | 13 | 9–4 | 69% | 0.00 | |
| D | 11 | 2–9 | 18% | -0.02 | |
| D | 8 | 2–6 | 25% | 0.00 | |
| B | 8 | 4–4 | 50% | 0.00 | |
| C | 8 | 3–5 | 38% | -0.02 | |
| S | 7 | 7–0 | 100% | 0.03 | |
| A | 7 | 4–3 | 57% | 0.05 | |
| italy | — | 4 | 2–2 | 50% | 0.05 |
| boulder | — | 4 | 4–0 | 100% | 0.07 |
| office | — | 4 | 2–2 | 50% | 0.01 |
| — | 4 | 2–2 | 50% | 0.02 | |
| fachwerk | — | 2 | 2–0 | 100% | 0.06 |
| — | 1 | 0–1 | 0% | -0.02 | |
| shelter | — | 1 | 1–0 | 100% | 0.02 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Anubis 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.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLLWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 32 | 50% | 1.08 | 16.4 |
| Anubis | 13 | 38% | 1.00 | 16.3 |
| Dust2 | 11 | 55% | 1.14 | 17.4 |
| Inferno | 8 | 50% | 1.27 | 16.9 |
| Ancient | 7 | 86% | 1.41 | 15.0 |
| Nuke | 3 | 67% | 1.39 | 16.0 |
| Cache | 2 | 100% | 1.54 | 16.5 |
| Overpass | 1 | 0% | 1.38 | 22.0 |
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.
- 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 0.4122 — 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.
18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| italy | 13–9 | 0.18 | 21% | 11 Aug → | |
| 7–13 | -0.02 | 20% | 10 Aug → | ||
| 13–11 | 0.03 | 24% | 10 Aug → | ||
| 13–7 | 0.00 | 25% | 10 Aug → | ||
| 12–12 | 0.03 | 24% | 10 Aug → | ||
| 13–9 | 0.01 | 17% | 10 Aug → | ||
| 13–10 | 0.01 | 24% | 10 Aug → | ||
| 13–4 | 0.01 | 18% | 10 Aug → | ||
| 13–16 | -0.01 | 12% | 10 Aug → | ||
| 8–1 | -0.06 | 31% | 10 Aug → | ||
| 13–9 | 0.12 | 21% | 10 Aug → | ||
| 13–6 | 0.10 | 17% | 10 Aug → | ||
| 13–0 | 0.08 | 12% | 9 Aug → | ||
| 13–11 | -0.06 | 14% | 6 Aug → | ||
| 13–11 | 0.02 | 13% | 6 Aug → | ||
| italy | 13–9 | 0.03 | 50% | 5 Aug → | |
| 13–4 | 0.18 | 29% | 5 Aug → | ||
| boulder | 13–4 | 0.12 | 23% | 5 Aug → | |
| 13–7 | 0.08 | 21% | 5 Aug → | ||
| italy | 9–13 | 0.06 | 14% | 5 Aug → | |
| 12–12 | 0.04 | 16% | 5 Aug → | ||
| 7–13 | -0.02 | 29% | 5 Aug → | ||
| 8–13 | 0.04 | 13% | 5 Aug → | ||
| 12–12 | 0.03 | 16% | 5 Aug → | ||
| 13–4 | -0.04 | 15% | 5 Aug → | ||
| 10–13 | -0.03 | 20% | 5 Aug → | ||
| 13–6 | -0.02 | 11% | 5 Aug → | ||
| 13–7 | 0.02 | 22% | 5 Aug → | ||
| boulder | 13–11 | 0.10 | 10% | 5 Aug → | |
| office | 13–7 | 0.09 | 18% | 5 Aug → | |
| 13–3 | -0.01 | 28% | 5 Aug → | ||
| 13–8 | -0.02 | 24% | 4 Aug → | ||
| 11–2 | 0.05 | 27% | 4 Aug → | ||
| 13–5 | -0.03 | 10% | 4 Aug → | ||
| fachwerk | 13–10 | 0.06 | 13% | 4 Aug → | |
| 7–13 | 0.01 | 15% | 4 Aug → | ||
| fachwerk | 13–10 | 0.06 | 15% | 4 Aug → | |
| office | 0–13 | -0.10 | 22% | 4 Aug → | |
| office | 13–11 | -0.01 | 20% | 11 Jul → | |
| boulder | 13–9 | -0.04 | 5% | 11 Jul → | |
| 13–1 | -0.01 | 27% | 11 Jul → | ||
| boulder | 13–6 | 0.09 | 15% | 11 Jul → | |
| italy | 5–13 | -0.07 | 18% | 11 Jul → | |
| shelter | 13–6 | 0.02 | 20% | 11 Jul → | |
| 13–6 | -0.03 | 10% | 11 Jul → | ||
| 13–10 | 0.07 | 13% | 6 Jul → | ||
| 7–13 | -0.04 | 23% | 6 Jul → | ||
| 7–13 | 0.00 | 14% | 6 Jul → | ||
| 4–13 | -0.03 | 31% | 6 Jul → | ||
| 8–13 | -0.07 | 14% | 6 Jul → | ||
| 5–13 | -0.08 | 21% | 5 Jul → | ||
| 10–13 | -0.01 | 6% | 5 Jul → | ||
| 3–13 | -0.10 | 11% | 5 Jul → | ||
| 10–13 | -0.01 | 10% | 5 Jul → | ||
| 6–0 | -0.00 | 20% | 5 Jul → | ||
| 11–13 | 0.03 | 15% | 5 Jul → | ||
| 8–13 | -0.03 | 14% | 5 Jul → | ||
| 13–4 | -0.05 | 7% | 5 Jul → | ||
| 15–15 | -0.05 | 9% | 4 Jul → | ||
| 9–13 | 0.01 | 27% | 3 Jul → | ||
| 13–7 | 0.02 | 18% | 3 Jul → | ||
| 7–13 | -0.03 | 29% | 2 Jul → | ||
| 13–4 | 0.15 | 15% | 2 Jul → | ||
| 9–13 | -0.02 | 14% | 2 Jul → | ||
| 8–13 | 0.01 | 14% | 30 Jun → | ||
| 10–13 | 0.07 | 16% | 30 Jun → | ||
| 1–13 | -0.06 | 33% | 30 Jun → | ||
| 4–13 | 0.02 | 30% | 30 Jun → | ||
| 12–16 | 0.03 | 16% | 30 Jun → | ||
| 13–11 | -0.02 | 22% | 30 Jun → | ||
| 9–13 | -0.04 | 18% | 30 Jun → | ||
| 11–13 | 0.02 | 32% | 30 Jun → | ||
| 13–16 | -0.03 | 15% | 29 Jun → | ||
| 5–13 | -0.03 | 29% | 29 Jun → | ||
| 13–6 | 0.02 | 17% | 28 Jun → | ||
| 8–3 | -0.04 | 18% | 28 Jun → | ||
| 13–8 | 0.01 | 29% | 28 Jun → | ||
| 13–7 | 0.03 | 13% | 28 Jun → | ||
| 7–13 | -0.03 | 17% | 28 Jun → | ||
| 6–13 | 0.04 | 9% | 28 Jun → | ||
| 6–13 | 0.02 | 11% | 28 Jun → | ||
| 3–13 | -0.04 | 29% | 28 Jun → | ||
| 13–10 | 0.03 | 23% | 16 Jun → | ||
| 13–3 | 0.03 | 15% | 8 Jun → | ||
| office | 5–13 | 0.07 | 20% | 2 Jun → | |
| 16–13 | -0.01 | 19% | 27 May → | ||
| 16–13 | -0.05 | 13% | 26 May → | ||
| 11–13 | 0.06 | 11% | 26 May → | ||
| 0–2 | -0.03 | 0% | 26 May → | ||
| 9–13 | 0.05 | 21% | 26 May → | ||
| 13–8 | 0.04 | 16% | 26 May → | ||
| 7–13 | -0.03 | 34% | 25 May → | ||
| 8–13 | -0.03 | 16% | 6 May → | ||
| 3–0 | 0.01 | 100% | 6 May → | ||
| 1–13 | -0.04 | 27% | 6 May → | ||
| 10–13 | -0.02 | 32% | 5 May → | ||
| 11–13 | -0.04 | 12% | 5 May → | ||
| 13–1 | 0.02 | 29% | 5 May → | ||
| 8–13 | -0.05 | 14% | 1 May → | ||
| 1–13 | -0.06 | 21% | 1 May → |
Match data via Leetify.