MoDo — CS2 Stats
PROSINNERS EsportsRomaniaAWPerSettings & gear profile →
76561198350221098[U:1:389955370]
Rating over time
Faceit ELO
- At peak — 4,311
- Reached: 4,000 ELO · 3,500 ELO · 3,000 ELO · 2,500 ELO
- 4,000 ELO first seen 2026-08-28
- 3,500 ELO first seen 2026-08-28
CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
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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
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerExcellent counter-strafing
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 s1mple 98% playstyle similarity
Most alike: opening-fight frequency, 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
Strengths
Aim. Aim score of 99 — the mechanical foundation is a clear strength.
CT openings. 67% 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.
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 8.8/10 (Elite), a weighted mean of the bars with a small opposition adjustment (×1.05 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 | 24 | 13–11 | 54% | 0.04 | |
| B | 21 | 10–11 | 48% | 0.03 | |
| C | 16 | 7–9 | 44% | 0.03 | |
| S | 11 | 9–2 | 82% | 0.02 | |
| D | 10 | 3–7 | 30% | 0.00 | |
| A | 10 | 6–4 | 60% | 0.04 | |
| S | 7 | 5–2 | 71% | 0.05 | |
| — | 1 | 0–1 | 0% | 0.02 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 865 | 62% | 1.56 | 20.4 |
| Ancient | 539 | 57% | 1.40 | 18.9 |
| Dust2 | 520 | 62% | 1.62 | 20.6 |
| Anubis | 406 | 57% | 1.53 | 19.2 |
| Nuke | 164 | 60% | 1.44 | 18.7 |
| Inferno | 100 | 66% | 1.69 | 17.7 |
| Overpass | 90 | 57% | 1.47 | 19.1 |
| Vertigo | 90 | 62% | 1.72 | 19.4 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Inventory
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–9 | 0.04 | 46% | 28 Aug → | ||
| 13–3 | 0.09 | 35% | 28 Aug → | ||
| 16–12 | 0.02 | 57% | 23 Aug → | ||
| 13–3 | 0.01 | 44% | 23 Aug → | ||
| 11–13 | 0.02 | 28% | 22 Aug → | ||
| 13–5 | 0.17 | 22% | 16 Aug → | ||
| 4–13 | -0.04 | 25% | 16 Aug → | ||
| 13–6 | 0.14 | 44% | 13 Aug → | ||
| 6–13 | -0.02 | 22% | 9 Aug → | ||
| 19–17 | 0.03 | 18% | 9 Aug → | ||
| 7–13 | 0.03 | 44% | 9 Aug → | ||
| 13–2 | 0.12 | 10% | 8 Aug → | ||
| 13–2 | 0.09 | 28% | 8 Aug → | ||
| 13–2 | 0.09 | 28% | 8 Aug → | ||
| 10–13 | -0.03 | 14% | 8 Aug → | ||
| 0–13 | -0.05 | 22% | 8 Aug → | ||
| 13–3 | 0.02 | 22% | 7 Aug → | ||
| 13–0 | 0.09 | 25% | 7 Aug → | ||
| 13–6 | 0.11 | 33% | 1 Aug → | ||
| 4–13 | -0.01 | 26% | 31 Jul → | ||
| 13–11 | 0.07 | 7% | 27 Jul → | ||
| 3–13 | 0.01 | 38% | 23 Jul → | ||
| 13–6 | 0.04 | 35% | 23 Jul → | ||
| 8–13 | 0.00 | 18% | 23 Jul → | ||
| 8–13 | -0.02 | 32% | 18 Jul → | ||
| 9–13 | 0.13 | 42% | 18 Jul → | ||
| 16–14 | 0.07 | 21% | 18 Jul → | ||
| 13–4 | 0.15 | 24% | 14 Jul → | ||
| 2–13 | -0.03 | 21% | 3 Jul → | ||
| 7–13 | 0.02 | 37% | 3 Jul → | ||
| 2–12 | 0.01 | 19% | 2 Jul → | ||
| 3–2 | -0.03 | 0% | 2 Jul → | ||
| 4–13 | 0.03 | 50% | 1 Jul → | ||
| 13–2 | 0.04 | 28% | 25 Jun → | ||
| 13–9 | 0.09 | 24% | 12 Jun → | ||
| 11–13 | 0.03 | 25% | 5 Jun → | ||
| 10–13 | 0.01 | 22% | 3 Jun → | ||
| 14–16 | 0.02 | 21% | 3 Jun → | ||
| 11–13 | -0.02 | 30% | 2 Jun → | ||
| 6–13 | 0.00 | 21% | 2 Jun → | ||
| 14–16 | 0.04 | 19% | 2 Jun → | ||
| 7–13 | 0.13 | 31% | 23 May → | ||
| 11–13 | 0.07 | 29% | 16 May → | ||
| 13–1 | 0.25 | 38% | 16 May → | ||
| 11–13 | 0.01 | 39% | 13 May → | ||
| 1–8 | -0.02 | 5% | 13 May → | ||
| 6–6 | -0.02 | 29% | 13 May → | ||
| 3–8 | 0.04 | 31% | 13 May → | ||
| 13–8 | 0.03 | 30% | 13 May → | ||
| 13–9 | -0.01 | 67% | 13 May → | ||
| 6–4 | -0.03 | 30% | 13 May → | ||
| 9–13 | -0.07 | 14% | 12 May → | ||
| 7–9 | 0.09 | 18% | 12 May → | ||
| 13–7 | 0.13 | 35% | 11 May → | ||
| 13–3 | -0.01 | 9% | 8 May → | ||
| 17–19 | 0.03 | 33% | 26 Apr → | ||
| 13–10 | 0.01 | 22% | 26 Apr → | ||
| 13–11 | -0.01 | 33% | 26 Apr → | ||
| 13–9 | 0.12 | 20% | 26 Apr → | ||
| 13–11 | 0.02 | 10% | 26 Apr → | ||
| 13–5 | -0.01 | 12% | 25 Apr → | ||
| 13–5 | 0.09 | 8% | 25 Apr → | ||
| 13–16 | -0.04 | 13% | 24 Apr → | ||
| 20–22 | 0.07 | 20% | 24 Apr → | ||
| 5–13 | 0.02 | 42% | 21 Apr → | ||
| 6–13 | -0.05 | 29% | 20 Apr → | ||
| 7–13 | -0.04 | 17% | 20 Apr → | ||
| 13–9 | 0.00 | 18% | 20 Apr → | ||
| 13–3 | 0.08 | 30% | 15 Apr → | ||
| 13–9 | 0.12 | 8% | 13 Apr → | ||
| 13–11 | -0.01 | 26% | 30 Mar → | ||
| 11–13 | 0.02 | 40% | 30 Mar → | ||
| 13–16 | 0.01 | 26% | 30 Mar → | ||
| 16–14 | 0.02 | 26% | 29 Mar → | ||
| 13–11 | 0.00 | 0% | 29 Mar → | ||
| 12–16 | 0.04 | 28% | 29 Mar → | ||
| 13–6 | 0.02 | 13% | 29 Mar → | ||
| 13–2 | 0.04 | 20% | 26 Mar → | ||
| 11–13 | 0.02 | 16% | 26 Mar → | ||
| 13–11 | 0.03 | 14% | 26 Mar → | ||
| 13–4 | 0.01 | 38% | 26 Mar → | ||
| 13–5 | 0.05 | 19% | 26 Mar → | ||
| 5–13 | -0.03 | 0% | 25 Mar → | ||
| 19–17 | 0.02 | 54% | 25 Mar → | ||
| 13–9 | -0.02 | 38% | 25 Mar → | ||
| 13–8 | 0.02 | 19% | 25 Mar → | ||
| 13–6 | 0.03 | 33% | 25 Mar → | ||
| 13–8 | 0.03 | 24% | 22 Mar → | ||
| 13–4 | 0.11 | 57% | 21 Mar → | ||
| 13–5 | 0.15 | 27% | 21 Mar → | ||
| 13–11 | 0.10 | 23% | 19 Mar → | ||
| 9–13 | 0.02 | 35% | 12 Mar → | ||
| 11–13 | -0.00 | 9% | 7 Mar → | ||
| 16–19 | -0.00 | 24% | 7 Mar → | ||
| 19–17 | 0.00 | 9% | 4 Mar → | ||
| 22–20 | 0.03 | 26% | 4 Mar → | ||
| 14–16 | 0.05 | 31% | 3 Mar → | ||
| 8–13 | 0.00 | 38% | 2 Mar → | ||
| 5–13 | -0.04 | 39% | 2 Mar → | ||
| 10–13 | 0.02 | 23% | 27 Feb → |
Match data via Leetify.