theo

theo — CS2 Stats

NO76561199172979795[U:1:1212714067]Steam profile ↗✓ No bans

725Tracked matches59%Win rate2021Tracked since
CSDB Rating6.5 SolidPositional Player
FaceitLevel 7Top 42.3% of ranked FACEIT players
WingmanGold Nova II
Ladder ranks via Leetify

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CSDB.GGtheoFACEITLevel 7STANDINGTop 42.3% of rankedcsdb.gg/stats

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Performance scores

Aim79
Positioning66
Utility28

0–100 skill scores via Leetify.

Recent form

STEADY48–50–2Last 10048%Win rateLWWLLLWLWW

Last 10 vs previous 10: +10pp win rate · +0.06 avg rating · −0.5pp headshot accuracy · −131ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 28%
  • Avg reaction 556ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 29%
  • Avg reaction 590ms

Last 20

  • 9–9–2 · 45% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 29%
  • Avg reaction 655ms

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 (+2.3 against its own average).

Aim7.9
Utility2.8
Positioning6.6
Opening Duels4.4
Clutch3.6

Limited 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

donk

Plays most like donk 87% playstyle similarity

Most alike: positioning profile, aim 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

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 655ms 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

Aim7.9
Positioning6.6
Utility2.8
Mechanics7.9
Opening Duels4.2
Win Impact7.9

Composite 6.5/10 (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

Match rating-0.01−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time678ms+73ms
first ⅓ avg 605ms → last ⅓ avg 678ms
Headshot accuracy26.4%−1.6%
first ⅓ avg 28.0% → last ⅓ avg 26.4%

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

0.18Best match rating · 9–5 · inferno, 16 Jul →
65%Best headshot accuracy · 10–13 · mirage, 20 Dec →
469msFastest reaction time · 13–3 · cache_b, 16 Jan →
13–0Biggest win · mirage, 21 Dec →

Across the last 100 tracked matches.

Highlights

4Longest win streak
8–11In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 70% over 10nukeWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
infernoB2311–1248%-0.00
mirageC145–936%-0.01
dust2C146–843%0.00
anubisS107–370%-0.01
ancientB105–550%-0.01
cache_bB105–550%0.00
nukeD62–433%0.03
vertigo—42–250%0.02
cache—32–167%-0.02
sanctum—21–150%-0.02
train—22–0100%0.03
poseidon—10–10%-0.11
overpass—10–10%0.05

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

268Matches
49%Win rate
1.11Avg K/D
73.9ADR
56%Headshot %

Clutches & streaks

38%1v1 clutch win
21%1v2 clutch win
5Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage5744%1.0414.6
Anubis5646%1.1516.4
Ancient4255%1.2016.4
Inferno3847%1.1316.1
Dust23751%1.2015.3
Nuke1771%1.3118.1
Cache540%0.7112.4
Overpass333%0.9316.3

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.

27.6%Headshot accuracy
34.5%Accuracy (enemy spotted)
37.1%Spray accuracy
85.5%Counter-strafing
9.4°Preaim
655msReaction time
45.1%T opening success
48.7%CT opening success
0.47Enemies flashed / flash
3.4%Flash assists
5.65HE damage / grenade
2.04Flashes / match

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.

  1. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4678 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Nuke

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 6 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo5–13-0.0334%15 Sept →
anubis19–160.0020%5 Sept →
anubis13–9-0.0130%18 Aug →
anubis11–13-0.0332%18 Jul →
cache8–130.0121%17 Jul →
mirage2–13-0.0125%17 Jul →
inferno13–11-0.0129%17 Jul →
dust29–13-0.0423%16 Jul →
ancient13–100.0534%16 Jul →
inferno9–50.1839%16 Jul →
nuke15–150.0039%16 Jul →
inferno11–130.0425%12 Jul →
dust213–8-0.0233%9 May →
cache13–9-0.0538%9 May →
cache13–3-0.0235%8 May →
poseidon4–9-0.1138%12 Apr →
inferno4–9-0.218%12 Apr →
inferno4–9-0.119%10 Apr →
inferno8–8-0.0336%10 Apr →
inferno9–6-0.0330%10 Apr →
inferno9–4-0.0114%10 Apr →
anubis13–110.0113%6 Apr →
ancient16–120.0825%5 Apr →
cache_b1–8-0.0229%5 Apr →
mirage13–7-0.0527%31 Mar →
inferno10–13-0.0022%31 Mar →
dust213–60.0929%30 Mar →
ancient13–3-0.0221%22 Mar →
inferno16–140.0220%20 Mar →
nuke2–130.0622%7 Mar →
overpass11–130.0521%6 Mar →
mirage13–7-0.0323%6 Mar →
ancient10–13-0.0523%26 Feb →
anubis13–6-0.0338%25 Feb →
mirage13–4-0.0528%25 Feb →
dust210–30.0732%15 Feb →
sanctum3–9-0.0638%14 Feb →
anubis9–130.0642%14 Feb →
sanctum9–20.0241%14 Feb →
mirage3–13-0.0637%13 Feb →
dust28–13-0.0321%27 Jan →
nuke13–100.0737%18 Jan →
inferno13–80.0219%18 Jan →
inferno7–130.0127%18 Jan →
dust214–160.0043%16 Jan →
cache_b13–30.0020%16 Jan →
dust213–4-0.0224%16 Jan →
vertigo11–13-0.0524%15 Jan →
dust24–13-0.0414%15 Jan →
mirage13–110.0036%3 Jan →
dust26–13-0.0134%3 Jan →
dust213–110.0130%2 Jan →
cache_b8–13-0.0315%2 Jan →
mirage20–220.0431%2 Jan →
cache_b16–14-0.0223%1 Jan →
nuke16–120.0231%29 Dec →
cache_b13–60.0537%29 Dec →
inferno13–40.1026%29 Dec →
mirage11–13-0.0619%26 Dec →
inferno11–13-0.0719%26 Dec →
mirage10–130.0229%26 Dec →
inferno6–13-0.0325%23 Dec →
anubis13–100.0132%23 Dec →
dust23–13-0.0817%21 Dec →
mirage4–130.0328%21 Dec →
anubis13–30.0135%21 Dec →
dust24–130.0224%21 Dec →
cache_b13–110.0239%21 Dec →
dust28–13-0.0030%21 Dec →
mirage13–00.0863%21 Dec →
mirage10–130.0165%20 Dec →
vertigo13–50.0727%20 Dec →
inferno7–13-0.0211%10 Dec →
inferno13–40.0441%6 Dec →
anubis2–1-0.090%6 Dec →
ancient13–3-0.0217%6 Dec →
ancient9–130.0018%6 Dec →
cache_b8–13-0.0028%5 Dec →
mirage7–13-0.039%5 Dec →
inferno2–13-0.0515%4 Dec →
inferno5–130.0437%29 Nov →
nuke6–13-0.0428%29 Nov →
cache_b10–130.0232%29 Nov →
train13–80.0520%29 Nov →
nuke2–130.0329%28 Nov →
ancient13–6-0.0521%28 Nov →
inferno13–8-0.0121%28 Nov →
inferno11–130.0634%27 Nov →
ancient10–13-0.0422%27 Nov →
train13–80.0141%27 Nov →
dust213–60.0842%23 Nov →
inferno13–9-0.0326%22 Nov →
mirage14–16-0.0123%21 Nov →
vertigo13–50.0819%21 Nov →
cache_b19–160.0623%20 Nov →
inferno13–60.0521%20 Nov →
ancient14–160.0234%14 Nov →
cache_b1–13-0.0423%14 Nov →
anubis2–13-0.0736%9 Nov →
ancient9–13-0.0429%5 Nov →

Match data via Leetify.

Recent teammates

Milestones

500 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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