Intars Dzintars

Intars Dzintars — CS2 Stats

76561198882109766[U:1:921844038]Steam profile ↗✓ No bans

675Tracked matches50%Win rate2021Tracked since
CSDB Rating6.9 SolidAll-Rounder
FaceitLevel 6Top 54.0% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 18,197 -295 27 May – 16 Jan · 30 days played
17,03819,999peak 19,99927 May16 Jan
19,999Peak Premier in tracked matches
50Days played since 2025-05-27

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

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CSDB.GGIntars DzintarsFACEITLevel 6STANDINGTop 54.0% of rankedcsdb.gg/stats

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Performance scores

Aim81
Positioning62
Utility57

0–100 skill scores via Leetify.

Recent form

STEADY50–45–5Last 10050%Win rateLLLWTWWWLW

Last 10 vs previous 10: +10pp win rate · +0.03 avg rating · +7.9pp headshot accuracy · −56ms 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

  • 1–3–1 · 20% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 32%
  • Avg reaction 589ms

Last 10

  • 5–4–1 · 50% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 30%
  • Avg reaction 616ms

Last 20

  • 9–10–1 · 45% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 26%
  • Avg reaction 643ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim8.1
Utility5.7
Positioning6.2
Opening Duels6.6
Clutch4.8

Excellent 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.

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

m0NESY

Plays most like m0NESY 93% playstyle similarity

Most alike: utility contribution, aim profile.

Where you differ: lower positioning profile; lower opening-duel success.

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

Preaim. Mechanical aim is strong but the crosshair sits 11.3° off target when enemies appear — placement, not flicking, is the bigger win available.

Reaction time. 664ms 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

Aim8.1
Positioning6.2
Utility5.7
Mechanics8.6
Opening Duels5.5
Win Impact5.0

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

Match rating0.04+0.01
first ⅓ avg 0.03 → last ⅓ avg 0.04
Reaction time672ms−4ms
first ⅓ avg 676ms → last ⅓ avg 672ms
Headshot accuracy24.3%+0.9%
first ⅓ avg 23.4% → last ⅓ avg 24.3%

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

0.16Best match rating · 13–3 · inferno, 10 Sept →
43%Best headshot accuracy · 9–13 · dust2, 10 Jun →
469msFastest reaction time · 13–9 · ancient, 23 May →
13–1Biggest win · dust2, 30 May →

Across the last 100 tracked matches.

Highlights

7Longest win streak
L3Current streak
7–7In matches decided by ≤2 rounds
12Overtime games

Map breakdown

infernoBest map · 85% over 13anubisWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
dust2B2512–1348%0.04
ancientB179–853%0.03
mirageC156–940%0.03
nukeC145–936%0.02
infernoS1311–285%0.04
overpassA74–357%0.03
anubisD62–433%0.05
train—21–150%-0.03
palacio—10–10%-0.01

Across the last 100 tracked matches.

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

Faceit stats

Combat

89Matches
57%Win rate
1.65Avg K/D
109.9ADR
53%Headshot %

Clutches & streaks

44%1v1 clutch win
34%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Vertigo2162%1.7223.1
Ancient1573%1.6920.9
Mirage1450%1.8320.9
Anubis1369%1.7621.5
Inferno1242%1.5419.8
Nuke540%1.1420.8
Dust2250%1.4423.5

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.

24.4%Headshot accuracy
38.8%Accuracy (enemy spotted)
41.3%Spray accuracy
88.8%Counter-strafing
11.3°Preaim
664msReaction time
49.0%T opening success
55.1%CT opening success
0.53Enemies flashed / flash
10.0%Flash assists
7.70HE damage / grenade
8.94Flashes / match

Recommended for you

Spend your practice time on Anubis

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.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient9–130.0534%29 Aug →
dust29–130.0543%10 Jun →
mirage8–130.0216%23 May →
ancient13–90.0332%23 May →
nuke15–150.0133%22 May →
anubis13–20.0830%22 May →
nuke13–70.0425%10 May →
mirage13–20.0727%25 Apr →
anubis9–130.0428%15 Mar →
dust213–50.0931%15 Mar →
mirage16–140.0127%15 Mar →
mirage8–130.0520%15 Mar →
dust26–13-0.0218%16 Jan →
nuke13–40.0716%16 Jan →
overpass13–40.0219%15 Jan →
nuke8–130.0131%14 Jan →
mirage6–13-0.0124%14 Jan →
mirage13–50.0824%14 Jan →
nuke5–13-0.0510%14 Jan →
inferno4–130.0032%10 Jan →
ancient13–80.1518%10 Jan →
mirage7–130.0730%10 Jan →
mirage9–130.0129%9 Jan →
dust211–130.0416%9 Jan →
dust213–90.0230%3 Dec →
nuke10–130.0524%3 Dec →
dust213–30.0417%26 Nov →
inferno13–10-0.0416%25 Nov →
inferno13–110.0315%23 Nov →
ancient15–150.0716%17 Nov →
dust213–70.0813%17 Nov →
ancient11–130.0123%10 Nov →
inferno13–90.0535%10 Nov →
overpass4–13-0.0323%10 Nov →
ancient13–110.0628%25 Oct →
dust212–120.0725%25 Oct →
nuke13–3-0.0139%23 Oct →
palacio12–12-0.0116%23 Oct →
ancient11–130.0225%26 Sept →
dust213–80.0820%26 Sept →
nuke9–13-0.0020%26 Sept →
overpass9–130.0022%25 Sept →
overpass11–130.0314%25 Sept →
ancient4–13-0.0317%20 Sept →
nuke9–130.0321%13 Sept →
mirage10–13-0.0419%12 Sept →
inferno13–30.1636%10 Sept →
dust28–13-0.0118%10 Sept →
nuke16–140.0125%9 Sept →
nuke9–130.1022%9 Sept →
dust22–13-0.1041%9 Sept →
overpass13–80.0930%7 Sept →
dust213–70.0838%6 Sept →
mirage13–6-0.0124%6 Sept →
inferno13–100.0820%4 Sept →
ancient13–80.0923%4 Sept →
dust213–90.0528%4 Sept →
inferno13–90.0522%3 Sept →
mirage14–160.0623%3 Sept →
overpass13–70.0222%2 Sept →
train13–11-0.0619%2 Sept →
overpass13–80.0727%2 Sept →
nuke16–14-0.0223%2 Sept →
inferno10–130.0226%2 Sept →
dust24–13-0.0313%1 Sept →
dust29–130.0226%1 Sept →
anubis6–130.0922%31 Aug →
dust213–110.0427%31 Aug →
mirage2–13-0.0120%31 Aug →
dust213–9-0.0127%27 Jun →
dust212–120.0618%26 Jun →
ancient16–120.0318%24 Jun →
anubis6–13-0.0124%24 Jun →
inferno13–7-0.0234%23 Jun →
inferno13–90.0713%18 Jun →
mirage13–80.0638%18 Jun →
ancient13–4-0.0424%18 Jun →
inferno13–70.0535%18 Jun →
ancient5–130.0212%15 Jun →
dust213–80.0517%15 Jun →
ancient10–13-0.0019%15 Jun →
mirage9–130.0320%13 Jun →
inferno13–90.0524%7 Jun →
inferno13–40.0636%6 Jun →
nuke12–160.0119%6 Jun →
nuke7–130.0421%6 Jun →
anubis13–60.0413%5 Jun →
anubis4–130.0619%5 Jun →
mirage13–60.0826%5 Jun →
ancient13–60.1221%2 Jun →
dust213–80.0615%2 Jun →
train12–16-0.0120%1 Jun →
ancient13–90.0241%30 May →
dust213–10.1333%30 May →
ancient13–70.0225%30 May →
dust212–160.0423%29 May →
ancient6–13-0.0521%28 May →
dust211–130.0523%28 May →
dust214–16-0.0217%28 May →
dust212–160.0327%27 May →

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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