Last Matches
| Date | Teams | ELO | Score |
|---|---|---|---|
|
01/04/26
|
1134 -19923 +18 |
1 2 |
|
|
01/04/26
|
889 -12893 +11 |
0 1 |
|
|
01/04/26
|
1231 +81139 -9 |
2 0 |
|
|
01/04/26
|
925 +14996 -25 |
1 0 |
|
|
01/04/26
|
1203 -131188 +12 |
1 2 |
|
|
01/04/26
|
1133 -151235 +8 |
0 2 |
|
|
01/04/26
|
1087 +4841 -5 |
2 1 |
|
|
01/04/26
|
978 -12980 +15 |
1 2 |
|
|
01/04/26
|
880 +171038 -29 |
2 1 |
|
|
01/04/26
|
1162 +81072 -9 |
2 0 |
|
|
01/04/26
|
1318 -161225 +15 |
1 2 |
|
|
01/04/26
|
1168 -181009 +17 |
1 2 |
|
|
01/04/26
|
1009 +6854 -7 |
2 0 |
|
|
01/04/26
|
1088 -191116 +11 |
1 2 |
|
|
01/04/26
|
954 -11986 +18 |
1 2 |
|
|
01/04/26
|
1010 +8791 -6 |
2 1 |
|
|
01/04/26
|
1066 -111115 +10 |
0 2 |
|
|
01/04/26
|
918 -111048 +12 |
0 2 |
|
|
01/04/26
|
1213 -101280 +9 |
1 2 |
|
|
01/04/26
|
1037 -23999 +17 |
0 2 |
Top 20 Teams
| # | Name | ELO | Matches |
|---|---|---|---|
|
1
|
1600
|
207
|
|
|
2
|
1439
|
220
|
|
|
3
|
1411
|
196
|
|
|
4
|
1406
|
221
|
|
|
5
|
1396
|
202
|
|
|
6
|
1392
|
246
|
|
|
7
|
1363
|
249
|
|
|
8
|
1346
|
277
|
|
|
9
|
1329
|
299
|
|
|
10
|
1302
|
367
|
|
|
11
|
1298
|
230
|
|
|
12
|
1292
|
222
|
|
|
13
|
1289
|
305
|
|
|
14
|
1277
|
294
|
|
|
15
|
1269
|
84
|
|
|
16
|
1264
|
295
|
|
|
17
|
1250
|
293
|
|
|
18
|
1249
|
58
|
|
|
19
|
1244
|
392
|
|
|
20
|
1243
|
156
|
ELO Clarity Powered by Data Accuracy
CS ELO Analyzer is a comprehensive web application designed for the analysis of competitive matches played in Counter-Strike 2, utilizing data sourced from HLTV. Our platform employs advanced algorithms to compute and adjust the ELO ratings of teams based solely on match results, reflecting a classic ELO system similar to that used in chess, but specifically tailored for the dynamics of CS2.
28126
Total Matches
08/05/2023
First Match Date
2016
Total Teams
01/04/2026
Last Match Date
How It Works:
Match Analysis
We gather data on numerous matches, including team performances and match outcomes. This comprehensive data allows us to create a reliable framework for analysis.
ELO Calculation
Using adapted formulas that consider the unique aspects of Counter-Strike gameplay, we calculate ELO ratings for each team. These formulas account for factors such as the relative strength of the teams involved, the match result, and the historical performance of the teams.
Dynamic Updates
As new matches are played, ELO ratings are automatically updated to reflect the latest performance metrics. This ensures that users have access to the most current and accurate team rankings.
Predictive Analytics
Our platform leverages artificial intelligence to forecast outcomes of upcoming matches based on several factors, including team ratings, current form, historical matchups, and other relevant statistics. This predictive model enhances strategic decision-making for fans and analysts alike.
User-Friendly Interface
Our web application offers an intuitive interface that displays the latest match results, top teams, and comprehensive statistics, making it easy to navigate and find the necessary information.