FAQ

FREQUENTLY ASKED QUESTIONS (NO ONE EVER ASKED)

Where are you from?

Poland

not yet

What's the purpose of creating this site?

I used to play a lot of Counter-Strike back then. However, I was bad af so I decided to focus more on programming. As part of my learning path, I decided to create something related to my previous hobby.

What is Balance?

Balance is information on how much ELO you gained or lost within the last 20 matches.

What does the OTHERS filter do?

The OTHERS filter shows Walkovers, as well as some special matches that were played on FACEIT, such as BLAST.

What is the Analyzer feature for?

The Analyzer feature was designed to enhance your experience during pre-match map banning. It calculates and displays statistics from the current map pool, allowing you to exclude individual players from calculations to see how team statistics change without them. Additionally, I developed a formula to identify the best map picks for your team. The best pick represents the most advantageous map to play against your opponents, ranked from left to right. It’s not perfect, and neither is, but it can give you a solid starting point when you’re stuck on which map to ban.

Why does the last 20 section in the Analyzer display more than 100 combined matches?

This happens when one of the players has played a BO3 match within their last 20 games.

Where can I report a bug?

Should you encounter any issues on this page, please leave a comment under my steam profile. Your feedback is widely appreciated.

How to contact with you?

For business inquiries please contact me via Twitter

How are best map picks calculated?

Yes. I developed a formula to determine which map yields the highest winning percentage. This is called pure dedication. However, "developed" word is pretty exaggerated in that case. Basically all I did was to put wages on the following factors:

1. Overall quantity of matches played on the map - 0.785

2. Overall Win Ratio % on the map - 0.105

3. Overall K/D on the map - 0.05

4. Overall K/R on the map - 0.05

5. Last 20 quantity of matches on the map - 0.0030

6. Last 20 Win Ratio on the map - 0.0030

7. Last 20 K/D on the map - 0.0020

8. Last 20 K/R on the map - 0.0020

Before applying the final formula, we need to normalize the data to rescale it between 0 and 1. For instance, if we have 5,000 matches as the total number of matches played by a team on a single map (summed up), we need to rescale this value to a range between 0 and 1 to make subsequent calculations more manageable. For this task, we use the Min-Max Normalization formula.

Min-Max Normalization Formula:

X_norm = (X - X_min) / (X_max - X_min)

X
is the original value.
X_norm
is the normalized value.
X_min
is the minimum value in the dataset.
X_max
is the maximum value in the dataset.

Here’s how I normalized the data:

1. Overall Matches:

Min: 0

Max: 17000

I assumed that the number of matches played on a single map by a team will not exceed 17000.

2. Win Ratio:

Min: 0

Max: 1

3. Overall K/D:

Min: 0

Max: 3

4. Overall K/R:

Min: 0

Max: 2

5. Last 20 Matches:

Min: 0

Max: 100

6. Last 20 K/D:

Min: 0

Max: 5

7. Last 20 K/R:

Min: 0

Max: 2

8. Last 20 Win Ratio:

Min: 0

Max: 1

Once we have normalized the data, we can use the final formula:

Score Calculation Formula:

SCORE = (0.785 * Normalized Overall Matches) + (0.105 * Normalized Overall WR) + (0.05 * Normalized Overall KR) + (0.05 * Normalized Overall KD) + (0.0030 * Normalized Last20 Quantity Of Matches) + (0.0030 * Normalized Last 20 WR) + (0.0020 * Normalized Last 20 KD) + (0.0020 * Normalized Last 20 KR)

I really like your page. How can I support you?

yes I think sending me your moni is a very good idea since it might allow me to afford and play with a butterfly knife in the future.

plz buy virtual beer: Buy me a beer