Identify esports teams
using AI
Below is a free classifier to identify esports teams. Just upload your image, and our AI will predict what esports team it is - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("esports-teams", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/esports-teams/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_image_url"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_image_url"}' \
https://www.nyckel.com/v1/functions/esports-teams/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict what esports team it is.
This pretrained image model uses a Nyckel-created dataset and has 35 labels, including 100 Thieves, Astralis, Bds Esports, Cloud9, Deathrow Esports, Dignitas, E-Sports, Evil Geniuses, Faze Clan and Fnatic.
We'll also show a confidence score (the higher the number, the more confident the AI model is around what esports team it is).
Whether you're just curious or building esports teams detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify esports teams at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Team Sponsorship Insights: Esports teams often seek sponsors to enhance their financial backing. By utilizing the false image classification function, brands can analyze team images to ensure they align with their values and target demographics before entering sponsorship deals.
- Social Media Content Moderation: Esports organizations maintain active social media presence. This function can automatically filter out inappropriate or false representations of teams in user-uploaded content, ensuring that the team’s online brand remains intact and professional.
- Merchandise Authenticity Verification: With the growing market for esports merchandise, counterfeiting has become a concern. This classification tool can help identify false representations of team logos or merchandise, safeguarding both the team’s intellectual property and fans' investment.
- Event Promotion Analysis: When promoting esports events, it’s crucial to visualize team presence strategically. The identification of esports teams in promotional images can optimize marketing strategies by ensuring appropriate branding, thereby enhancing audience engagement and event turnout.
- Fan Engagement Metrics: Understanding fan interactions with team imagery can provide insights into brand loyalty. By analyzing how often and in what context certain images are shared, organizations can better tailor their engagement strategies to resonate with their audience.
- Content Creation for Marketing: Esports teams create promotional materials for events and sponsorships. This image classification function can be employed to ensure that specific teams are depicted correctly in content, facilitating more effective and accurate marketing campaigns.
- Competitive Advantage Analysis: Teams can monitor how they are depicted in media relative to competitors. By classifying false representations, organizations can take corrective actions to address misportrayals, ensuring they maintain a favorable image compared to rival teams.