Identify MLS teams
using AI
Below is a free classifier to identify MLS teams. Just upload your image, and our AI will predict the winning MLS team for this season - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("mls-teams", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/mls-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/mls-teams/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the winning MLS team for this season.
This pretrained image model uses a Nyckel-created dataset and has 32 labels, including Atlanta, Austin, Chicago, Colorado, Columbus, Crew, Dynamo, Earthquakes, Fc Dallas and Fire.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the winning MLS team for this season).
Whether you're just curious or building MLS teams detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify MLS teams at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Team Performance Analysis: The false image classification function can be used to analyze team performance by identifying whether images incorrectly representing teams are being circulated. By addressing these discrepancies, organizations can ensure that fans and analysts are accessing accurate representations of team activity, which plays a crucial role in building fan loyalty and engagement.
- Marketing Campaign Verification: In marketing campaigns, teams can utilize this function to verify the authenticity of images being used in promotions. By ensuring that only valid team images are utilized, businesses can maintain brand integrity and avoid misleading fans or potential customers.
- Social Media Monitoring: This function can assist in monitoring social media platforms for false representations of a team's branding or logo. By identifying and flagging these images, organizations can take corrective actions to protect their brand and engage with fans more effectively through accurate visuals.
- E-commerce Brand Protection: For merchandise sales, the false image classification function can be implemented to scan product images to ensure only authorized team merchandise is displayed. This helps in combating counterfeit goods and protecting brand reputation, thereby enhancing customer trust and reducing losses.
- Fan Engagement Initiatives: Teams can leverage the image classification function to engage with fans by promoting accurate imagery of their players and events. By ensuring the correct representation of team images, organizations can create a more authentic and engaging fan experience, solidifying loyalty and passion.
- Visual Content Moderation: Organizations can use this function to moderate user-generated content related to the team across platforms, ensuring that false or misleading images do not proliferate. This helps maintain a positive online community and enhances the overall image of the team among fans and sponsors.
- Sponsorship Compliance Checks: The function can be employed to verify that images used in sponsorship materials align with contractual obligations regarding logo and branding usage. By ensuring compliance with such agreements, teams can avoid legal issues and maintain strong relationships with sponsors, maximizing promotional opportunities.