Images of the PSG x Air Jordan 5 Low have emerged

If you purchase an independently reviewed product or service through a link on our website, Footwear News may receive an affiliate commission.

Jordan Brand and Paris Saint-Germain have a new sneaker collaboration on the way.

More footwear news

Sneaker leak social media account @Solebyjc shared images on Instagram of the upcoming PSG x Air Jordan 5 Low, a new colorway of Michael Jordan’s iconic basketball shoe designed in collaboration with the Paris-based football club .

The PSG x Air Jordan 5 Low dons a fairly straightforward color scheme, with Light Gray dressing the majority of the shoe’s suede upper. Adding to the collab look is a special label above the midfoot mesh netting that reads “Paname”, which is Paris’ last name. Additional details include a blue Jumpman logo on the tongue, an orange lace up closure and debossed PSG branding on the heel. Completing the look is a black midsole and translucent outsole.

Jordan Brand announced their partnership with Paris Saint-Germain in September 2018 where they unveiled their first footwear and apparel collection which included new iterations of the popular Air Jordan 5 and Air Jordan 1 High. The duo also previewed an exclusive special friends and family colorway of the Jordan 5 that has not been released to the public.

According to @zSneakerheadz on Instagram, the PSG x Air Jordan 5 Low will release on July 16 at select Jordan Brand retailers for a retail price of $200. As of press time, Jordan Brand has yet to confirm the collaboration’s release.

In Air Jordan News, DJ Khaled has confirmed that his Air Jordan 5 “We The Best” collaboration will be hitting stores in a slew of colorways before the end of the year.

The best of shoe news

Sign up for the FN newsletter. For the latest news, follow us on Facebook, Twitter and Instagram.

Click here to read the full article.

Previous Images of an Edinburgh street photographer from the 1950s and 60s will be on display
Next Progressive compressive detection of large images with multi-scale deep learning reconstruction