Ik Sandhu Hunda Si is the latest Punjabi movie of Gippy Grewal. It also features Neha Sharma, Roshan Prince, Babbal Rai and Vikramjeet Virk in main roles. Though, it being a action-drama Punjabi film, the movie has a lot of audience. Thus, Ik Sandhu Hunda Si Box Office Collection is provided here. The movie has released yesterday and 1st day collection of ISHS is estimated around Rs. 1.5 Cr on domestic screens. Also, Ik Sandhu Hunda Si 2nd Day Box Office Collection is predicted about Rs. 1.2 Cr
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Ik Sandhu Hunda Si Box Office Collection | 2 Days Business
Ik Sandhu Hunda Si is one of the new Punjabi movies that are much awaited and have great craze among the audience. Also, Canada and Australia are the great market place for Pollywood industry. As, Punjabi films do a great box office business in overseas too. Thus, Worldwide Collection of Ik Sandhu Hunda Si will be great to see. Well, exact figures are yet to come, but Ik Sandhu Hunda Si total box office collection in 2 days is predicted around Rs. 3 Cr (including overseas income). Rakesh Mehta’s directorial ISHS movie budget is reported about Rs. 8 Cr (approximately).
Ik Sandhu Hunda Si 2nd Day Box Office Collection | New Punjabi Movies Collection
Ik Sandhu Hunda Si second day box office business may get some hike due to audience good words of mouth. List of movies doesn’t stop here, as, list of upcoming Punjabi movies also keeps Chal Mera Putt 2 and Yaar Anmulle Returns in the queue. Ik Sandhu Hunda Si movie reviews are also quite good. This shows that Gippy Grewal’s Ik Sandhu Hunda Si Box Office Collection may break his previous movies collection record.
Ik Sandhu Hunda Si Worldwide Collection
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To know the 1st weekend movie earnings of Ik Sandhu Hunda Si at Pollywood Box Office, stay tuned with us. For regular updates about Pollywood Box Office Collection, follow us on social networks and stay tuned with us at boxofficecollection2020.com
Disclaimer: The Box office data is gathered from various sources and research. These collection figures are approximate and we do not claim the authenticity of the data.