James Wiseman, who was acquired by the Detroit Pistons from the Golden State Warriors during the 2022-23 season, is set to make a move to the Indiana Pacers.
According to NBA insider Adrian Wojnarowski, Wiseman has inked a two-year deal with the Pacers.
Wiseman, the second overall pick in the 2020 NBA Draft, brings his talent and potential to Indiana.
Free agent center James Wiseman has agreed on a two-year contract with the Indiana Pacers, sources tell ESPN. Wiseman was the No. 2 overall pick in the 2020 NBA Draft. pic.twitter.com/UBA9Yhlejx
— Adrian Wojnarowski (@wojespn) July 2, 2024
Last season, Wiseman showcased his skills with the Pistons, averaging 7.1 points and 5.3 rebounds in 17.3 minutes per game off the bench.
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You read several articles on how to build a treehouse on a social media platform. This information might be added to a profile to mark your interest in content related to outdoors as well as do-it-yourself guides (with the objective of allowing the personalisation of content, so that for example you are presented with more blog posts and articles on treehouses and wood cabins in the future).
You have viewed three videos on space exploration across different TV apps. An unrelated news platform with which you have had no contact builds a profile based on that viewing behaviour, marking space exploration as a topic of possible interest for other videos.
Content presented to you on this service can be based on your content personalisation profiles, which can reflect your activity on this or other services (for instance, the forms you submit, content you look at), possible interests and personal aspects. This can for example be used to adapt the order in which content is shown to you, so that it is even easier for you to find (non-advertising) content that matches your interests.
Examples:
You read articles on vegetarian food on a social media platform and then use the cooking app of an unrelated company. The profile built about you on the social media platform will be used to present you vegetarian recipes on the welcome screen of the cooking app.
You have viewed three videos about rowing across different websites. An unrelated video sharing platform will recommend five other videos on rowing that may be of interest to you when you use your TV app, based on a profile built about you when you visited those different websites to watch online videos.
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You have clicked on an advertisement about a “black Friday” discount by an online shop on the website of a publisher and purchased a product. Your click will be linked to this purchase. Your interaction and that of other users will be measured to know how many clicks on the ad led to a purchase.
You are one of very few to have clicked on an advertisement about an “international appreciation day” discount by an online gift shop within the app of a publisher. The publisher wants to have reports to understand how often a specific ad placement within the app, and notably the “international appreciation day” ad, has been viewed or clicked by you and other users, in order to help the publisher and its partners (such as agencies) optimise ad placements.
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Examples:
The owner of an online bookstore wants commercial reporting showing the proportion of visitors who consulted and left its site without buying, or consulted and bought the last celebrity autobiography of the month, as well as the average age and the male/female distribution of each category. Data relating to your navigation on its site and to your personal characteristics is then used and combined with other such data to produce these statistics.
An advertiser wants to better understand the type of audience interacting with its adverts. It calls upon a research institute to compare the characteristics of users who interacted with the ad with typical attributes of users of similar platforms, across different devices. This comparison reveals to the advertiser that its ad audience is mainly accessing the adverts through mobile devices and is likely in the 45-60 age range.
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Examples:
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An advertiser is looking for a way to display ads on a new type of consumer device. It collects information regarding the way users interact with this new kind of device to determine whether it can build a new mechanism for displaying advertising on this type of device.
Content presented to you on this service can be based on limited data, such as the website or app you are using, your non-precise location, your device type, or which content you are (or have been) interacting with (for example, to limit the number of times a video or an article is presented to you).
Examples:
A travel magazine has published an article on its website about the new online courses proposed by a language school, to improve travelling experiences abroad. The school’s blog posts are inserted directly at the bottom of the page, and selected on the basis of your non-precise location (for instance, blog posts explaining the course curriculum for different languages than the language of the country you are situated in).
A sports news mobile app has started a new section of articles covering the most recent football games. Each article includes videos hosted by a separate streaming platform showcasing the highlights of each match. If you fast-forward a video, this information may be used to select a shorter video to play next.
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