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Full Breakdown: Four-star SF Dennis Parker, Jr.

On3 imageby:Jamie Shaw10/25/22

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2023 4-star Dennis Parker, Jr. (photo cred- Jamie Shaw)

Four-star Dennis Parker, Jr. is set to announce his commitment on Wednesday, October 26. The small forward published his final three schools as Oklahoma State, Georgetown, and NC State.

The 6-foot-7 Parker averaged 13.0 points, 4.3 rebounds, and 3.3 steals in leading his Team Loaded Va to the Adidas 3SSB Circuit championship game this July.

Parker, who is No. 59 in the updated 2023 On3 150, has taken official visits to all three of his finalists; Georgetown on August 26, Oklahoma State on September 3, and NC State on September 9.

Two-way presence

Dennis Parker, Jr. is a connective-type wing. He does the tough-guy stuff on the floor that help a team win a game. On the defensive end, Parker is very instinctive in the passing lanes. These instincts are where a lot of his production comes from.

Parker has long arms with good anticipation. He plays with a toughness and aggression off the ball on the defensive end. Parker’s foot speed can be a tick slow guarding on the ball, but there is intrigue with him playing as a switchable four-man.

During Adidas 3SSB Championship week, Parker’s primary cover scored 0.571 points per possession, which graded him in the 58th percentile among his peers. He also averaged 3.3 steals per game over the week.

His frame

Dennis Parker has a basketball player’s frame. At 6-foot-7, he has broad shoulders with long arms, very projectable once he gets into a college strength and conditioning program.

Parker is an above-average athlete. A lot of his production comes from his strength and toughness. It will be interesting to see how he is used positionally at the next level. The small ball four, the switchable forward, has a lot of value in today’s basketball.

How does Parker score?

A lot of Parker’s points come in transition. Playing aggressively in the passing lanes, he turns a lot of defense into offense and stretches his legs when filling the lanes. In transition, Parker attacks the front of the rim with a purpose and with balance.

The jump shot is streaky. He shoots it with good balance, but his release is inconsistent, getting a different spin on different shots. Parker can shoot a two-dribble pull-up with confidence, especially going left. Parker lacks blow-by speed off the bounce. At this point, playing as a wing in the half-court, things can become inefficient. Parker shot 24.5 percent from three through 17 games on the Adidas 3SSB Circuit this summer.

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However, Parker is a smart cutter off the ball. He finishes well around the basket, absorbing contact and getting to the free-throw line. He does a good job getting downhill off of ball reversal in straight lines. Parker shot 52.4 percent from two during Adidas 3SSB championship week.

In Parker’s words

“My decision is going to come down to where I fit best,” Parker told On3. “Which school has the best plan for me, and where I can achieve my dreams? What school is going to let me play and be the best version of myself?

“I want to go somewhere where I can make an impact as a freshman. A place where the coach lets me make mistakes and learn from them instead of just getting yanked out of the game and getting benched for the rest of the game. I want to go someplace where I can be the best player I am, and they can create me and let me be the best man I can possibly be.”

On3s Recruiting Prediction Machine

Dennis Parker, Jr. will announce his college decision on October 26. The final three schools he is choosing between are NC State, Georgetown, and Oklahoma State.

On3s Recruiting Prediction Machine (RPM) gives NC State a 37.2 percent chance of landing the four-star wing. RPM says Georgetown has a 19.8 percent chance, and Oklahoma State has a 17.8 percent chance.

The On3 engineering group teamed up with Spiny.ai to create RPM, the industry’s first algorithm and machine learning-based product to predict where athletes will attend college. Starting from the ground up, On3 built an entirely new product that utilizes data, human expertise, and machine learning.