The NCAA Transfer Portal is armed and operational, and there are lots of athletes whose names are already in it.

If you didn’t already know, new Hog basketball coach Eric Musselman likes transfers. None of Nevada’s top five scorers last season began their careers with the Wolf Pack, and while Musselman’s transfer strategy probably won’t be that extreme in Fayetteville, he’s going to need at least two transfers this off-season just to get enough depth on the floor for next year.

Arkansas is badly in need of an immediately-eligible forward, as the Hogs have just four that are likely capable of major minutes next year: Reggie Chaney, Gabe Osabuohein, Adrio Bailey, and Ethan Henderson. A transfer guard to replace the departed Keyshawn Embery-Simpson would be nice, although this particular spot doesn’t necessarily need to be immediately-eligible.

Several names have been linked to Musselman or the Hogs. Here, we’ll take a look at four of them. We’ll evaluate them using three statistics:

Usage . This stat should be familiar to long-time readers at Arkansas Fight. Usage rate is the percentage of a team’s total possessions that are recorded to that player while they are on the court. As there are always five guys on the floor, the average usage rate over a season is 20% for each team. Players higher than 20% are considered “high usage” while players lower than that are “low usage.” Usage by itself isn’t an indicator of how good a player is, but low-usage players might not be able to maintain the same level of production if their usage goes up. High-usage players often get more efficient when their usage drops.

. This stat should be familiar to long-time readers at Arkansas Fight. Usage rate is the percentage of a team’s total possessions that are recorded to that player while they are on the court. As there are always five guys on the floor, the average usage rate over a season is 20% for each team. Players higher than 20% are considered “high usage” while players lower than that are “low usage.” Usage by itself isn’t an indicator of how good a player is, but low-usage players might not be able to maintain the same level of production if their usage goes up. High-usage players often get more efficient when their usage drops. Offensive/Defensive Rating . I’m using the standard NBA calculation, found here as an insanely complicated formula that takes every little statistic into account. Offensive rating (or offensive efficiency) measures the number of points produced per possession. Note that points produced is not the same as points scored: a player gets a small boost to points produced for dishing out an assist, for example. Grab an offensive rebound and you just produced points... the amount is based on how many the team would be expected to score on the new possession. Turn it over and you lose points... again, the amount is based on how many the team would have been expected to score had there not been a turnover. Defensive efficiency takes all relevant defensive statistics (rebounds, blocks, steals, fouls) and does the same thing. A lower number here is better.

. I’m using the standard NBA calculation, found here as an insanely complicated formula that takes every little statistic into account. Offensive rating (or offensive efficiency) measures the number of points produced per possession. Note that points produced is not the same as points scored: a player gets a small boost to points produced for dishing out an assist, for example. Grab an offensive rebound and you just produced points... the amount is based on how many the team would be expected to score on the new possession. Turn it over and you lose points... again, the amount is based on how many the team would have been expected to score had there not been a turnover. Defensive efficiency takes all relevant defensive statistics (rebounds, blocks, steals, fouls) and does the same thing. A lower number here is better. Win Shares. A player’s “win shares” are the number of a team’s wins their play was responsible for. There are offensive and defensive win shares, and they are added together to find the total. The sum of all players’ win shares should be approximately equal to the team’s total number of wins: in Arkansas’ case, the total team win shares was 18.98, and the Hogs won 18 games. So the statistics indicate that Arkansas played well enough to win about 19 games, and those wins are divded among each player based on their qualifying stats. The (also complicated) formula can be found here.

2018-2019 Advanced Player Stats Player School Usage ORtg DRtg Off_Win_Shares Def_Win_Shares Total_Win_Shares Win_Share_Pct Player School Usage ORtg DRtg Off_Win_Shares Def_Win_Shares Total_Win_Shares Win_Share_Pct Daniel Gafford Arkansas 26.0% 113.422 94.000 3.68 2.11 5.79 30.4% Isaiah Joe Arkansas 21.0% 112.714 101.694 3.08 1.14 4.22 22.2% Mason Jones Arkansas 22.8% 109.517 101.565 2.87 1.13 4.00 21.0% Jalen Harris Arkansas 17.3% 95.943 102.938 0.48 0.96 1.45 7.6% Adrio Bailey Arkansas 17.3% 95.164 98.688 0.20 1.00 1.20 6.3% Reggie Chaney Arkansas 18.7% 94.741 95.821 0.16 1.12 1.28 6.7% Desi Sills Arkansas 17.4% 97.581 104.070 0.38 0.43 0.81 4.3% Keyshawn Embery-Simpson Arkansas 17.3% 88.139 102.183 -0.28 0.50 0.22 1.1% Gabe Osabuohien Arkansas 17.0% 83.525 96.205 -0.69 1.01 0.32 1.7% Ethan Henderson Arkansas 13.8% 85.519 93.391 -0.04 0.12 0.08 0.4% Jahaad Proctor High Point 29.3% 109.746 101.673 3.91 1.19 5.10 35.0% Conor Vanover California 22.3% 103.963 110.333 0.88 -0.11 0.78 24.0% Jazz Johnson Nevada 15.6% 128.279 99.820 3.80 1.33 5.13 14.5% Jordan Brown Nevada 17.7% 95.256 94.958 0.11 0.72 0.83 2.4%

Let’s quickly evaluate the four players I’ve added to the Hogs’ roster, for comparison purposes.