With their roster available, the Washington Wizards continued their scorching shooting of the past several games, and pummeled the shorthanded Portland Trail Blazers, 126-101.

Washington connected on 17-33 from three-point range and finished the game with a 67.7% effective field goal percentage — their 11th best shooting night in franchise history. It pushed to 12th the 67.5% efg they posted against the Golden State Warriors, last night.

On Saturday — just three days ago — the Wizards had a 72.0% efg, which is the second best shooting night in franchise history.

To recap, in the past three games, the Wizards have had the 2nd, 11th and 12th best shooting games in franchise history. Not bad for a week’s work.

Last time these teams got together, Washington built a 20-point first half lead, which they lost (along with the game) in the second half. Tonight, they led by as much as 12 in the first half, never trailed, and made it impossible for Portland to mount a serious comeback by making shots at a preposterous rate.

The Wizards defense was good in the sense that the Trail Blazers missed shots. That’s phrased intentionally because Washington allowed a ton of open and wide-open looks from three and from in close. Portland misfired most of the night, however.

Good Stuff

• In his first game back after missing four with an ankle injury, Kyle Kuzma knocked off some early rust and played great. He knocked down threes — 6-10 — drove aggressively and kept the turnovers to a reasonable level (3 in 36 minutes).
• Kristaps Porzingis scored 28 points on 15 field goal attempts, grabbed 12 rebounds and handed out 5 assists.
• Delon Wright was disruptive with 4 steals in 29 minutes. He also had 6 assists.
• Bradley Beal had a ho-hum game overall, but produced a three-point play at a critical point in the fourth quarter when Portland had cut the lead to 10.
• Wes Unseld Jr.’s offensive system continues to put the Wizards in position to succeed. My favorite set of the night came in the first quarter. Beal and Porzingis set up what looked like a stagger screen pin down for Corey Kispert. Instead of screening, Porzingis took a pass and the fake pin down transformed into a fake dribble handoff. Just as Portland defenders might have been feeling good about blowing up that action, Beal cut back door, Porzingis hit him with the pass, and Beal got a dunk. Every movement on that play was on the coach’s white board first. Great design.
• In just two minutes of garbage time, both Johnny Davis and Quenton Jackson knocked down the first threes of their careers.
• If you have league pass, catch a Trail Blazers game just for the broadcast. Travis Demers (usually their radio guy) was excellent on play-by-play, and they had regular check-ins from analytics insider Corey Jez, who did a superb job of explaining complex data and applying it to the game. Their regular play-by-play person is Kevin Calabro, who’s one of the best in the business. The real treat: Lamar Hurd, who masterfully breaks down Xs and Os in a way that’s both high level and accessible.
• With a series of transactions at the trade deadline, Portland has larded its roster with all-reputation wings. These are guys who have fans who’ve been saying for 2-3-4 years that said wing is great...or soon will be if he could just get away from that idiot coach who inexplicably hates him. The list: Cam Reddish, Matisse Thybulle, Nassir Little and Kevin Knox II. That said, I think collecting all of them isn’t the worst idea. If one or two becomes a rotation player (or better), it’s a positive development for a Portland team that needs an infusion of inexpensive talent and production.

Also, Shaedon Sharpe is ridiculous.

Photo by Amanda Loman/Getty Images

Four Factors

Below are the four factors that decide wins and losses in basketball — shooting (efg), rebounding (offensive rebounds), ball handling (turnovers), fouling (free throws made).

I’ve simplified them a bit. While the factors are usually presented as percentages, I often find the raw numbers more useful when analyzing a single game.

Stats & Metrics

Below are a few performance metrics, including the Player Production Average (PPA) Game Score (very similar to the one I used to call Scoreboard Impact Rating). PPA is my overall production metric, which credits players for things they do that help a team win (scoring, rebounding, playmaking, defending) and dings them for things that hurt (missed shots, turnovers, bad defense, fouls).

Game Score (GmSC) converts individual production into points on the scoreboard. The scale is the same as points and reflects each player’s total contributions for the game. The lowest possible GmSC is zero.

PPA is a per possession metric designed for larger data sets. In small sample sizes, the numbers can get weird. But some readers prefer it, so I’m including PPA scores as well. Reminder: in PPA, 100 is average, higher is better and replacement level is 45. For a single game, replacement level isn’t much use, and I reiterate the caution about small samples producing weird results.

POSS is the number of possessions each player was on the floor in this game.

ORTG = offensive rating, which is points produced per individual possessions x 100. League average last season was 112.0. Points produced is not the same as points scored. It includes the value of assists and offensive rebounds, as well as sharing credit when receiving an assist.

USG = offensive usage rate. Average is 20%.

ORTG and USG are versions of stats created by Wizards assistant coach Dean Oliver and modified slightly by me. ORTG is an efficiency measure that accounts for the value of shooting, offensive rebounds, assists and turnovers. USG includes shooting from the floor and free throw line, offensive rebounds, assists and turnovers.

+PTS = Tentatively dubbed “plus points,” this stat is a measure of the points gained or lost by each player based on their efficiency in this game compared to league average efficiency on the same number of possessions. A player with an offensive rating (points produced per possession x 100) of 100 who uses 20 possessions would produce 20 points. If the league average efficiency is 114, the league — on average — would produced 22.8 points in the same 20 possessions. So, the player in this hypothetical would have a +PTS score of -2.8.

Note: I dropped points scored from the table because a) it’s easily available just about everywhere, and b) there’s a limit to the number of columns I could use in the tables.