Legacy Leagues

OPOY - Tua

Coach Frederick Aura We're ending our regular season tonight.  It’s not gone like I would have liked.  Yeah, we’ve won 15 games.  But we’ve lost 14.  Worse, we’re stuck in the bottom half of the conference standings with a 7 and 10 record.  We had 2 season-long injuries, but I can’t blame our record on that. If you look at our team stats, they’re pretty much average and about the same as our opponents.  But that’s merely reflective of our overall near .500 record.  We don’t have any individual stars.  Craig Smith is our leading scorer (11.3 ppg) and rebounder (6.9 rpg).  Melvin Steele and Nick McPherson have combined to do a pretty good job at C.  Our perimeter players have been adequate but haven’t provided the production we need from those positions. Tonight the Charleston Cougars are visiting.  They are right below us in the conference standings with a 6-11 record and have only won 7 of the 28 games they’ve played throughout the season.  But they whipped us by 19 points when we played them earlier this season on their court.  The Cougars leading scorer is SF Lee Read who is averaging 11.5 ppg.  He scored 15 against us earlier this season, so I’m hopeful we can limit him. I’m starting 4 seniors, Holmes at PG, Evans at SG, Settles at SF, and Smith at PF, tonight since this will be their final home game for us.  But our two regular starters (Ryan Taylor at SG and Eric Shannon at SF) will get their normal minutes. So here’s how the game went: We started out 1 for 7 from the field and fell behind 9-2.  The Cougars’ C Mike Patterson scored 13 of Charleston’s first 15 points.  At that point we trail by 10 and have hit just 2 of 14 FG attempts.  Midway through the half we finally woke up and began cutting into their lead.  With 5 minutes remaining we went ahead 25-23 on a dunk by Melvin Steele.  We continued to play well and took a 42-32 halftime lead.  We raised our FG shooting to 45%.  We forced Charleston to make 10 turnovers.  SF Matt Settles scored 11 to lead us offensively. Defense predominated early in the 2nd half.  Midway through the half we were up by 13.  The Cougars made a few mini runs to give us a scare but we were able to pull away again each time.  We finished with a 76-60 victory that improved our conference record to 8-10 to place us in a tie with Elon for 6th place.  We held an advantage in most team stats, but most importantly we made just 12 turnovers while Charleston had 21. PF Craig Smith dropped in 16 points and had 8 rebounds.  SG Ryan Taylor also scored 16, SF Eric Shannon had 11, and PG Ryan Holmes hit for 10. Yeah, this is me trying to help our guys find tha basket:

Northwestern State Demons | Team 2 Episode 8: And a Stumble "We are at Northwestern State at this stage of our journeyman save.  We have completed a stellar first season.  We had a nice run last episode, can it continue this go-round?  Follow along and we’d appreciate a Like and a Subscribe."

Tim Moungey Wolverine Studios Community Manager What Do Those Advanced Basketball Stats Mean, Anyway? Sports metrics and measures of analysis have made dramatic improvements over the last decade or so. We’re now able to better pinpoint from a statistical perspective just how good a given player or team actually is. Here at Wolverine Studios, we keep current on the latest models and advanced statistics and find ways to integrate them into our games. But that can often lead to confusion from people who aren’t as familiar with the latest trends. What’s Offensive Rating?, they ask, and what does that stat tell me about my team and players? Consequently, we thought it’d be a good idea to talk about some of the advanced stats for one of our flagship games, Draft Day Sports: Pro Basketball – specifically, explaining what they measure and how you can use them as a gauge. Offensive Rating, Defensive Rating, and Net Rating The brainchild of statistician Dean Oliver, Offensive Rating, Defensive Rating, and Net Rating mark one of the biggest leaps forward in terms of understanding how both players and teams perform on those respective sides of the ball. Offensive Rating Team We won’t delve into the mathematical formulas here, as they can be rather eye-glazing and don’t address what you want to know. But simply put, a team’s Offensive Rating measures how many points a team scores per 100 possessions. Player As you might expect from the above, a player’s Offensive Rating measures how many points that individual scores per 100 possessions. The higher the offensive rating, the better the number, obviously. So what’s a good offensive rating? That depends. For the last two seasons, the average NBA offensive rating has been 110.4, according to Basketball Reference. In the early 2000s – before today’s perimeter-oriented offense, it ranged from 103-106. However, take note of any time a player, team, or lineup has an Offensive Rating below 100. That means they’re scoring less than a point per possession. That’s not very efficient usage at all. Defensive Rating Team As you can probably guess, Defensive Rating looks at how many points a team gives up per 100 possessions – or the opposite of what Offensive Rating measures. Player Similar to what we’ve already seen, a player’s Defensive Rating tells us how many points a player surrenders per 100 possessions. Completely opposite to Offensive Rating, you want the Defensive Rating for both your team and players to be as low as possible. Don’t be surprised if a player has an average Defensive Rating over 100, though – only 30 people in NBA history have ever achieved a Defensive Rating under 100. Net Rating Simply, net rating is the difference between Offensive Rating and Defensive Rating. A positive number is good; a negative number bad. Let’s take a look at some of the lineup data from a save to see how this is displayed in DDS:PB. Our in-game lineup tracking lets you easily see what the good (and bad) rotations areAs you can see, the team’s most used lineup and third-most used lineup are playing very well, and there’s a potential Death Lineup (h/t to the Golden State Warriors for introducing this to our basketball vocabulary) at the bottom of the screen. Excellent net ratings all around. Where there’s an issue? The second-most used lineup. That’s a horrible Net Rating. And although we haven’t shown you the full screen, it’s clear from looking at the aggregate lineup data that Mike Berry and Jason Minor on the court together is the issue – every single lineup involving that pair has a negative Net Rating, regardless of who else is with them. Effective Field Goal %, True Shooting %, and Usage Rate The days when Field Goal Percentage and 3 Point Percentage were the best measurements of a player’s offensive efficiency have been dead since the 1990’s. We now have Effective Field Goal %, True Shooting %, and Usage Rate, which paint a far more clear picture of just how good a player is on the offensive end. Effective Field Goal % The math here is simple enough – (Field Goals + 0.5* Three Pointers)/Field Goal Attempts. What EFG % has over plain FG% is that it takes into account the fact that three-pointers are worth more on the stat sheet than two-pointers. So you could, for example, have a player who attempts 10 field goals inside the arc and makes 4 of them. You could have another player who attempts 10 field goals behind the arc and makes 4 of those. On the stat sheet, the FG % will be 40% for both. But the EFG will be 40% for Player A, and 60% for Player B. That’s a massive 20% difference. What qualifies as a good Effective Field Goal percentage will, like everything else, depend on your league. In the early 2000s, the league average was around 47-48%. In today’s NBA, the average is 52.4%. Averaging them, you can use 50% as a ballpark measure. True Shooting % So what’s missing from Effective Field Goal %? That’s right – free throws. True Shooting % (TS %) rectifies that. The formula is Total Points Scored/(2*(Field Goal Attempts + 0.44 * Free Throw Attempts). As a rule of thumb, True Shooting of 50% is average, 55% is excellent, and above 60% is world-class efficiency. To gain a complete measure of how good a shooter a player is, it’s best to take into account both their Effective Field Goal % and their True Shooting %. Usage Rate The calculation is incredibly lengthy, so we’ll simplify it for you.Usage Rate establishes what percentage of a team’s plays a given player was involved in that resulted in one of the following: a field goal attempt, a free throw attempt, or a turnover. An average usage rate is around 20%, which is logical – 100% Usage available, divided by five players on the court = 20% usage per player – everything be equal. Where this matters in DDS:PB terms: You want your most effective players, as measured by Effective Field Goal and True Shooting percentages, to have the highest Usage Rates to maximize your team’s offensive efficiency. Let’s look at the same team from earlier to see an example. DDS: Pro Basketball 2020 is full of advanced stats to help you make decisionsGreat news here from the team’s perspective – Kendall Dallas  has the highest True Shooting and Effective Field Goal percentage *and* the highest Usage Rate. No wonder this squad went 48-34 this season. Dennis Sanchez, on the other hand, looks terrible from those metrics. But that’s why he’s only played in 3 games this season. The staff knows he’s a poor performer in their setup. As you can see from that screen, there’s more advanced stats we could talk about, but we’ll reserve those for another post. We hope you’ve found this information helpful. To check out a free demo of Draft Day Sports: Pro Basketball or any of other sports simulations, go here. The post Understanding Advanced Stats appeared first on Wolverine Studios. View the full article