I believe they are looking for someone to replace their previous data scientist, Diana Mu, who left for another job in March after four years with the team.
Last I heard, the Lakers had a 4-person analytics department, which is about an average size for NBA teams.
Oddly, the largest departments seem to belong to some of the worse teams -- Wizards (10), Kings (8), Knicks (8), and OKC (8).
Joined: 24 Dec 2007 Posts: 35854 Location: Santa Clarita, CA (Hell) ->>>>>Ithaca, NY -≥≥≥≥≥Berkeley, CA
Posted: Mon May 09, 2022 12:23 pm Post subject:
How many data scientists does it take to figure out Russell Westbrook is a bad fit? _________________ Damian Lillard shatters Dwight Coward's championship dreams:
I believe they are looking for someone to replace their previous data scientist, Diana Mu, who left for another job in March after four years with the team.
Last I heard, the Lakers had a 4-person analytics department, which is about an average size for NBA teams.
Oddly, the largest departments seem to belong to some of the worse teams -- Wizards (10), Kings (8), Knicks (8), and OKC (8).
Yea, I recall they had created the department a few years ago was it?
I wonder if these just crunch the numbers or actually innovate new ways interpret the data. _________________ 💜💛 🏆 👀 🍖 #18!!!
I believe they are looking for someone to replace their previous data scientist, Diana Mu, who left for another job in March after four years with the team.
Last I heard, the Lakers had a 4-person analytics department, which is about an average size for NBA teams.
Oddly, the largest departments seem to belong to some of the worse teams -- Wizards (10), Kings (8), Knicks (8), and OKC (8).
Data and analytics can only take you so far. It's a copycat league, and teams tend to emulate the Warriors and think 3pt shooting is the magical ingredient to a successful offense. It's way more complicated and nuanced than that. Ironically, teams like the Cavs and Pels found a lot more success using the 90s style, traditional 2 big lineups during the regular season. The teams that play to their personnel have the most success, so getting caught up in analytics can be stressful for the coaches. Not every team needs a Walmart Curry and Kirkland Klay to thrive, although 3pt shooting is an important aspect of the modern game.
Yea, I recall they had created the department a few years ago was it? I wonder if these just crunch the numbers or actually innovate new ways interpret the data.
I believe the Lakers launched their analytics department about a decade ago. I am not sure how anyone on the outside would be able to determine how innovative or successful the department is.
KindCrippler2000 wrote:
Data and analytics can only take you so far. It's a copycat league, and teams tend to emulate the Warriors and think 3pt shooting is the magical ingredient to a successful offense. It's way more complicated and nuanced than that. Ironically, teams like the Cavs and Pels found a lot more success using the 90s style, traditional 2 big lineups during the regular season. The teams that play to their personnel have the most success, so getting caught up in analytics can be stressful for the coaches. Not every team needs a Walmart Curry and Kirkland Klay to thrive, although 3pt shooting is an important aspect of the modern game.
I think very few fans (and very few people) understand what analytics are. People often fall into camps where they dismiss analytics completely or think it's magical.
Analytics is the science of looking for patterns in data to help guide decision-making. Done well, it can suggest courses of actions, but it can't make the decisions for you.
The analytics that fans have access to tend to fairly simplistic, and are not the type of information that NBA teams actually use. This is another factor in why most fans have such little understanding of the topic. Many think analytics is nothing more than PER.
Yea, I recall they had created the department a few years ago was it? I wonder if these just crunch the numbers or actually innovate new ways interpret the data.
I believe the Lakers launched their analytics department about a decade ago. I am not sure how anyone on the outside would be able to determine how innovative or successful the department is.
KindCrippler2000 wrote:
Data and analytics can only take you so far. It's a copycat league, and teams tend to emulate the Warriors and think 3pt shooting is the magical ingredient to a successful offense. It's way more complicated and nuanced than that. Ironically, teams like the Cavs and Pels found a lot more success using the 90s style, traditional 2 big lineups during the regular season. The teams that play to their personnel have the most success, so getting caught up in analytics can be stressful for the coaches. Not every team needs a Walmart Curry and Kirkland Klay to thrive, although 3pt shooting is an important aspect of the modern game.
I think very few fans (and very few people) understand what analytics are. People often fall into camps where they dismiss analytics completely or think it's magical.
Analytics is the science of looking for patterns in data to help guide decision-making. Done well, it can suggest courses of actions, but it can't make the decisions for you.
True, and I'm aware of what it is because my field and line of work involved data, statistics and simulations. It's not something to dismiss, but you can't blindly rely on it either. My argument was that there has to be a middle ground between analytics and natural feel for the game. Predictive value is important, but sometimes outside the box approaches work better. I'm fond of teams that buck the trends by going against analytics and find success. That takes a lot of trial and error, and experimentation. Shane Battier had a popular segment about stopping Kobe through the use of analytics. He talked about areas on the floor where Kobe was weak and he'd desperately try to force him to that spot, but it didn't matter because it's just one aspect of the game. The best usually figure out ways to thrive and adapt.
The analytics that fans have access to tend to fairly simplistic, and are not the type of information that NBA teams actually use. This is another factor in why most fans have such little understanding of the topic. Many think analytics is nothing more than PER.
Yup. My understanding is they produce hundreds of pages on player and team tendencies. They have access to hordes of data and putting it together to make a coherent conclusion is a complex endeavor.
Data and analytics can only take you so far. It's a copycat league, and teams tend to emulate the Warriors and think 3pt shooting is the magical ingredient to a successful offense. It's way more complicated and nuanced than that. Ironically, teams like the Cavs and Pels found a lot more success using the 90s style, traditional 2 big lineups during the regular season. The teams that play to their personnel have the most success, so getting caught up in analytics can be stressful for the coaches. Not every team needs a Walmart Curry and Kirkland Klay to thrive, although 3pt shooting is an important aspect of the modern game.
I think very few fans (and very few people) understand what analytics are. People often fall into camps where they dismiss analytics completely or think it's magical.
In particular, a lot of fans — probably most — don’t understand that analytics and metrics are not the same thing. Metrics are tools that are sometimes used in analytics. As you say, analytics are much broader. _________________ Internet Argument Resolved
I believe they are looking for someone to replace their previous data scientist, Diana Mu, who left for another job in March after four years with the team.
Last I heard, the Lakers had a 4-person analytics department, which is about an average size for NBA teams.
Oddly, the largest departments seem to belong to some of the worse teams -- Wizards (10), Kings (8), Knicks (8), and OKC (8).
Yea, I recall they had created the department a few years ago was it? I wonder if these just crunch the numbers or actually innovate new ways interpret the data.
I believe the Lakers launched their analytics department about a decade ago. I am not sure how anyone on the outside would be able to determine how innovative or successful the department is.
KindCrippler2000 wrote:
Data and analytics can only take you so far. It's a copycat league, and teams tend to emulate the Warriors and think 3pt shooting is the magical ingredient to a successful offense. It's way more complicated and nuanced than that. Ironically, teams like the Cavs and Pels found a lot more success using the 90s style, traditional 2 big lineups during the regular season. The teams that play to their personnel have the most success, so getting caught up in analytics can be stressful for the coaches. Not every team needs a Walmart Curry and Kirkland Klay to thrive, although 3pt shooting is an important aspect of the modern game.
I think very few fans (and very few people) understand what analytics are. People often fall into camps where they dismiss analytics completely or think it's magical.
Analytics is the science of looking for patterns in data to help guide decision-making. Done well, it can suggest courses of actions, but it can't make the decisions for you.
True, and I'm aware of what it is because my field and line of work involved data, statistics and simulations. It's not something to dismiss, but you can't blindly rely on it either. My argument was that there has to be a middle ground between analytics and natural feel for the game. Predictive value is important, but sometimes outside the box approaches work better. I'm fond of teams that buck the trends by going against analytics and find success. That takes a lot of trial and error, and experimentation. Shane Battier had a popular segment about stopping Kobe through the use of analytics. He talked about areas on the floor where Kobe was weak and he'd desperately try to force him to that spot, but it didn't matter because it's just one aspect of the game. The best usually figure out ways to thrive and adapt.
I'm not sure that any team blindly relies on analytics, but it's hard to know exactly how teams incorporate analytics into their decision-making. There are obviously some GMs who have been branded as analytics focused, so they talk about it a lot, but we still don't know how much the analytics factor into their decisions.
Shane Battier is an interesting case. I'm pretty sure he's the only ex player who now heads a analytics department 14
I think very few fans (and very few people) understand what analytics are. People often fall into camps where they dismiss analytics completely or think it's magical.
In particular, a lot of fans — probably most — don’t understand that analytics and metrics are not the same thing. Metrics are tools that are sometimes used in analytics. As you say, analytics are much broader.
Yeah, you often see fans use analytics as a synonym for statistics.
Yea, I recall they had created the department a few years ago was it? I wonder if these just crunch the numbers or actually innovate new ways interpret the data.
I believe the Lakers launched their analytics department about a decade ago. I am not sure how anyone on the outside would be able to determine how innovative or successful the department is.
KindCrippler2000 wrote:
Data and analytics can only take you so far. It's a copycat league, and teams tend to emulate the Warriors and think 3pt shooting is the magical ingredient to a successful offense. It's way more complicated and nuanced than that. Ironically, teams like the Cavs and Pels found a lot more success using the 90s style, traditional 2 big lineups during the regular season. The teams that play to their personnel have the most success, so getting caught up in analytics can be stressful for the coaches. Not every team needs a Walmart Curry and Kirkland Klay to thrive, although 3pt shooting is an important aspect of the modern game.
I think very few fans (and very few people) understand what analytics are. People often fall into camps where they dismiss analytics completely or think it's magical.
Analytics is the science of looking for patterns in data to help guide decision-making. Done well, it can suggest courses of actions, but it can't make the decisions for you.
True, and I'm aware of what it is because my field and line of work involved data, statistics and simulations. It's not something to dismiss, but you can't blindly rely on it either. My argument was that there has to be a middle ground between analytics and natural feel for the game. Predictive value is important, but sometimes outside the box approaches work better. I'm fond of teams that buck the trends by going against analytics and find success. That takes a lot of trial and error, and experimentation. Shane Battier had a popular segment about stopping Kobe through the use of analytics. He talked about areas on the floor where Kobe was weak and he'd desperately try to force him to that spot, but it didn't matter because it's just one aspect of the game. The best usually figure out ways to thrive and adapt.
I'm not sure that any team blindly relies on analytics, but it's hard to know exactly how teams incorporate analytics into their decision-making. There are obviously some GMs who have been branded as analytics focused, so they talk about it a lot, but we still don't know how much the analytics factor into their decisions.
Shane Battier is an interesting case. I'm pretty sure he's the only ex player who now heads a analytics department 14
It's very interesting to watch which teams take the "analytically sound" approach and which ones don't. Watching the Heat-Sixers game last night, it's fairly clear that the Heat were either attacking the paint or taking 3pt shots. It really seemed like Spoelstra instructed them to avoid shots in the midrange area. And that approach makes the most sense, because it is currently the most efficient way to score in the current era while the midrange is not:
Quote:
Mid-range jumpers are anything from about four feet away from the rim all the way to the arc. Knocked down at only 42% they often leave the shooter in poor position to get the rebound, but usually too deep in the floor to quickly get back to defend. Despite the tendency to take closely contested shots, the rate of drawing a foul is negligible. It is possible for shooters to create space between themselves and their defenders to take an open look, often by taking a fadeaway or a floater, both of which can decrease accuracy and foul rate. A mid-range jumper — especially the deeper mid-range shots (taken from about 14 feet and beyond) — is quite risky and unrewarding. These shots combine the worst parts of a shot at the rim and combine them with the worst parts of shooting a three without adding the positive aspects of either shot. It is only worth as much as a layup but knocked down as often as a three. The low percentage combined with its low value defies the risk/reward analysis and makes it statistically the worst shot in basketball. 42% shooting on a shot worth two points results in 0.84 points per shot.
Quote:
In response to analytics, three-point frequency is skyrocketing, and one statistician thinks it could go higher. David Locke, one of the most articulate and outspoken proponents of basketball analytics and shot selection, also has apparent qualms with the mid-range. At length, he has used statistical data to disparage that shot. He has explored the idea of teams shooting well over 50% of their shots from beyond the arc. When asked where the three-point revolution is going, Locke replied, “I think we’re going to 60 to 65 percent of all shots are threes and about 30 percent are at the rim and about 5 percent are mid-range shots.”
Citing the inevitability of defensive adjustments, he immediately adjusted himself saying that maybe we never get that high. But he does maintain that due to improved analysis, teams will continue to increase the number of three-point attempts. This scenario laid out by David Locke would break down to 65/30/5, resulting in 75 threes, 35 rim shots, and 5 mid-range shots per game equating to an average of 147 points per game. This seems to disprove the 40/40/20 rule, and instead indicates that shooting as few mid-range shots as possible — and replacing them with more efficient shots — is the number one way to increase shot selection efficiency and, in turn, total offensive production.
And that's also my biggest problem with it. Taking such a static approach to offensive strategy is doomed to fail, because defensive coverages vary from game to game (zone, rim protectors, etc). For example, Embiid's return played a monumental role in deterring players from the paint. I do think that they should have changed up their strategy a bit. This might have been an instance where the "inefficient" midrange shot would have been useful.
Last edited by KindCrippler2000 on Mon May 09, 2022 4:02 pm; edited 1 time in total
In a related news, the Lakers announced all computers in the organization will be migrating to a new blazingly fast UI: OS/2 Warp.
The coaching staff will also be provided with new Palm Pilots to improve communication within the organization.
Jeanie:
Quote:
"Money is no issue if it's about improving the team and and being at the forefront of technology in the NBA."
_________________ “Properly read, the bible is the most potent force for atheism ever conceived.”
― Isaac Asimov
I’m guessing he/she will be required to do a whole analytics department’s worth of work.
But only if the results go down with the Rambusses
Requirements:
Candidate will conduct analytics on Player performance.
Candidate will track lineup data and provide findings on best starting lineups.
Candidate will provide reports on opponent 24 hours prior to game time.
All reports go to the Data Analytics Department Head (Linda Rambis) and Deputy (Kurt Rambis) for approval.
Joined: 10 Apr 2001 Posts: 65135 Location: Orange County, CA
Posted: Thu May 12, 2022 5:53 pm Post subject:
The analytics would work better if there was a coach that was more strict in specific offensive sets and optimizing PPP by lineup combinations.
But it definitely doesn't seem as necessary on offense. Defensively, on the other hand, I don't think it takes a data scientist to see what works. _________________ Resident Car Nut.
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