I wanted to share a big project of mine that I finished this off-season. I’ve created all-time rosters for every NBA, ABA, and WNBA team along with overall ratings for every player in each league’s history. Players were rated 1-100 using a formula that incorporates career Win Shares, VORP, BPM, MP/G and GP. They were then assigned to the team they accumulated the most win shares with. Players were assigned the position they played the most games at . The NBA rosters are 15-deep at each position, so you can basically divide each franchise up into A, B, and C teams. The ABA teams feature a lot less players, and the WNBA teams aren’t as well-defined by positions, so I created a 15-player roster on the right side that balances the amount of guards and forwards/centers. I hope you all enjoy looking at this as much as I have!
This is going into next season so I’m thinking of regression and progression.
I got my starting centers from ESPN depth chart but I took some liberties for certain ones.
I’m not factoring in potential or contract value so your team’s favorite young player might not be ranked high but that does not mean I don’t like their potential or think they shouldn’t start.
I’m factoring in fit but not that much I’m also factoring in how well they would fit on any team not just a team designed for them to be good at
I value the jobs of a center more than the pluses. Shooting, playmaking are great but not as valuable as interior defense, rebounding and setting screens when it comes to the role of a center. That being said if a center is so good at the the other stuff that I will rank them high
Just because someone is in the same tier does not mean I don’t think one isn’t better than the other
Tier Six Eh: I guess you could plug them in as the starter but it’s probably due to lack of depth on the roster. Very unlikely to be a starter next year
Nic Claxton, Hassan Whiteside, Mason Plumlee, Isaiah Stewart, Alpren Sengun, Thomas Bryant
Five Starters: Definitely starting level talent but below average when compared to other starters more of a role player
Mitchell Robinson, Jakob Poetl, Ivica Zubac, Chet Holmgren, Wendell Carter Jr
Tier Four Good: Pretty Good level centers but not moving the needle, good to have but replaceable
Christian Wood, Nikola Vuecivic, Brook Lopez, Jaren Jackson Jr, Evan Mobley, Jusuf Nurkic, Jonas Valunchunas, Kristaps Porzingis, Myles Turner
Tier Three Great: Not quite the one or two guy pieces but someone is very integral to a team and is a lock for starter
Draymond Green, Robert Williams, Bam Adebeyo, Deandre Ayton, Clint Capela, Jarrett Allen, Domantas Sabonis
Tier Two Amazing: Description: Guys that can be the number two on a championship team
Anthony Davis, Pascal Siakam, Rudy Gobert, Karl Anthony Towns
Tier One Elite: Description: Guys you build your franchise around can lead a team to a championship
Joel Embiid, Nikola Jokic
>In my house yesterday, I moved my wife’s oatmeal to a different cabinet. And she sends me a text, I wasn’t there, she goes ‘where’s my oatmeal…?’
> I go, oh it’s in such-and-such cabinet.
> She just texted me back ‘a very strange decision, very strange.’
>Danny Ainge has moved the game on winning deals… What he got for Gobert, everybody in the league is bitching about, like, ‘Can you believe it? How could they possibly do that?’ I’ve talked to 10 different people who’ve bitched to me about that trade.
Just for fun, I wanted to see how the careers of Mitchell and Melo compared at the time of trade to the Knicks :
Carmelo- Age 27 season
Mitchell- Age 26 season
Carmelo- 3 all stars
Mitchell- 3 all stars
Carmelo- 4 all NBA teams
Mitchell- 0 all NBA teams
Carmelo- 1 conference finals appearance
Mitchell- 0 conference finals appearances
Carmelo- 2 playoff series wins
Mitchell- 2 playoff series wins
Carmelo- 24.8/6/3.1 career average on 45.9/31/80 splits
Mitchell- 23.9/4/4.5 career average on 44/36/83 splits
Carmelo- 24/7/3 playoff average on 42/34/82 splits, 16-30 record in playoffs
Mitchell- 28/4.9/4.7 playoff average on 42/37/86.5 splits, 17-22 record in playoffs
Different eras, different positions, Mitchell with much better playoff splits , but still.
What play, trade, draft pick, or off-court incident changed the trajectory of the NBA *as a whole* the most?
My lean is the coin flip for Kareem. The back to back drafting of Bird and Magic is a big one as well, as they saved the league’s image.
On the court I lean towards the acts of Donaghy. Undermining confidence in officials and exposing real corruption in the officials ranks is a serious issue.
An actual play is tough. Even more iconic plays mostly affect individual legacies and franchise fortunes. I’m having some difficulty thinking of a single play that affected the league as a whole. Maybe the Malice and the Palace due to major suspensions of important players, but it is technically off the court.
I was with everyone when the idea of a “mid-season tournament” was first introduced. It sounded ridiculous. Why would fans care who wins the “Mid-Season Cup” when it has never been established? Why would star players care about $1M or extra draft picks?
That’s when I came up with an idea that would incentivize players, franchises and fans to care about the tournament:
Teams play 36 games from October-December.
These 36 games are **solely** to determine midseason tournament seeding in each conference. Single-elimination midseason tournament is played around Christmas/New Year’s.
Top 24 teams make the tournament. Top 8 teams get a first round bye .
The 6 teams that miss the tournament start January with a 0-18 record. The 8 teams that lose in round 1 start 3-15. The 8 teams that lose in round 2 start 6-12. The 4 teams that lose in round 3 start 9-9. The 2 teams that lose in final four start 12-6. Finally, the midseason championship loser starts 15-3, midseason champion starts 18-0.
This means after the midseason tournament, the standings will be reset and look like this in each conference:
1. 18-0 or 15-3
36 additional games are played in January-April to determine final 54-game record for each team. The first two-way tiebreaker can also be “whoever advanced further in midseason tournament.”
If the league wants to throw in $1M for each winning player, an extra draft pick, or an obscure “midseason trophy” and midseason tournament MVP, so be it. But this proposal IMO at least incentivizes teams to care in October-December. A contending team is going to fight for a top 4 spot in their conference to ensure they don’t end up one bad game away from 3-15, worse teams will fight to avoid 0-18 with a decent shot at 6-12, and with records being only 54 games, three additional wins will be significant to the final standings.
Also, less overall games played.
Seth Partnow is out with his annual NBA tiers:
Here are the top 3 tiers :
* **Tier 1A**: Giannis, Durant, Jokic, Curry
* **Tier 1B**: Embiid, Doncic
* **Tier 1C**: Kawhi, Lebron
* **Tier 2A**: Tatum, Butler
* **Tier 2B**: Davis, Morant, Harden, Trae
* **Tier 2C**: Paul, Lillard, Booker, George, Gobert
* **Tier 3A**: Bam, Brown, Jrue, Middleton, Kyrie
* **Tier 3B**: Beal, DeRozan, Mitchell, Draymond, Murray, Siakam, Shai, LaVine
* **Tier 3C**: Edwards, Simmons, McCollum, JJJ, Towns, Klay, LaMelo, Zion
Here’s Partnow’s methodology:
> To slot players into those tiers, I start, but don’t end with metrics, as I’m trying to identify their impact towards winning for a championship. Some of the major factors considered:
> * I weigh playoff viability and success highly. While regular-season floor-raising matters, lifting a team’s ceiling matters even more.
> * As such, I try to envision that player in the role he would likely play for a contending team. This does lead to some tension when deciding between a top role player and a more middling offensive hub.
> * I consider the whole of a player’s recent career, not just last season. This serves to eliminate, or at least reduce, wild year-to-year swings in player tiering due to factors often outside of a player’s control — changes in role/situation; a period playing through a nagging injury or simply production altered by a lengthy slump or hot streak. Evaluating anyone “in a vacuum” is incredibly difficult, because context plays a large role in performance even for the very top players, but I do my best to smooth that out.
> * Especially for players with long track records, I tend to give the benefit of the doubt for a single season that goes completely off the rails. Yes, this strongly influences where I slotted Kevin Durant.
> * Health is only a factor in cases when a player might be permanently diminished by an injury or is so prone to getting hurt that a team can’t count on them for more than 55 or 60 games a season.
> * I do my best to ignore salary; being overpaid doesn’t make someone a worse player, just a worse trade/cap asset. And I’m tiering players, not ranking assets.
> * Rising second-year players get a small bump in terms of projected improvement from last year, but everyone else is largely “come as you are,” though I try to be aware of signs that a player is on the verge of falling off the steep end of the late-career aging curve.
> * As a final tiebreaker, to reiterate: when in doubt, push them down. While occasionally a team will underestimate the talent on its roster, it is far more common to elide the difference between an All-Star and a superstar. The numerical ranking gap between, just as an example, Devin Booker and Luka Doncic might be around 10 slots, but the difference in impact, especially in the playoffs, is enormous across even small differences at the top of the pyramid.
**AMERICAN FOOTBALL** –
**RUGBY UNION** –
**RUGBY LEAGUE** –
**AUSSIE RULES** –
**WATER POLO** –
A few months ago, I posted something asking the community if they’d be interested in listening to a sports analytics podcast . Since there was a lot of positive responses, I decided to take a leap of faith and start my own podcast. I realized that it might have more reach if it focuses on basketball in general instead of just basketball analytics.
I just released my first episode of the “Shooters Shoot” podcast which is available on both Spotify and Apple Podcasts. It focuses on quick game recaps and some slight analysis of particular NBA games during the week. Was thinking about uploading weekly but could change if the feedback is super positive.
Would love if you all could go give it a listen and provide any positive/negative feedback you have. Hoping I made the right decision and maybe it could even grow into something big! Hope you enjoy!
Hey everyone! I recently started building , a really easy way for software developers to understand video content. We’ve just started to work with quite a few media / sports analytics companies after having primarily focused on other applications like security, supply chain, and general media.
I’m personally a huge basketball fan . I’m just trying to better understand what everyone doing regular number crunching data science on sports wish they had more visibility on. Maybe every time any player did a celebration? Or how fast a player is moving at all times?
Companies like Second Spectrum ) have great examples of what these insights might lead to at a higher level, but I’m curious to understand what basic things you feel like you’re missing information about in sports numbers.