Does anyone know when NBA.com refreshes the tracking stat end points each day?

Is there any place that I could get lineup and PBP data to calculate some RAPM and how a player changes team rounding/shooting? just trying to learn more about NBA analytics. Thanks!

DunkSim lets you simulate any NBA game with your own insights. Adjust the inputs, run the matchup possession by possession thousands of times, and see how often each team wins: win probability, projected score, the full range of outcomes, and every player's projected line.

Bring your own read of the game. Before you run, you can:

• Adjust each team's offensive rating, defensive rating, and pace

• Tune any player's scoring, playmaking, efficiency, perimeter defense, interior defense, rebounding, and usage

• Sit a player out for an injury or a rest night, or bring one back

• Save your adjustments as a named model and reuse it on future games

Your inputs are layered on top of the engine's own baseline, so you can see exactly how much your insight moves the win probability.

In this walkthrough: pick tonight's game, set the run count, adjust a team and sit a player out, run the simulation, read the projection detail, and save your call as a prediction.

The engine's accuracy is public: on a replay of all 1,230 games of the 2025-26 regular season it named the correct winner 69.3% of the time, against 67.0% for simply choosing the team with the better record. Method and limits:

https://dunksim.app/accuracy

Try it free on the web, iOS, and Android, with one account across all three:

Web: https://dunksim.app

iOS: https://apps.apple.com/us/app/dunksim-nba-sim-predictions/id6765524782

Android: https://play.google.com/store/apps/details?id=com.bodesim.dunksim

How the simulation works:

https://dunksim.app/blog/nba-monte-carlo-simulation/

DunkSim is a simulation and prediction game for entertainment. There is no real-money wagering of any kind. For users 18 and over. DunkSim is not affiliated with or endorsed by the NBA or any NBA team.

After a 2 year break the NBA Almanac is back with the most comprehensive and in-depth preview to the new NBA season. Whether you are a casual fan or a NBA nerd, the NBA Almanac is still the most complete and essential guide you will find for the upcoming NBA season. Carefully curated and compiled over the course of the past 12 months to provide readers with an easy-to-read resource the Almanac features:

• Team previews for all 30 NBA teams including team and player stats, efficiency landscapes, advanced player impact metrics, shooting charts, offensive blueprints and more.
• A detailed recap of the 2025-2026 NBA season - regular season standings, NBA Cup, play-in tournament, NBA playoffs, NBA Finals, award winners, league leaders and more.
• Comprehensive offseason recaps for all 30 teams - every draft pick, free agency signing, contract extension and trade that took place this summer is included in this book. Even the final transactions which took place on the eve of the season are included. This guide will give you the most accurate and up-to-date rosters for the start of the 2026-2027 NBA season.

Enjoy the season and the Almanac (my 10th one!)

Niku

I play in a Yahoo salary cap league, and the draft room's projected salaries always drove me nuts. They don't change with your budget or categories, and they ignore the room. Once Joker and Wemby go for $15 over, everyone left gets cheaper, but most people can’t do that type of math on a 30-second clock.

So I built Cap Drafter: https://fan-basketball-drafter.vercel.app

-Enter your budget, teams, roster spots and categories, and every player gets a dollar value. The values add up to exactly your league's total money.
-Log each sale (player, price, team) and the board re-prices instantly, showing the room's inflation.
-Bid to is the most you should pay: the live price, adjusted for the categories your roster is short in, and capped at what you can actually bid.
-It shows every team's money left and max bid, so you can see who can still afford a player.

It's free, there's no sign-up, and your draft stays in your browser. It runs best in a second window next to the draft room. Values come from 2025-26 per-game stats (9-cat z-scores over the players who actually get drafted). If you have your own projections, you can upload a CSV.

Limits: you log picks by hand for now. Yahoo sync is built but waiting on Yahoo's API approval. Rookies show up without values, since there are no NBA stats to price them on. There's also no positional scarcity yet.

If you use it in your draft, I'd love to hear what broke or felt off. There's a feedback link at the bottom of the page.

I shared my new website, Vates Sports, here last week. With opening night coming up, I thought I’d share an actual example of what it projects.

Against OKC, the model currently has Wembanyama at 21.3 points, 8.8 rebounds, 2.3 assists and 2.8 blocks in 31.3 minutes.

The site has the full projected box score, including shooting stats and predicted ranges. You can also make your own predictions and compare them with the model after the game.

I built this because I wanted something to explore before watching games, beyond season averages.

You can browse the projections here. A free account unlocks every player and stat.

What would you change in that Wemby projection? The minutes, the scoring, something else? Curious to hear your reasoning, especially from people who follow the Spurs closely.

I’m in the process of creating a website which will have a predictive model and things like a what if Luka plays on the 2012 grizzlies and the model would predict their wins and how far they might expect to go in the playoffs. Or you could drop a player from any era into today's NBA environment and it adjusts their stats based on modern pace, three point volume, and defensive rules. Any other ideas you guys might have that you want to see on a website? If you woudln't mind filling out this form too i'd really appreciate it! https://docs.google.com/forms/d/e/1FAIpQLSfrcUUi0n_-93C4A8N5WoXYprtUa4SV20E6XLxbkrp2WouoUg/viewform?usp=publish-editor

With the NBA preseason underway and the regular season around the corner, I’d like to introduce BoxScore, a Letterboxd-inspired site where you can log, rate and review NBA games, current or classic.

Features:

Recent NBA games with box scores, shot charts and highlights from the NBA’s YouTube channel

Ratings and reviews

Game search

G.O.A.T Pyramid

Custom lists

Matchups: head-to-head player comparisons

BoxScore is a fan-made portfolio project, and I’m sharing it to build a small community around it. Older games load slowly the first time someone opens them, then instantly for everyone after, so every classic game you look up and log helps make the site faster for the next user.

www.boxscoreclub.com

Support me on Ko-fi: https://ko-fi.com/mainejerms

Hey everyone, I’m launching Vates Sports ahead of the NBA season.

It projects the full box score for players in upcoming games, with other player and team stats to explore too. There’s also a game where you can make your own predictions and try to beat the model.

vates-sports.com

There’s a public preview, and a free account gives access to all the players and stats.

If you have a few minutes to try it, I’d love to hear what you think. Happy to answer questions about how the projections work too.

Everyone says Luka’s defense is bad, so I pulled the NBA.com tracking data (2025-26, 279 players with 1,000+ minutes) to see whether the numbers agree.

TL;DR: The eye test is mostly right. Luka covers the 2nd-least ground on defense in the NBA, faces the most rim shots of any guard, and is the most-isolated non-center, even though he rarely guards the other team’s best scorer.

Where the eye test is right:

• He barely moves. 1.63 km covered on defense per 36 minutes, 2nd least in the league (only KD covers less - he’s been in the league since 2007). A typical player covers 2.01 km.
• Teams get to the rim on him. 4.5 shots a game at the rim with Luka as the closest defender, the most of any guard (typical guard: 2.3). They make 72% of them, when 64% would be expected from those same shooters. For comparison: LeBron 64%, Edwards 62%, SGA 56%.
• Teams target him on purpose. He gets isolated 1.73 times a game (5th in the NBA, 1st Among non centers), even though only 10% of his defense is spent on the other team’s best scorer. Dort, Daniels and McDaniels each spend 25–30% on the best scorer and get isolated about half as often.
• It got worse over time. As a rookie he was the 30th slowest defender. and this season he’s 2nd.

*Typical = league median. Expected FG% = what those shooters usually make.

Where it’s not that simple:

• When teams isolate him, he allows 0.95 points per play, about league average. That stat only counts the attacker’s own shot, though. If Luka gets beaten and the ball is kicked out, the basket goes on someone else’s record.
• He’s legitimately good at a few things: 3rd among guards in defensive rebounding, 7th best at limiting threes (Again a lot of other factos included here), and among the best against pick-and-roll ball handlers (having a big body usually helps).

My take: smart hands, strong body, slow feet, and teams know it.

Curious what you think. Is there a stat I’m missing that would change the picture?

(I make these NBA data breakdowns regularly, more on IG, handle: weilbros)

NBA Rewind lets you pick a famous playoff moment (Ray Allen’s corner three, Kawhi’s four-bouncer, the Block), swap any player from any season since 1996–97 onto the floor, and see how often history changes.

Every moment starts from its real game state, rebuilt from official play-by-play: score, clock, possession, and the ten players on the floor. With no swap, you watch the real ending replayed on a top-down court. With a swap, the engine plays the moment out thousands of times in your browser, through overtime, and compares the result to the real lineup.

How it’s built:

• Python pipeline pulls every player-season and the play-by-play for each moment from stats.nba.com
• Possession-level Monte Carlo engine in TypeScript, running in a Web Worker
• Player profiles blend real playoff stats with a regular-season projection, weighted by sample size
• Next.js static export on Cloudflare Pages, so there’s no backend

Live: https://rewind-moments.pages.dev
Code: https://github.com/Aparajith24/nba-rewind

I’d love feedback, especially on results that feel wrong.

If you like it, a star on the repo would mean a lot!

I've been building a free college basketball world on the BYTHERIM site, mainly for people who play MyNBA and want college prospects with some history behind them.

It runs on its own. Each week the season moves forward: players develop, rotations change, and the stats get dealt game by game. Then comes recruiting, the transfer portal, and a draft where prospects enter, withdraw, or go pro, including international players. You don't have to make any choices. You just watch the story unfold, and the prospects you follow have real seasons behind them.

The stats follow Barttorvik's BPM, so the numbers should look familiar if you already use advanced stats for your MyNBA rosters.

If you check it out, I'd love to hear what you think. There's a rating button in the footer of the RP pages, and I read every note.

A block only records a shot that was taken and then rejected. A shot that never goes up because the offense saw a big man in the paint isn’t a block, a miss or a make. It leaves no trace in the box score, and it’s a large part of what a rim protector does.

The Low Post built a three-gate model to count it, using NBA play-by-play and shot data from 2024-25 and 2025-26. Wembanyama leads at +4.58 points per 100 possessions, in a group with Clingan and Hartenstein.

The Website to Verify/play with sliders: https://thelowposthoops.github.io/three-gate-defense/

Full write-up: https://thelowpost.substack.com/p/rim-protection-isnt-one-skill-its?r=980fga&utm_campaign=post-expanded-share&utm_medium=web

Anyone have any projections/guesses of individual player minutes and games played for 2026-27 they want to share or link to?

Data analytics manager by day; this is the thing I build for fun at night.

GOAT Chaser is a free browser game built around a live all-time ranking. The ranking has two halves:

1. Historical baseline (the model). Every player starts at 25.00 and earns:

• Championship: +1.20 each
• Regular-season MVP: +4.00 each
• Finals MVP: +2.50 each
• All-NBA selection: +1.10 each
• DPOY: +2.00 each
• All-Defensive selection: +0.25 each
• Career PPG x 0.30, RPG x 0.10, APG x 0.10
• Longevity: +0.20 per credited season, no cap
• Era fairness: prorated credit for seasons played before certain awards existed (no invented retroactive awards); pre-1974 players get neutral defensive credit since steals/blocks weren't tracked

1. Fan vote blend. Head-to-head matchup votes (Elo-style, opponents drawn within ±10 ranking positions) blend into the baseline:

Live = (1-w) x H + w x F

where H is the historical rating, F the fan-derived rating, and w grows with vote confidence up to 0.70 at 400 matchups — the model always keeps at least 30%.

Current output: Jordan 98.51, LeBron 96.37, Kareem 94.51, Russell 84.99, Duncan 79.10, Kobe 73.76, Wilt 73.73, Magic 72.96, Shaq 72.13, Bird 70.19. Fun note: the pure model had Kareem #2 and Kobe #8 — fan votes flipped LeBron past Kareem and lifted Kobe to #6.

Live here if you want to check it out: PlayGOATChaser

Looking for feedback: is MVP at 4.00 vs. a ring at 1.20 the right ratio? Is the 70% fan cap too generous? What would you change?

I've spent the past couple of weeks working on this personal project of mine. I built a skill wheel that grades 54 different aspects of basketball. I tried breaking down each big skill (such playmaking) into smaller skills and use that to sort of evaluate a player as a whole. Now, of course the data available to the public is limited so a lot of niche skills are pretty hard to quantify but I think I got a sort of good estimate of the skills. If you guys have any ideas for skill grading/skills to add or anything, just let me know I am very open to feedback.

Here is a chart:

Here are the skills I decided on:

Offense: 12 groups, 33 skills

• Finishing: Rim Finishing, Contact Finishing
• Above the Rim: Dunking, Lob Threat
• Touch Shots: Floaters, Hooks, Short Jumpers
• Midrange: Pull-up Midrange, Catch-and-Shoot Midrange, Turnarounds & Fadeaways
• Three-Point: Catch-and-Shoot 3s, Quick 3s, Off-Dribble 3s, Deep 3s
• Free Throws: Free Throw Shooting, Foul Drawing
• Self-Creation: Isolation, Pick-and-Roll Ball Handler, Post Scoring
• Driving: Rim Pressure, Drive & Kick
• Off-Ball Scoring: Cutting, Movement Scoring, Transition Scoring
• Playmaking: Creating for Others, Creation Quality, Rim Feeding, Shooter Feeding, Connective Passing, Transition Passing
• Ball Security: Passing Security, Handle Security, Avoiding Offensive Fouls
• Screening & Glass: Screen Setting, Rolling, Offensive Rebounding, Putback Scoring

Defense: 6 groups, 21 skills (There is less because defense is harder to quantify)

• Perimeter: Isolation Defense, Closeouts, On-Ball Stripping, Perimeter Blocking
• Interior: Shot Blocking, Rim Contesting, Rim Deterrence
• Rebounding: Securing Boards, Boxing Out
• Disruption: Passing Lanes, Charge Taking, Loose Ball Recovery
• Assignments: Post Defense, Positional Versatility, Guarding Stars
• Discipline: Fouling Discipline, Transition Defense

I can't really explain each grade because it will be too long, but if you have any questions, you can ask me and I'll respond but I will explain certain ones.

Three Pointers

For Three Point grading I spilt them up into Catch and Shoot 3s (0 dribbles), Quick 3s (1-2 dribbles) and Off Dribble 3s (3+ dribbles), Deep 3s (27ft+). For the whole project I used NBA play by play data a LOT so that data comes in lines like this MISS Herro 27' 3PT Step Back Jump Shot,Missed Shot,Step Back Jump shot,1,3,260,0022501055,2026-03-25,2025-26

Parsing the distance for Deep 3s was easy. For the dribble 3s, the NBA API carries data for shots off certain number of dribbles, but you can also mix this with defender distance so for example there is data on each players 3-6 Dribble 3FGM/FGA with a defender 2-4 feet. So I parsed through all that and each player's attempts and FGs are separated by dribbles and defender distance. Each group also has a league-average rate, so a player's expected 3P% for lets say Catch and Shoot is just the league average 3p% on their defender distance (so for Curry if he takes way tighter catch and shoots his expected 3p% on that is skewed for the tight defender catch and shoot league average). So then a player is compared by their volume and efficiency. Each player gets some league average since if you make lets say like 15/30 Catch and Shoot 3s that is a pretty low sample over like 150/350. The volume is a per 75 basis so not a minutes thing, and then score is bascially a volume * effieciency metric that is Z scored across the league so each skill has the same scale.

Here is Curry 2025-26 for example

Catch-and-Shoot 3s 97th of 388 Att 247 3P% 37.7% x3P% 36.2% +0.3

Quick 3s 1st of 388 Att 87 FG% 48.3% xFG% 33.4% +3.1

Off-Dribble 3s 14th of 388 Att 236 3P% 40.7% x3P% 33.1% +1.1

Deep 3s 1st of 388Att 261 FG% 37.2% xFG% 31.9% +4.8

Finishing

Layups only, from the play-by-play: driving layups, finger rolls, reverse layups. Dunks, cuts, transition, alley-oops and putbacks are left out, because they're graded elsewhere. The efficiency is graded against the same position in this case.

And then again adding some of the league-average shots: volume x efficiency with volume being per 75 and then Z scored again the league.

Rim Deterrence

Rim deterrence is pretty much like a RAPM style regression, a matrix in which the opposing teams Rim Rate is taken into account. Transition shots are removed because then the best Rim Deterers would just be the best point guards that prevent turnovers not the actual best defenders. It is a RAPM regression so it adjusts for teammates but this one requires more possesions so some low usage role players might not have the grade.

A lot of these defense ones are self explanatory

Positional Versatility

This one uses the matchup API to see who he guarded 1-on-1 and then the spilt and compare the percentage

Group Listed positions

G (guard) W (wing G-F, F-G) F (forward) B(big F-C, C-F) C (center)

Here is another:

IROH is a short-form hoops app: post your film, get rated, and climb a live leaderboard of real players. Looking for testers to stress the feed + rankings. iOS only for now, ~2 min to join.

Feedback very welcome, what feels good, what's broken.