You can watch NBA games (and probably some Premier League games) with me on Playback.tv, I will aim to do a stream at least once a week for the rest of the season.

[Here is the link to my Playback room.](https://www.playback.tv/backfirednbapod) This is a really cool platform, so I hope you'll join and watch along with me!

Exciting announcement!!!

The internet has run wild with [this Reddit post](https://old.reddit.com/r/nba/comments/10nbau4/memphis_grizzlies_scorekeeper_posting_fraudulent/), entitled "Memphis Grizzlies scorekeeper posting fraudulent numbers." The post talks about Jaren Jackson Jr.'s home/road splits for steals and blocks, alleging that Jaren does not actually earn a good chunk of the blocks and steals he records at home, calling into question his Defensive Player of the Year candidacy.

That's a strong allegation, but I wanted to check everything out myself before I believed it. **_[Here's a link to a Google Doc](https://docs.google.com/spreadsheets/d/1NqVYtAa_zAJmHajL0A9lB0pAR52rgnB4620oqLMiBmo/edit?usp=sharing) with video links to all of JJJ's blocks and steals._ **In summary, I don't think there's anything malicious here.

# **BLOCKS**
-  91 of Jaren's 103 blocks are 100% accurate.
-  There were 8 I marked as "maybe" where I simply can't tell if Jaren gets a hand on it or not, because the video is too pixelated. I trust that the NBA verified those are true blocks.
-  There were 4 I could not find film for.

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<table class="tableizer-table">
<thead><tr class="tableizer-firstrow"><th></th><th>Yes</th><th>Maybe</th><th>No film</th><th>Grand total</th></tr></thead><tbody>
 <tr><td>Home</td><td>59</td><td>5</td><td>2</td><td>66</td></tr>
 <tr><td>Away</td><td>32</td><td>3</td><td>2</td><td>37</td></tr>
 <tr><td>Total</td><td>91</td><td>8</td><td>4</td><td>103</td></tr>
</tbody></table>


# **STEALS**
- 26 of Jaren's 33 steals are 100% accurate.
- There are 2 that are not steals for Jaren. Both of those steals happened outside of Memphis.
- There were 4 I marked as maybe, but Jaren does have a reasonable claim to them.
- There was 1 I could not find film for.

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	table.tableizer-table {
		font-size: 12px;
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<table class="tableizer-table">
<thead><tr class="tableizer-firstrow"><th></th><th>Yes</th><th>Maybe</th><th>No</th><th>No film</th><th>Grand total</th></tr></thead><tbody>
 <tr><td>Home</td><td>18</td><td>3</td><td>0</td><td>0</td><td>21</td></tr>
 <tr><td>Away</td><td>8</td><td>1</td><td>2</td><td>1</td><td>12</td></tr>
 <tr><td>Total</td><td>26</td><td>4</td><td>2</td><td>1</td><td>33</td></tr>
</tbody></table>

Overall, no, Memphis's scorekeeper is not fraudulently inflating JJJ's blocks and steals. Jaren Jackson Jr., like his team, just plays better at home. The Memphis Grizzlies are extremely good at home this year (20-3) and horrible on the road (11-15).

Verifying Jaren Jackson Jr.'s blocks and steals

large_Screen Shot 2023-01-28 at 11.42.13 AM.png

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small_Screen Shot 2023-01-28 at 11.42.13 AM.png

thumbnail_Screen Shot 2023-01-28 at 11.42.13 AM.png

Screen Shot 2023-01-28 at 11.42.13 AM.png

_Note: For a tutorial on how to pull this data yourself, check out [this post](https://www.backfirednba.com/posts/creating-a-soccer-style-table-for-the-nba)._

Updating the soccer-style NBA table through the games on Thursday, 1/26.

large_NBA EPL Table thru 1:26.jpeg

medium_NBA EPL Table thru 1:26.jpeg

small_NBA EPL Table thru 1:26.jpeg

thumbnail_NBA EPL Table thru 1:26.jpeg

NBA EPL Table thru 1:26.jpeg

NBA Table 1/27/23

I got a wild hair up my ass last night and made a few Pokémon/NBA crossovers after having several successful TikToks about what NBA players would evolve into one another, Pokémon style. Here are the ones I've made so far:

### Pokémon King Version
#### ft. LeBron James as the box legendary
![Pokemon LeBron.jpg](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/Pokemon_Le_Bron_327b8d7d9c.jpg)

I used the Game Boy Color banner on the side even though by the time LeBron James was in the NBA, the Game Boy Advance was in vogue and Pokémon Ruby and Sapphire were already out. The Game Boy Advance banner has a curve to it and as a novice graphic designer, it was too hard to work with. In most ways, though, this one is modeled after Pokémon Ruby's box art.


### Pokémon Hoya [Destroya] Version
#### ft. Patrick Ewing as the box legendary
![NBA Ewing.jpg](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/NBA_Ewing_15e826b3bf.jpg)
 
This one is my favorite one, I really love Patrick Ewing and the New York Knicks teams of the 1990s. This was modeled off of the Pokémon Blue art, which features Blastoise. Blastoise is my favorite Pokémon, so I had to go all-out on this one. I couldn't make "Hoya Destroya" fit in a way that looked good, so I shortened the version nickname to just "Hoya."

### Pokémon Mamba Version
#### ft. Kobe Bryant as the box legendary
![Pokemon Kobe.jpg](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/Pokemon_Kobe_b68417f9f6.jpg)

Originally I was just going to make this one and the MJ one, but I was able to get the process down fairly quickly. This one is modeled off of Pokémon Yellow, but I was able to find a background that had a purplish tint to it that I felt fit the Los Angeles Lakers and Kobe Bryant. 
I might make another one of these with Frobe/#8 on it instead to fully fit the 90s theme.

### Pokémon GOAT Version
#### ft. Michael Jordan as the box legendary
![Pokemon MJ.jpg](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/Pokemon_MJ_b2457caf11.jpg)

This one is modeled off of Pokémon Red. I wanted to keep it pretty simple and just have a flame-and-black background to go with the red-and-black jersey that Michael Jordan is wearing. The base set Charizard card (below) and Jordan are icons of the 1990s.

![charizard_cropped.jpg](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/charizard_cropped_00be4ac898.jpg)

Pokémon/NBA crossover box art

Right before the season began, on the episode of my podcast about [big Vegas underachievers (episode 24)](https://www.backfirednba.com/episodes/24), I made some predictions for the current NBA season. Let's see how I've done so far.

# Award picks

Here were my award picks from the episode:
- MVP: **Joel Embiid**
I thought Embiid would be able to close the gap after receiving 26 first-place votes to  Jokić's 65 last season, but Jokić is having anoter spectacular season, so he may 3-peat as MVP. I did also consider Luka Dončić as an option for this, and per [RotoWire](https://www.rotowire.com/betting/nba/mvp-odds.php), he is the current favorite.

- Finals MVP, **Giannis Antetokounmpo**
Right now, it doesn't look like the Bucks will win the title, so this is wide open. They are 4-6 in their last 10 games, but I'm sure they'll break out of this slump.

- Rookie of the Year, **Paolo Banchero**
Paolo is a lock for Rookie of the Year barring injury. 

- Most Improved Player, **James Wiseman**
NOPE! (This was a homer pick— I did some work for the Memphis Tigers the season that he was briefly on the team.) Shai Gilgeous-Alexander currently leads the field.

- Coach of the Year, **JB Bickerstaff**
The Cavaliers are great, but Jacque Vaughn and Joe Mazzulla are currently in the lead.

- 6th Man of the Year, **Jordan Poole**
In a normal season, Poole would be running away with this because he's averaging 20 points per game, but the Lakers' recent success with Russell Westbrook coming off the bench has Westbrook taking a lead over Poole.

- Defensive Player of the Year, **Bam Adebayo**
Bam's certainly not having a bad season on the defensive end, but this award is Jaren Jackson, Jr.'s to lose right now and Brook Lopez's to gain. That's about it.

So, I'm going to give myself a 1.5 out of 7 on that one, the half-point being Poole's since he actually has a shot to win it still. I'm not very good at this, huh?

-------

# Over/unders

Here were my over/under picks and notes for why I was making that pick:

> Boston Celtics, 53.5, under - too much unknown about this team to say they’re going to be the top seed in the league

I stand by the reasoning for this pick (Robert Williams III's injury and the Udoka/Mazzulla situation), but the Celtics will probably go over. **0/1**

> Milwaukee Bucks, 52.5, over - even with the Middleton injury I think Giannis is going to drag them to 56 wins

Maybe not 56, but it does look like this will be a slight over as of right now. **1/2**

>LA Clippers, 52.5, under - load management, I see high 40s for them

Mid-to-low 40s is probably closer to the truth, since they're 22-21 right now. Kawhi has played 19 games so far and Paul George has played 30. **2/3**

> Phoenix Suns, 52.5, under - similar to Boston, there’s a lot of dysfunction going on there that I think will bleed onto the court - we still don’t even know what’s going on between Monty Williams and DeAndre Ayton, which I don’t like

Devin Booker's injury has done more damage to the Suns than any ownership stuff. I don't think the over will be realistic by the time he gets back. That 1-9 stretch that just ended is a killer. **3/4**

> Golden State Warriors, 51.5, over - slight over - they have too much talent to go under but won’t go too hard in the regular season

They will most likely go under due to their injury struggles and horrid start to the season. **3/5**

>Brooklyn Nets, 50.5, over - this will be a better team than last year with Kyrie being able to play for the first time, and KD is still KD

Hopefully Kevin Durant comes back from injury soon, but this team looks great. They'll go over unless they completely fall apart without KD. **4/6**

> Philadelphia 76ers, 50.5, over - this team is loaded and will try really hard in the regular season

They're looking like a slight over, even with a 5-7 start that looked like the beginning of the end for Doc Rivers and weathering injuries to Joel Embiid, James Harden, and Tyrese Maxey. **5/7**

> Denver Nuggets, 49.5, over - same thing, they will try really hard to get home court advantage

Easy over. **6/8**

> Memphis Grizzlies, 48.5, under - they won’t go quite as hard as they did last year and JJJ missing time and then getting re-integrated will take a little while. May start slow and finish strong like last year

I've got to stop doubting my own favorite team. They're looking like they're going to be a top-3 seed in the West and they have the presumptive Defensive Player of the Year on the roster. Hell yeah. **6/9**

> Dallas Mavericks, 48.5, under - this roster really isn’t very good, Luka by himself is a winning record but Christian Wood isn’t gonna be a positive addition to this team and I think like 45-46 is where they’ll fall

This may end up being correct. I'd peg them at 46 today as well. **7/10**

> Miami Heat, 48.5, under - Kyle Lowry and Jimmy Butler are a year older

Jimmy Butler is still very good at basketball but Kyle Lowry is certainly getting older. This will go under. **8/11**

> Minnesota Timberwolves, 48.5, over, these guys are going to try extremely hard this season and be really, really good, Anthony Edwards is incredible and adding Gobert is automatically going to make them a top defense

I didn't anticipe Karl-Anthony Towns getting injured and I really didn't anticipate Rudy Gobert getting worse. I knew the trade was going to be bad in the long run, but I thought this season would be the one happy year before everything went off the rails. They should have kept Patrick Beverley. **8/12**

> Cleveland Cavaliers, 47.5, over, way over, way way over. Mid 50s, I love Mobley and the Garland-Mitchell pairing is going to be deadly, this team rules and I can’t wait to see them in a real game

I was right! I love this Cavs team and they'll win 50+ games this season. They've weathered Darius Garland missing some time well and they have the second-best defense this season. **9/13**

>Atlanta Hawks, 45.5, under - the Cavs and Nets and 76ers all improved more than the Hawks did this offseason

Yep. The Hawks are so uninspiring this season. Maybe they can hire a better coach before Trae Young jumps ship. **10/14**

>Los Angeles Lakers, 45.5, under - they’re a play-in team at best

Everyone could see this one coming from a mile away. They're not horrendous, but they're still probably going to be around the 10th seed. Maybe Anthony Davis can come back and they can win a bunch of games before he gets injured again. **11/15**

> Toronto Raptors, 45.5, under - very slight under, like 44 or 45. They’re good

Well, they're definitely going under. I didn't see them completely imploding like this. **12/16**

> New Orleans Pelicans, 44.5, way over, 1 they're going to try extremely hard and 2, Zion is that good, adding him to last year’s team which came on at the end of the season is going to be a top 2 seed in the east

If Zion were going to be healthy the entire season, I'd agree with the top-2 seed thing, but still, they're going over. This team is STACKED. **13/17**

> Chicago Bulls, 41.5, under - blah

They have been on a pretty good run lately-- they're 8-4 in their last 12 games-- but that's still got them under .500. They're going to miss the playoffs. **14/18**

> Portland Trail Blazers, 39.5, under - I like the Jerami Grant acquisition but I just don’t like what I see here

They may actually go over on this, but things really aren't looking good right now. They're 19-21 and on a 4-game losing streak. They're on pace for 39 wins right now, so I'll grade this as me being right so far, but I don't feel good about it. **15/19**

> New York Knicks, 38.5, over - Brunson will improve this team and I’m banking on improvement from Barrett and Randle et al

The Knicks are fun again! Jalen Brunson is very good at basketball. Unless they shoot themselves in the foot somehow, they'll go over. **16/20**

> Washington Wizards, 35.5, under - I don’t even know what to say about the Wizards, like the Bulls, it’s just a blah team

They're on pace for 34, so like the Blazers, they may wind up going over if they get hot at any point, but man, what a bland team this is. **17/21**

> Sacramento Kings, 33.5, over - It still feels like a fever dream that Domantas Sabonis is on the Sacramento Kings, but I think him and Fox are a good pairing and Keegan Murray is a stud. They’ll go over but still won’t be in the play-in

I have never been so happy to be wrong. This is the best Kings team in forever. They're going to be in the playoffs and will probably bypass the play-in. As of right now, they're the 5th seed and on pace for 45 wins. LIGHT THE BEAM! **17/22**

> Charlotte Hornets, 33.5, under - just another uninspiring team, and unfortunately, they’ll be without LaMelo Ball for a little while to start the season, I hate that

Another uninspiring team. They're on pace to go way under this number. If LaMelo had played the whole year, the same thing may have still happened. **18/23**

> Detroit Pistons, 29.5, over - I’m very high on Cade, on Jaden Ivey, on Memphis Tiger Jalen Duren, I like the Bojan Bogdanovic acquisition, they have a really weird roster but I think it’s got some talent and I like them going slightly over

Any chance of that happening went out the window with Cade Cunningham's injury. I do like this team, though - they've been fun to watch. **18/24**

>Orlando Magic, 26.5, over - so much talent and passion on this roster. It’s going to take them holding multiple players out if they want to tank this year

They're 16-26, so they might actually go over on this one. This team has got a ton of talent, like I said, and they're a fun watch. They're fun, have a bright future, and will still get a high lottery pick this summer. That's a great position to be in. **19/25**

> Utah Jazz, 24.5, over - I’m sure they’ll move on from Mike Conley and Jordan Clarkson at some point this year, but whether they like it or not, Collin Sexton is gonna win them some games, Walker Kessler is gonna be a good defender, maybe not immediately, but later in the year, they’ve got enough competent NBA players on the roster that unless they move off of them before the trade deadline, they may accidentally go over

I certainly didn't see their hot start coming, but it's statistically impossible for them to go under at this point. **20/26**

> Indiana Pacers, 23.5, under - I think this may be the first full season the Indiana Pacers intentionally tank and I hope it pays off for them

Who needs to tank when you've got Tyrese Haliburton and Bennedict Mathurin?? They'll go over in the next couple of days. **20/27**

> OKC Thunder, 23.5, under - they have their eyes on the prize here.

They're going to go over their win total soon. The Thunder aren't going to get Victor Wembanyama, most likely, unless they get some crazy lottery luck or they shut down Shai Gilgeous-Alexander once again. **20/28**

> Houston Rockets, 23.5, over - like I said, they have too much talent between Green and Sengun and Jabari Smith etc that they’re gonna be in the low 30s

Low 30s isn't going to happen, but I stand by what I said about their talent. This isn't their year, but they'll figure out how to win eventually. I doubt they go over, though. **20/29**

> And then the San Antonio Spurs, 22.5, under, alongside the Thunder, the Spurs are going to smash the under to get either Victor Wembanyama or Scoot Henderson, the Spurs and Thunder are experienced veterans of the tank game and they will not disappoint their fans by winning more than 20 games this year

The Spurs are on track for 26 wins right now, so unless something changes, they'll likely go over. It's really tough to pick over-unders for tanking teams. **20/30**



So, it looks like I'll get 20 of the 30 picks right. I guess that's not too bad, that's better than flipping a coin. I was doing really well until we got to the worst teams... Anyway. 

-----

# Playoffs

My playoff picks were:
-The Clippers would defeat the Warriors in the Western Conference Finals
-The Bucks would defeat the Nets in the Eastern Conference Finals, and
-The Bucks would defeat the Clippers in the NBA Finals.

The West is way off, but I can still see the Milwaukee-Brooklyn matchup in the ECF happening.

I'll check in on this again at the end of the season. 

Checking in on my preseason predictions. Yeeeeowch!

Mid-season check-in on preseason predictions

I found this tweet while I was researching an error I was getting while trying to scrape data from Basketball Reference:

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">sports research just got a bit more difficult: basketball-reference has implemented recaptcha and is enforcing a 3 second crawl delay.</p>&mdash; alex cardazzi (@ACardazzi) <a href="https://twitter.com/ACardazzi/status/1608126560870998016?ref_src=twsrc%5Etfw">December 28, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

I figured this was eventually going to be the case, considering in the [Sports Reference terms of service](https://www.sports-reference.com/termsofuse.html) (sec. 5i) it says we shouldn't scrape from them without permission and myself and plenty of others have been skating by for years.

Per Basketball Reference's [robots.txt,](https://www.basketball-reference.com/robots.txt) you should throw in `Sys.sleep(3)` commands liberally while scraping in R. I will incorporate that into any code I publish on here in the future.

I'd started getting a 403 error message after calling 10-15 pages, but I just ran a script that pulls about 100 pages. While it was slower than I'm used to becuase of the delays, it never kicked me out, so I'm satisfied. As long as we can keep pulling data from there, that's all that matters to me.

Sports Reference has started to enforce a 3-second crawl limit

It would be very helpful if the NBA stats website gave users the option to exclude certain types of turnovers from a player's assist-to-turnover ratio. While it doesn't tell the entire story, I think the assist-to-_bad-pass_ ratio can give a clearer picture of the quality and security of a player's passes.

Think about it— if your goal is to measure the quality of a player's passing (which is not always the stated goal of using A/TO), is the number of times a player committed and offensive foul or carried the ball relevant at all? 

Below are the top 100 players by career assist-to-bad-pass ratio (min. 400 assists). Detailed play-by-play data only exists from 1996-97 onward and I've cut this off at the 2021-22 season. Here are a couple of examples of why I think this is a good piece of information to have:

1. Tyus Jones is #1, which lines up with what you'd expect. He's finished with the league's best assist-to-turnover ratio several times in his career. His younger brother, Tre, would be #2 if this I lowered the minimum assists threshold. 
2. Nikola Jokić's career assist-to-turnover ratio is around 2.24. When you exclude offensive fouls, which he does a fair amount, and other non-passing turnovers, his ratio goes up to 4.1, which is much more representative of his superior passing skills. I'm not a Jokić fan in the slightest— I'm the opposite, really— but even I have to admit that any offensive statistic that doesn't show him as being one of the best could use some adjusting.

And I just want to note: this is not a perfect representation of a player's passing ability. It doesn't answer the question "Who is the best passer in the league?", but it's a start.

For example, by this measure, Brandon Clarke of the Memphis Grizzlies would have a ratio of 6.6, and would show up near the top of this list if he had enough assists. **You should not consider Brandon Clarke to be one of the greatest passers of all time.** This statistic rates him well because although he is not in the type of role where he has many opportunities to get assists, he does tend to make passes that reach his teammates' hands instead of his opponents'. 


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<table class="tableizer-table">
<thead><tr class="tableizer-firstrow"><th>Rank</th><th>Player</th><th>Assists</th><th>Bad Pass Turnovers</th><th>Assist to Bad Pass Ratio</th></tr></thead><tbody>
 <tr><td>1</td><td>Tyus Jones</td><td>1691</td><td>227</td><td>7.4</td></tr>
 <tr><td>2</td><td>Monte Morris</td><td>1042</td><td>142</td><td>7.3</td></tr>
 <tr><td>3</td><td>Kevon Looney</td><td>498</td><td>69</td><td>7.2</td></tr>
 <tr><td>4</td><td>Chris Quinn</td><td>455</td><td>64</td><td>7.1</td></tr>
 <tr><td>5</td><td>Travis Diener</td><td>432</td><td>62</td><td>7.0</td></tr>
 <tr><td>6</td><td>Chris Paul</td><td>10977</td><td>1625</td><td>6.8</td></tr>
 <tr><td>7</td><td>Brandon Roy</td><td>1517</td><td>230</td><td>6.6</td></tr>
 <tr><td>8</td><td>Tyrese Maxey</td><td>441</td><td>70</td><td>6.3</td></tr>
 <tr><td>9</td><td>Ryan Arcidiacono</td><td>460</td><td>75</td><td>6.1</td></tr>
 <tr><td>10</td><td>Gary Payton</td><td>5848</td><td>973</td><td>6.0</td></tr>
 <tr><td>11</td><td>Jordan McLaughlin</td><td>498</td><td>83</td><td>6.0</td></tr>
 <tr><td>12</td><td>Frank Kaminsky</td><td>619</td><td>105</td><td>5.9</td></tr>
 <tr><td>13</td><td>Terrell Brandon</td><td>2662</td><td>462</td><td>5.8</td></tr>
 <tr><td>14</td><td>Delon Wright</td><td>1246</td><td>217</td><td>5.7</td></tr>
 <tr><td>15</td><td>Antonio Daniels</td><td>2934</td><td>511</td><td>5.7</td></tr>
 <tr><td>16</td><td>Jason Collins</td><td>626</td><td>110</td><td>5.7</td></tr>
 <tr><td>17</td><td>Jason Hart</td><td>774</td><td>140</td><td>5.5</td></tr>
 <tr><td>18</td><td>José Calderón</td><td>5148</td><td>935</td><td>5.5</td></tr>
 <tr><td>19</td><td>Avery Johnson</td><td>2662</td><td>486</td><td>5.5</td></tr>
 <tr><td>20</td><td>Anthony Mason</td><td>1926</td><td>352</td><td>5.5</td></tr>
 <tr><td>21</td><td>Ish Smith</td><td>2799</td><td>515</td><td>5.4</td></tr>
 <tr><td>22</td><td>Kevin Ollie</td><td>1501</td><td>277</td><td>5.4</td></tr>
 <tr><td>23</td><td>Muggsy Bogues</td><td>1238</td><td>229</td><td>5.4</td></tr>
 <tr><td>24</td><td>Fred VanVleet</td><td>1704</td><td>316</td><td>5.4</td></tr>
 <tr><td>25</td><td>Al Horford</td><td>3144</td><td>589</td><td>5.3</td></tr>
 <tr><td>26</td><td>Alvin Williams</td><td>1877</td><td>352</td><td>5.3</td></tr>
 <tr><td>27</td><td>T.J. McConnell</td><td>2404</td><td>456</td><td>5.3</td></tr>
 <tr><td>28</td><td>Bimbo Coles</td><td>1241</td><td>236</td><td>5.3</td></tr>
 <tr><td>29</td><td>Anthony Goldwire</td><td>625</td><td>119</td><td>5.3</td></tr>
 <tr><td>30</td><td>Speedy Claxton</td><td>1441</td><td>276</td><td>5.2</td></tr>
 <tr><td>31</td><td>Jeff McInnis</td><td>2514</td><td>482</td><td>5.2</td></tr>
 <tr><td>32</td><td>Michael Kidd-Gilchrist</td><td>515</td><td>99</td><td>5.2</td></tr>
 <tr><td>33</td><td>Tim Frazier</td><td>1142</td><td>220</td><td>5.2</td></tr>
 <tr><td>34</td><td>Earl Boykins</td><td>2092</td><td>406</td><td>5.2</td></tr>
 <tr><td>35</td><td>Tony Parker</td><td>7036</td><td>1367</td><td>5.1</td></tr>
 <tr><td>36</td><td>Cory Joseph</td><td>2186</td><td>425</td><td>5.1</td></tr>
 <tr><td>37</td><td>Carlos Arroyo</td><td>1761</td><td>343</td><td>5.1</td></tr>
 <tr><td>38</td><td>Donald Sloan</td><td>651</td><td>128</td><td>5.1</td></tr>
 <tr><td>39</td><td>Damon Stoudamire</td><td>4718</td><td>933</td><td>5.1</td></tr>
 <tr><td>40</td><td>Kenny Anderson</td><td>2505</td><td>497</td><td>5.0</td></tr>
 <tr><td>41</td><td>Sam Cassell</td><td>5064</td><td>1012</td><td>5.0</td></tr>
 <tr><td>42</td><td>Pooh Richardson</td><td>425</td><td>85</td><td>5.0</td></tr>
 <tr><td>43</td><td>Markelle Fultz</td><td>623</td><td>125</td><td>5.0</td></tr>
 <tr><td>44</td><td>Jalen Brunson</td><td>1034</td><td>208</td><td>5.0</td></tr>
 <tr><td>45</td><td>LaMarcus Aldridge</td><td>2076</td><td>418</td><td>5.0</td></tr>
 <tr><td>46</td><td>Derrick White</td><td>1006</td><td>205</td><td>4.9</td></tr>
 <tr><td>47</td><td>Tyrese Haliburton</td><td>937</td><td>191</td><td>4.9</td></tr>
 <tr><td>48</td><td>Adrian Griffin</td><td>653</td><td>134</td><td>4.9</td></tr>
 <tr><td>49</td><td>Rod Strickland</td><td>3745</td><td>769</td><td>4.9</td></tr>
 <tr><td>50</td><td>Spencer Dinwiddie</td><td>1933</td><td>398</td><td>4.9</td></tr>
 <tr><td>51</td><td>Damon Jones</td><td>1806</td><td>372</td><td>4.9</td></tr>
 <tr><td>52</td><td>Terry Rozier</td><td>1509</td><td>311</td><td>4.9</td></tr>
 <tr><td>53</td><td>John Stockton</td><td>4496</td><td>929</td><td>4.8</td></tr>
 <tr><td>54</td><td>DeMar DeRozan</td><td>3729</td><td>771</td><td>4.8</td></tr>
 <tr><td>55</td><td>Jimmy Butler</td><td>2836</td><td>588</td><td>4.8</td></tr>
 <tr><td>56</td><td>Mark Jackson</td><td>4444</td><td>923</td><td>4.8</td></tr>
 <tr><td>57</td><td>Tyronn Lue</td><td>1727</td><td>359</td><td>4.8</td></tr>
 <tr><td>58</td><td>Giannis Antetokounmpo</td><td>3020</td><td>630</td><td>4.8</td></tr>
 <tr><td>59</td><td>Ronnie Brewer</td><td>828</td><td>173</td><td>4.8</td></tr>
 <tr><td>60</td><td>Immanuel Quickley</td><td>402</td><td>84</td><td>4.8</td></tr>
 <tr><td>61</td><td>Deron Williams</td><td>6819</td><td>1426</td><td>4.8</td></tr>
 <tr><td>62</td><td>Arron Afflalo</td><td>1386</td><td>290</td><td>4.8</td></tr>
 <tr><td>63</td><td>Chauncey Billups</td><td>5636</td><td>1186</td><td>4.8</td></tr>
 <tr><td>64</td><td>Andre Miller</td><td>8524</td><td>1796</td><td>4.7</td></tr>
 <tr><td>65</td><td>Dejounte Murray</td><td>1540</td><td>326</td><td>4.7</td></tr>
 <tr><td>66</td><td>Matt Bonner</td><td>552</td><td>117</td><td>4.7</td></tr>
 <tr><td>67</td><td>Bobby Portis</td><td>537</td><td>114</td><td>4.7</td></tr>
 <tr><td>68</td><td>Kawhi Leonard</td><td>1672</td><td>355</td><td>4.7</td></tr>
 <tr><td>69</td><td>Kirk Hinrich</td><td>4245</td><td>903</td><td>4.7</td></tr>
 <tr><td>70</td><td>Yogi Ferrell</td><td>601</td><td>128</td><td>4.7</td></tr>
 <tr><td>71</td><td>Bryn Forbes</td><td>506</td><td>108</td><td>4.7</td></tr>
 <tr><td>72</td><td>George Hill</td><td>2697</td><td>576</td><td>4.7</td></tr>
 <tr><td>73</td><td>Brevin Knight</td><td>4481</td><td>960</td><td>4.7</td></tr>
 <tr><td>74</td><td>Tomáš Satoranský</td><td>1586</td><td>340</td><td>4.7</td></tr>
 <tr><td>75</td><td>Travis Best</td><td>2347</td><td>505</td><td>4.6</td></tr>
 <tr><td>76</td><td>Tayshaun Prince</td><td>2406</td><td>518</td><td>4.6</td></tr>
 <tr><td>77</td><td>Cameron Payne</td><td>905</td><td>195</td><td>4.6</td></tr>
 <tr><td>78</td><td>Brad Wanamaker</td><td>464</td><td>100</td><td>4.6</td></tr>
 <tr><td>79</td><td>Royal Ivey</td><td>501</td><td>108</td><td>4.6</td></tr>
 <tr><td>80</td><td>Mike Conley</td><td>5407</td><td>1166</td><td>4.6</td></tr>
 <tr><td>81</td><td>Eric Snow</td><td>4172</td><td>900</td><td>4.6</td></tr>
 <tr><td>82</td><td>Anthony Johnson</td><td>2274</td><td>491</td><td>4.6</td></tr>
 <tr><td>83</td><td>Steve Kerr</td><td>522</td><td>113</td><td>4.6</td></tr>
 <tr><td>84</td><td>Nemanja Bjelica</td><td>826</td><td>179</td><td>4.6</td></tr>
 <tr><td>85</td><td>Brandon Jennings</td><td>3151</td><td>685</td><td>4.6</td></tr>
 <tr><td>86</td><td>Malik Beasley</td><td>418</td><td>91</td><td>4.6</td></tr>
 <tr><td>87</td><td>Kyle Anderson</td><td>1167</td><td>255</td><td>4.6</td></tr>
 <tr><td>88</td><td>Darren Collison</td><td>3545</td><td>776</td><td>4.6</td></tr>
 <tr><td>89</td><td>Elfrid Payton</td><td>2868</td><td>629</td><td>4.6</td></tr>
 <tr><td>90</td><td>Lee Mayberry</td><td>701</td><td>154</td><td>4.6</td></tr>
 <tr><td>91</td><td>Malcolm Brogdon</td><td>1596</td><td>351</td><td>4.5</td></tr>
 <tr><td>92</td><td>Ty Lawson</td><td>3316</td><td>732</td><td>4.5</td></tr>
 <tr><td>93</td><td>Austin Rivers</td><td>1438</td><td>319</td><td>4.5</td></tr>
 <tr><td>94</td><td>Brian Roberts</td><td>721</td><td>160</td><td>4.5</td></tr>
 <tr><td>95</td><td>Devonte' Graham</td><td>1203</td><td>268</td><td>4.5</td></tr>
 <tr><td>96</td><td>Moochie Norris</td><td>1233</td><td>275</td><td>4.5</td></tr>
 <tr><td>97</td><td>Facundo Campazzo</td><td>452</td><td>101</td><td>4.5</td></tr>
 <tr><td>98</td><td>Brendan Haywood</td><td>442</td><td>99</td><td>4.5</td></tr>
 <tr><td>99</td><td>Patrick Beverley</td><td>1839</td><td>412</td><td>4.5</td></tr>
 <tr><td>100</td><td>Charlie Bell</td><td>857</td><td>192</td><td>4.5</td></tr>
</tbody></table>

I make a case for using a slightly different statistic to measure the quality of a player's passes.

small_EtCTPGHXIAAae84

thumbnail_EtCTPGHXIAAae84

EtCTPGHXIAAae84

Measuring the quality of a player's passes by looking at assist-to-bad-pass turnover rate

One of the things that I think Basketball Reference should add on their team pages is something they already do on their Sports Reference college basketball site: adding the % of minutes and/or scoring returned from the previous year's team. Here is a picture of that in action on the [2023 Memphis Tigers roster:](https://www.sports-reference.com/cbb/schools/memphis/2023.html)

![Screen Shot 2022-12-22 at 12.32.54 PM.png](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/Screen_Shot_2022_12_22_at_12_32_54_PM_0da721295c.png)

There at the bottom, you can see that after a rash of transfers and three players entering the NBA draft, the Tigers are only returning about a third of their minutes from last year's squad. 

But on Basketball Reference, that kind of information is nowhere to be found. There is a [hard-to-find list](https://www.basketball-reference.com/friv/continuity.html) that tells you the percentage of minutes played by people who were on the roster the previous year, but not what percentage of minutes from last year's roster returned. (This may sound like a questionable distinction, but I promise it's different.) Instead, immediately beneath the roster on all team pages is a list of the assistant coaches.

So, I wrote a function in R that calculates for any team in any season:

   (1) the number of returning players from the previous season,
   (2) the number of minutes returned from the previous season, and
   (3) the percent of minutes returned from the previous season.

The code is below. You'll need the `rvest`, `stringr`, and `dplyr` packages.




```
returning_minutes_calc = function(team,year){

  #fill in the URLs for the year of interest and the previous year
  url_previous_year <- paste0('https://www.basketball-reference.com/teams/',team,'/',year-1,'.html')
  url_current_year <- paste0('https://www.basketball-reference.com/teams/',team,'/',year,'.html')
    
  
  #get total minutes played by each player from the previous year's team
  previous_year_html_tables <- read_html(url_previous_year) %>%
    html_nodes("table") %>%
    html_table(fill = TRUE)
  
  previous_year_minutes <- data.frame(previous_year_html_tables[[4]]) %>% 
    select(Player=2,MP) %>% 
    filter(Player!='')
  
  
  #do the same for this year's team, but in the second command, create a flag "return" to help determine whether the player did return from last year's squad
  current_year_html_tables <- read_html(url_current_year) %>%
    html_nodes("table") %>%
    html_table(fill = TRUE)
  
  current_year_minutes <- data.frame(current_year_html_tables[[4]]) %>% 
    select(Player=2) %>% 
    mutate(return=1) %>% 
    filter(Player!='')
  
  #join the two tables together and 
  previous_year_minutes %>% 
    left_join(current_year_minutes) %>% 
    mutate(return=ifelse(is.na(return),0,return)) %>%  #(this is where the "return" flag comes in handy)
    mutate(returning_minutes_from_previous_year=MP*return,team=team,year=year) %>% 
    group_by(team,year) %>% 
    summarize(number_of_returning_players=sum(return),
              returning_minutes_from_previous_year=sum(returning_minutes_from_previous_year),
              previous_year_total_minutes=sum(MP)) %>% 
    mutate(percent_minutes_returning=100*(returning_minutes_from_previous_year/previous_year_total_minutes)) %>% return()
  
}
```

Here are a couple of examples of what the result of this function looks like:

```
returning_minutes_calc("LAL",2022)
```
 

 
<style type="text/css">
	table.tableizer-table {
		font-size: 12px;
		border: 1px solid #CCC; 
		font-family: Arial, Helvetica, sans-serif;
	} 
	.tableizer-table td {
		padding: 4px;
		margin: 3px;
		border: 1px solid #CCC;
	}
	.tableizer-table th {
		background-color: #000000; 
		color: #FFF;
		font-weight: bold;
	}
</style>
<table class="tableizer-table">
<thead><tr class="tableizer-firstrow"><th>team</th><th>year</th><th>number_of_returning_players</th><th>returning_minutes_from_previous_year</th><th>previous_year_total_minutes</th><th>percent_minutes_returning</th></tr></thead><tbody>
 <tr><td>LAL</td><td>2022</td><td>3</td><td>3970</td><td>17456</td><td>22.7</td></tr>
</tbody></table>


```
returning_minutes_calc("MEM",2023)
```

<style type="text/css">
	table.tableizer-table {
		font-size: 12px;
		border: 1px solid #CCC; 
		font-family: Arial, Helvetica, sans-serif;
	} 
	.tableizer-table td {
		padding: 4px;
		margin: 3px;
		border: 1px solid #CCC;
	}
	.tableizer-table th {
		background-color: #000000; 
		color: #FFF;
		font-weight: bold;
	}
</style>
<table class="tableizer-table">
<thead><tr class="tableizer-firstrow"><th>team</th><th>year</th><th>number_of_returning_players</th><th>returning_minutes_from_previous_year</th><th>previous_year_total_minutes</th><th>percent_minutes_returning</th></tr></thead><tbody>
 <tr><td>MEM</td><td>2023</td><td>11</td><td>15659</td><td>19782</td><td>79.2</td></tr>
</tbody></table>


So as we can see, this year's Memphis Grizzlies roster brought back a much larger share of last year's team than the 2022 Los Angeles Lakers brought back from 2021. Everyone on this year's roster, save for the 5 rookies and Danny Green, was on the team last year, while last season the Lakers only brought back LeBron James, Anthony Davis, and Talen Horton-Tucker. That's it. Almost everyone else was signed as a free agent that summer on a short-term contract, and as we know, that had disastrous results for LA last year.

-----------
Just for fun, let's check out the relationship between percent of minutes returned and current season winning percentage (through games that took place on December 21st, 2022). We'll just use the Atlantic Division, which is the Brooklyn nets, the Boston Celtics, the New York Knicks, the Philadelphia 76ers, and the Toronto Raptors.

```
atlantic_teams <- c("BRK", "BOS", "NYK", "PHI", "TOR")
               
atlantic_teams_data <- sapply(atlantic_teams,returning_minutes_calc, year=2023)
atlantic_teams_data_frame <- as.data.frame(t(atlantic_teams_data))
```

###### (I am using `sapply` in lieu of a for-loop to make the code a little cleaner, but I like for-loops better. I've omitted the section of code where I converted this list result into a data frame and set each column to the proper type.)

Then we left join in the standings. I had that in spreadsheet form already, so I'm just importing that into the object `standings`. This is what it looks like:

```
>head(standings)
team   wins   losses   win_pct

MIL    22     9        70.96774
BOS    22     10       68.75
CLE    22     11       66.67
BRK    20     12       62.5
PHI    18     12       60
NYK    18     14       56.25
```


So we join the table `atlantic_teams_data_frame` to `standings` and then plot them together. Here's a ggplot2 graph showing the relationship between % of minutes returned from last season and their current win %:


![Screen Shot 2022-12-22 at 12.29.57 PM.png](https://backfired-strapi-aws-s3-images-bucket.s3.us-east-2.amazonaws.com/Screen_Shot_2022_12_22_at_12_29_57_PM_1032fd1ec6.png)

Assuming the correlation between those two is positive when you look at the entire league, we see a massive outlier: the Toronto Raptors, who are returning over 90% of last season's minutes, but currently sit at 14-18 with Pascal Siakam, OG Anunoby, and Fred VanVleet in trade rumors. 


Here's the code for the plot, if you're curious:

```
data_and_standings <- atlantic_teams_data_frame %>% left_join(standings)

library(ggplot2)
ggplot(data_and_standings,aes(x=percent_minutes_returning,y=win_pct, label=team)) + 
  geom_point() + 
  labs(title="Returning minutes and\n winning percentage, 2022-23",
       x ="% of minutes returned from previous season", y = "Team win %") +
  theme(
    plot.title = element_text(hjust=.5, face="bold"),
    axis.title.x = element_text(size=10, face="bold"),
    axis.title.y = element_text(size=10, face="bold")
  ) + 
  labs(caption="Source: basketballreference.com") +
  geom_text(hjust=0, vjust=0)
```


A quick R tutorial to determine the number of minutes an NBA team is returning from its previous year.

large_slam-238-memphis-grizzlies-cover-1-of-3-600094.jpg

medium_slam-238-memphis-grizzlies-cover-1-of-3-600094.jpg

small_slam-238-memphis-grizzlies-cover-1-of-3-600094.jpg

thumbnail_slam-238-memphis-grizzlies-cover-1-of-3-600094.jpg

slam-238-memphis-grizzlies-cover-1-of-3-600094.jpg

Calculating NBA roster continuity in R

As someone who only watches basketball and the English Premier League, I love getting to combine the two in some way. Even though I'm not the biggest Boston Celtics fan in the world, seeing my favorite footballer, Bukayo Saka, taking in a Celtics game was one of the bright spots in my malaise after Arsenal's late-season loss to Tottenham Hotspur ended their hopes at an improbable top-4 finish.

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Bukayo Saka linking up with Boston Celtics basketball player Aaron Nesmith during the Celtics 102-82 win over the Miami Heat in Game 4 of the Conference Finals in Boston last night. 🏀 <a href="https://twitter.com/hashtag/BleedGreen?src=hash&amp;ref_src=twsrc%5Etfw">#BleedGreen</a><a href="https://twitter.com/BukayoSaka87?ref_src=twsrc%5Etfw">@BukayoSaka87</a> 🤝 <a href="https://twitter.com/aaronnesmith24?ref_src=twsrc%5Etfw">@aaronnesmith24</a> <a href="https://t.co/K7cK1V2SY1">pic.twitter.com/K7cK1V2SY1</a></p>&mdash; afcstuff (@afcstuff) <a href="https://twitter.com/afcstuff/status/1528998295581904898?ref_src=twsrc%5Etfw">May 24, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

So when I had the idea to convert the NBA standings into a soccer-style table, I thought it would be a great little project. I'm going to break down the necessary parts of the short R script that I wrote to accomplish this. It involves scraping data from Basketball Reference.

So first off, I wanted to make this script portable. This script will work on any recent NBA season, but if you want to adapt this for an NBA season that happened before the Hornets became the Pelicans and the Bobcats became the Hornets, you'll just have to change what team abbreviations go into the "teams" vector.

Here I will load the necessary packages:
```
library(dplyr)
library(stringr)
library(rvest)
```

\
This is a vector that holds all 30 teams' abbreviations on Basketball Reference:

```
teams <- c('BOS','TOR','PHI','NYK','BRK',
                    'ATL','CHO','WAS','MIA','ORL',
                    'MIL','CHI','IND','DET','CLE',
                    'MEM','DAL','HOU','SAS','NOP',
                    'LAL','LAC','SAC','GSW','PHO',
                    'MIN','UTA','DEN','OKC','POR')
```
\
Now we set the year and initialize the "schedule" data frame. I'm going to do this for the current season, 2022-23. The end result table will be accurate through the games on Friday, December 16th, 2022.
```
year=2023

schedule <- data.frame()
```

\
Now I'll pull all 30 teams' schedules using this for-loop:

```
for(i in 1:length(teams)){

   url <- paste0('https://www.basketball-reference.com/teams/',teams[i],'/',year,'_games.html')
   
   webpage <- read_html(url)
   
   tbls_ls <- webpage %>%
   html_nodes("table") %>%
   html_table(fill = TRUE)
     
#only pulling a few columns from the first table in each list
    
   sched <- data.frame(tbls_ls[[1]])[c(2,6,7,9:11)]
   
   sched <- sched %>% filter(Date!="Date")
   
   names(sched) <- c("Date","Home_Away","Opponent","Overtime",
                        "Points_For","Points_Against")
                        
   sched$Team <- teams[i]
   
   schedule <- rbind(schedule,sched)
 }
```
\
Because we scraped everything from online, it's all text, so we'll convert the dates to dates and the numbers to numbers. Revolutionary.

```
 schedule$Date <- as.Date(schedule$Date,format = "%a, %b %d, %Y")
 
 schedule$Points_For <- as.numeric(schedule$Points_For)
 
 schedule$Points_Against <- as.numeric(schedule$Points_Against)
 
 schedule$Overtime <- ifelse(is.na(schedule$Overtime)," ",schedule$Overtime)

```
\
Now is where the tough decision comes in. Soccer is famous for having ties, basketball is famous for going into as many overtimes as possible to decide a winner and loser in every single game. If we don't incorporate a tie in some way, the "points" on the table will just be 3 for every win and 0 for every loss, and then the table will be no different from the standings. 

So, I arbitrarily decided that, in addition to overtime games, a "draw" could also include a result within 3 points. It could be 4 or 5. You could just include games that went into overtime. I just chose overtime games and games within 3 points. Feel free to change the draw threshold around and see how different the table becomes!

```
 schedule$Result <- ifelse(schedule$Overtime=="OT", 'D',  
 ifelse(abs(schedule$Points_Against-schedule$Points_For)<=3, 'D', 
 ifelse(schedule$Points_For > schedule$Points_Against,'W','L')))
 
 schedule$points <- ifelse(schedule$Result=='D',1,ifelse(schedule$Result=='W',3,0))
```

\
Now we will put everything together in a nice clean table in the same column order as the soccer table. (Here's where I switch from base R to dplyr full-time.)
```
table <- schedule %>% 
    filter(!is.na(points)) %>% 
  group_by(Team) %>% 
  summarize(
      `Matches Played` = sum(!is.na(points)),
        Wins = sum(ifelse(points==3,1,0)),
        Draws = sum(ifelse(points==1,1,0)),
        Losses = sum(ifelse(points==0,1,0)),
       `Scored` = sum(Points_For,na.rm=T),
       `Conceded` = sum(Points_Against,na.rm=T),
         Differential = Scored-Conceded,
         Points=sum(points,na.rm=T)) %>% 
  arrange(desc(Points),desc(Differential)) %>% 
  mutate(Rank=row_number()) %>% 
  print(n=30)
```

But we also want to show the "Form" column that shows the 5 most recent results for each team. So we'll make that and join it into the final table, first initializing the blank "form" data frame:

```
 form <- data.frame()
 
 for(i in 1:length(teams)){
       L5 <- schedule %>% 
                 filter(Team==teams[i] & !is.na(points)) %>% 
                 tail(5) %>% 
                 mutate('Last 5' = paste0(Result[5],
                           Result[4],
                           Result[3],
                           Result[2],
                           Result[1]))
       form[i,1] <- teams[i]
       form[i,2] <- L5$`Last 5`[1]
}

names(form) <- c("Team",'Form')
```
\
Now we left-join the table with "form" and rearrange a couple of columns to get our full result.

```
full_table <- table %>% 
                     left_join(form) %>% 
                     select(10,1:9,11)
```
\
And so, for the day I'm writing this up, this is the current soccer-style table for the NBA. If the NBA relegated and promoted teams like soccer leagues did, we'd have the Boston Celtics clearly winning the league, the Memphis Grizzlies, Cleveland Cavaliers, and New Orleans Pelicans joining them in the Champions League, and the San Antonio Spurs, Detroit Pistons, and Charlotte Hornets facing relegation.



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		font-family: Arial, Helvetica, sans-serif;
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</style>
<table class="tableizer-table">
<thead><tr class="tableizer-firstrow"><th>Rank</th><th>Team</th><th>Matches Played</th><th>Wins</th><th>Draws</th><th>Losses</th><th>Scored</th><th>Conceded</th><th>Differential</th><th>Points</th><th>Form</th></tr></thead><tbody>
 <tr><td>1</td><td>Boston Celtics</td><td>30</td><td>20</td><td>5</td><td>5</td><td>3572</td><td>3383</td><td>189</td><td>65</td><td>LDLLW</td></tr>
 <tr><td>2</td><td>Memphis Grizzlies</td><td>28</td><td>17</td><td>4</td><td>7</td><td>3261</td><td>3117</td><td>144</td><td>55</td><td>WWWWW</td></tr>
 <tr><td>3</td><td>Cleveland Cavaliers</td><td>30</td><td>16</td><td>6</td><td>8</td><td>3327</td><td>3144</td><td>183</td><td>54</td><td>WWDWL</td></tr>
 <tr><td>4</td><td>New Orleans Pelicans</td><td>28</td><td>16</td><td>6</td><td>6</td><td>3287</td><td>3129</td><td>158</td><td>54</td><td>DLDWW</td></tr>
 <tr><td>5</td><td>Milwaukee Bucks</td><td>28</td><td>17</td><td>3</td><td>8</td><td>3142</td><td>3047</td><td>95</td><td>54</td><td>LWLDW</td></tr>
 <tr><td>6</td><td>Phoenix Suns</td><td>29</td><td>15</td><td>8</td><td>6</td><td>3343</td><td>3211</td><td>132</td><td>53</td><td>WLDLL</td></tr>
 <tr><td>7</td><td>Brooklyn Nets</td><td>30</td><td>15</td><td>5</td><td>10</td><td>3381</td><td>3333</td><td>48</td><td>50</td><td>DWDWW</td></tr>
 <tr><td>8</td><td>Philadelphia 76ers</td><td>28</td><td>14</td><td>5</td><td>9</td><td>3120</td><td>3027</td><td>93</td><td>47</td><td>WWWDL</td></tr>
 <tr><td>9</td><td>Sacramento Kings</td><td>28</td><td>14</td><td>5</td><td>9</td><td>3298</td><td>3233</td><td>65</td><td>47</td><td>WDLLW</td></tr>
 <tr><td>10</td><td>Denver Nuggets</td><td>28</td><td>13</td><td>7</td><td>8</td><td>3239</td><td>3213</td><td>26</td><td>46</td><td>LWWDD</td></tr>
 <tr><td>11</td><td>Los Angeles Clippers</td><td>31</td><td>13</td><td>6</td><td>12</td><td>3322</td><td>3350</td><td>-28</td><td>45</td><td>LWWWL</td></tr>
 <tr><td>12</td><td>Golden State Warriors</td><td>30</td><td>13</td><td>5</td><td>12</td><td>3511</td><td>3505</td><td>6</td><td>44</td><td>LLLWD</td></tr>
 <tr><td>13</td><td>New York Knicks</td><td>29</td><td>12</td><td>6</td><td>11</td><td>3315</td><td>3260</td><td>55</td><td>42</td><td>WDWWW</td></tr>
 <tr><td>14</td><td>Toronto Raptors</td><td>29</td><td>12</td><td>6</td><td>11</td><td>3233</td><td>3214</td><td>19</td><td>42</td><td>DDLLW</td></tr>
 <tr><td>15</td><td>Indiana Pacers</td><td>30</td><td>12</td><td>6</td><td>12</td><td>3447</td><td>3474</td><td>-27</td><td>42</td><td>LWLDW</td></tr>
 <tr><td>16</td><td>Utah Jazz</td><td>31</td><td>11</td><td>8</td><td>12</td><td>3654</td><td>3589</td><td>65</td><td>41</td><td>DWLLD</td></tr>
 <tr><td>17</td><td>Portland Trail Blazers</td><td>29</td><td>11</td><td>7</td><td>11</td><td>3262</td><td>3256</td><td>6</td><td>40</td><td>LWWWD</td></tr>
 <tr><td>18</td><td>Atlanta Hawks</td><td>30</td><td>12</td><td>4</td><td>14</td><td>3417</td><td>3451</td><td>-34</td><td>40</td><td>WLLDL</td></tr>
 <tr><td>19</td><td>Minnesota Timberwolves</td><td>29</td><td>12</td><td>4</td><td>13</td><td>3313</td><td>3360</td><td>-47</td><td>40</td><td>DLLLW</td></tr>
 <tr><td>20</td><td>Los Angeles Lakers</td><td>28</td><td>11</td><td>5</td><td>12</td><td>3230</td><td>3255</td><td>-25</td><td>38</td><td>WDWDL</td></tr>
 <tr><td>21</td><td>Chicago Bulls</td><td>28</td><td>11</td><td>5</td><td>12</td><td>3157</td><td>3187</td><td>-30</td><td>38</td><td>LDDWW</td></tr>
 <tr><td>22</td><td>Dallas Mavericks</td><td>29</td><td>8</td><td>13</td><td>8</td><td>3241</td><td>3188</td><td>53</td><td>37</td><td>WLWLD</td></tr>
 <tr><td>23</td><td>Washington Wizards</td><td>29</td><td>9</td><td>6</td><td>14</td><td>3220</td><td>3303</td><td>-83</td><td>33</td><td>LLLLL</td></tr>
 <tr><td>24</td><td>Miami Heat</td><td>30</td><td>7</td><td>11</td><td>12</td><td>3241</td><td>3277</td><td>-36</td><td>32</td><td>DDWLW</td></tr>
 <tr><td>25</td><td>Oklahoma City Thunder</td><td>29</td><td>8</td><td>6</td><td>15</td><td>3344</td><td>3400</td><td>-56</td><td>30</td><td>DDLLL</td></tr>
 <tr><td>26</td><td>Houston Rockets</td><td>28</td><td>8</td><td>3</td><td>17</td><td>3086</td><td>3230</td><td>-144</td><td>27</td><td>DWWLW</td></tr>
 <tr><td>27</td><td>Orlando Magic</td><td>30</td><td>7</td><td>5</td><td>18</td><td>3281</td><td>3406</td><td>-125</td><td>26</td><td>WWWWD</td></tr>
 <tr><td>28</td><td>San Antonio Spurs</td><td>28</td><td>7</td><td>3</td><td>18</td><td>3085</td><td>3370</td><td>-285</td><td>24</td><td>LDWWL</td></tr>
 <tr><td>29</td><td>Detroit Pistons</td><td>31</td><td>5</td><td>4</td><td>22</td><td>3441</td><td>3649</td><td>-208</td><td>19</td><td>LDLLL</td></tr>
 <tr><td>30</td><td>Charlotte Hornets</td><td>29</td><td>4</td><td>7</td><td>18</td><td>3194</td><td>3403</td><td>-209</td><td>19</td><td>LDLLL</td></tr>
</tbody></table>


_Note: I cut out parts of my script that automatically push the results to Google Sheets, but to make this table in a clean HTML format, I copied-and-pasted the spreadsheet result into [this tool](https://tableizer.journalistopia.com/)._

If you're curious, here are the top 4 teams of the past few seasons:

<u>**2021-22:**</u>

Phoenix Suns, 180 points

Memphis Grizzlies, 160 points

Miami Heat, 160 points,

Golden State Warriors, 153 points


<u>**2020-21:**</u>

Utah Jazz, 155 points

Brooklyn Nets, 140 points

Los Angeles Clippers, 139 points

Philadelphia 76ers, 135 points


<u>**2019-20:**</u>

Milwaukee Bucks, 166 points

Toronto Raptors, 151 points

Los Angeles Lakers, 141 points

Boston Celtics, 138 points


A quick R tutorial for web scraping and data processing.

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Creating a soccer-style table for the NBA

Third-year center Nick Richards is flourishing for the Charlotte Hornets.

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Nick Richards, the Putback King of Charlotte

It's really fun when an NBA player has a signature move of some sort, whether they're a Hall-of-Famer, a star, or just a role player-- something that other people are free to do, but they're just _better_ at. Jose Alvarado lurks out of bounds or behind referees during inbound plays, taking advantage of the other team's lack of attentiveness. Damian Lillard has the deep three (bonus points if it's the waning seconds of the final game of a playoff series). James Harden spammed the step-back three. Dirk Nowitzki had his one-legged fadeaway. 

But it's kind of rare for a role player to have a signature _dunk._ Sure, LeBron James has his tomahawk dunk-- but he's a superstar, possibly the greatest basketball player of all time. Of course he gets a signature dunk. But to me, that's why what Santi Aldama does is so amusing and satisfying.

If you've never heard of [Santi Aldama,](https://www.basketball-reference.com/players/a/aldamsa01.html) you're probably not alone. He's a second-year power forward out of Loyola University Maryland who barely played last season but has started 16 games for the Memphis Grizzlies this year in the absense of Jaren Jackson, Jr. His numbers don't jump off the page, but he's been very solid for the Grizzlies this year, vastly improved from his rookie season when he was so raw that the Grizzlies only trusted him to play 15+ minutes seven times.

In that rookie season, though, he had a couple of iconic moments. The first was his first career double-double. Ok, you're thinking, some random bench guy got 18 points and 10 rebounds in a game. Who cares? Well, that double-double came in the Grizzlies' 73-point victory over the Oklahoma City Thunder, the largest margin of victory in NBA history. That's a story he'll be able to tell forever.

The second, though, is this driving reverse dunk against the #1-seeded Phoenix Suns:

<iframe src="https://videos.nba.com/nba/pbp/media/2022/04/01/0022101155/611/2470cb07-b62a-c3d2-0cc7-69deacfed8a2_1280x720.mp4" title="Santi Aldama reverse dunk vs. Phoenix Suns" frameborder="0" allow="accelerometer; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

That was one of the defining moments of the Grizzlies' season that was full of defining moments. Remember, the team won 10 out of 11 games immediately after losing their All-NBA point guard Ja Morant to injury, then rattled off 11 straight wins when he returned. That got them back on track, but Aldama's dunk was the spiritual nail in the coffin for one of the most significant wins of the season. This win kept the possibility alive that this team might break the franchise win total record. (They eventually tied the 56-win mark that the legendary Grit-N-Grind squad set in 2013.)

But the focus that particular night was on Aldama. _He_ got a courtside interview immediately after the game. _He_ got to speak at the postgame press conference later on. And it was all because of the emphatic reverse dunk-- one that has become his signature-- that he borrowed from his fellow Spaniard.

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Santi Aldama having a signature dunk style is one of the best things about the NBA.</p>&mdash; chase (@deepfriedcouch) <a href="https://twitter.com/deepfriedcouch/status/1599566302896537600?ref_src=twsrc%5Etfw">December 5, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">gotta ask about this the next time he does media. he does always go reverse 😂</p>&mdash; Devin Walker (@Devin_Walker2) <a href="https://twitter.com/Devin_Walker2/status/1599816050903613440?ref_src=twsrc%5Etfw">December 5, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<blockquote class="twitter-tweet"><p lang="en" dir="ltr">He’s talked about it. Inspired by Rudy Fernandez. Drew wrote it up that night.</p>&mdash; Chris Herrington (@ChrisHerrington) <a href="https://twitter.com/ChrisHerrington/status/1599839199485562880?ref_src=twsrc%5Etfw">December 5, 2022</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

Rudy Fernández, a first-round pick in the 2007 draft, played for the Portland Trail Blazers and Denver Nuggets in the NBA before returning to Spain to play for Real Madrid. While not a Hall-of-Famer, he's got a more impressible résumé than most NBA players: he and Real Madrid have won EuroLeague twice, and while representing Spain, he's earned several gold medals at FIBA events and two Olympic silver medals. He's one of the greatest Spanish basketball players ever.  

But while European NBA players come pre-packaged with the reputation of being slow and unathletic, Fernández was such a prolific dunker that he participated in the 2009 Slam Dunk Contest and threw down a nasty jam on Dwight Howard in the Olympic Gold Medal match in 2008.

Here is Rudy Fernández throwing down the dunk that Aldama loves to emulate:

<iframe width="560" height="315" src="https://www.youtube.com/embed/pSsUwA_5ZCw" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

And here's a compilation I made of all of Aldama's reverse dunks in his career so far. Enjoy!

<iframe src="https://www.youtube.com/embed/pu6mcfwhtC8" title="Every reverse dunk Santi Aldama has ever thrown down - Memphis Grizzlies" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

Santi Aldama's go-to move is an homage to his fellow Spaniard, Rudy Fernández.

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Santi Aldama's signature reverse dunk

 _This is part 1 of a series covering the 13 voided trades that occurred in the NBA from 1992 to 2022. It is an adaptation of an episode of Backfired that I published on May 11, 2022. If you would like to listen to this series instead, you can either toggle to the "Episodes" section on this site or find your preferred podcast platform in the sidebar to the left._

# July 2nd, 1992 - Greg Kite

>Houston Rockets receive: Greg Kite

>Orlando Magic receive: 1993 second-round pick, 1996 second-round pick

The first voided trade in this series occurred in 1992. 

The Orlando Magic, just days after drafting Shaquille O’Neal, agreed to send their veteran center, Greg Kite, to the Houston Rockets in exchange for a couple of second-round picks. Kite was sad to be leaving Orlando, but he was very vocal when he was traded, defending the Magic GM Pat Williams and calling the trade “a vindication of one of the charges against Williams.” 

Per the _Orlando Sentinel,_ Pat Williams had been criticized for signing mediocre players like Kite, who had career averages of just 2.3 points and 3.2 rebounds, to long-term contracts at above-market-rate salaries.

(I haven’t looked into all of the contracts that Pat Williams offered, but when you’re running an expansion franchise, if you identify someone you want to play for your team— someone you think is a cultural fit— you’ve gotta sweeten the pot a little bit to entice them to play for a team that’s 100% going to win about 20 games. Maybe he went a little overboard.)

“I think with this trade, Pat Williams has been found not guilty of one of the charges levied against him by members of the media,” said Kite, “and that charge is that Pat Williams didn’t know what he was doing when he signed me and other players to long-term contracts. The Rockets seem to think that I am of some value. By signing me, the Magic had an asset.”

The Rockets gave Kite a physical and it turned out that he had an irregular heartbeat. They said no deal, which sent Kite back to Orlando, and that created a lot of extra work for the Magic’s front office to restructure contracts to be able to offer Shaq his rookie deal, which wound up being $17.4 million dollars, over four seasons. (This was before rookie scale contracts were introduced, so the Magic had to clear cap space and make a convincing offer to Shaq.)

Every voided NBA trade from 1992-2022 (Part 1/13)

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The voided Greg Kite trade from Orlando to Houston - July 2nd, 1992

You may be wondering, “Why is the NBA team located in Salt Lake City called the Utah Jazz?”

The reason is that they kept the team name from when the franchise relocated from their first home in New Orleans. “New Orleans Jazz” makes a whole lot more sense, but at this point, the team’s been in Utah for over 40 years. The Utah Jazz is an iconic brand. They would never change their name.


But what if they had to? I made a list of a few names that I think would be good for an NBA team in Utah. Not joke names like the Utah Mormons or Salt Lake Sister Wives, but a real list that I spent upwards of four minutes on.

1. The Utah Saints

   a. Of course, the Mormon church, The Church of Jesus Christ of Latter Day Saints is based in Salt Lake City, so that’s an easy one.

2. The Utah Bees or Honeybees

   a. Back in 1849, the Mormons claimed a large swath of the western United States, parts of Utah, Arizona, southern and eastern California, Oregon, Colorado, Wyoming, Idaho, and New Mexico, and called it the State of Deseret. Deseret is the word for a honeybee in the Book of Mormon.
   
   b. _The Deseret News_ is one of the major newspapers in Utah, sort of the state newspaper of the Mormon church. A [_Rodong Sinmun_](https://en.wikipedia.org/wiki/Rodong_Sinmun) for the most beautiful state in our fair nation, so to speak.

   c. There was also a minor league baseball team in Salt Lake called the Salt Lake City Bees. Cities love bringing back old minor league baseball or rugby team names from long ago like, for example, the New Orleans Pelicans.

3. The Utah Arches.

   a. Arches National Park is in Utah. This one is going along the same lines as naming a team the Denver Nuggets or Minneapolis Lakers— just naming the team after an environmental feature of the area.

   b. If the Colorado Rockies baseball team weren’t so close to Utah, I’d go with the Rockies. I’m ok with borrowing the “Saints” moniker since New Orleans is almost 2000 miles away from Salt Lake, but Utah and Colorado border each other.

Or, how about this— they lean into the absurdness of their existing name and call the team the Utah Funk.

The Utah Jazz shouldn't change their name. But what if they did?

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Alternative names for the Utah Jazz

[Olden Polynice](https://www.basketball-reference.com/players/p/polynol01.html) was the 8th overall pick out of Virginia in the 1987 NBA draft, initially drafted by the Chicago Bulls but immediately traded to the Seattle SuperSonics in exchange for the draft rights to Scottie Pippen. In a six-week span in the year 2000, while playing for the Utah Jazz, he got popped for impersonating a police officer twice, once in September and once in October.

I’ll start with the September one. This one happened first but came to light after the one in October was reported in the newspaper. There was a couple driving along in Salt Lake City when somebody in a Mercedes almost hit them. The man of the couple didn’t appreciate that, so he honked his horn and flipped off the car. The couple said the Mercedes began following them and tried to run them off the road, so they pulled over. 

The man driving the Mercedes, Polynice, also pulled over, got out of his car, and started arguing with the couple. He then pulled out a badge, got in the man’s face, and said, “I'm with the California Sheriff's Office and I can have you arrested.”

Polynice eventually got back in his car and sped off. The couple didn’t recognize him, so they just went on their way, no doubt a little freaked out that a 7-foot-tall police officer had just tried to run them off the road.

Six weeks later, in West Valley City, a suburb of Salt Lake City, a second couple was driving home. They turned on the blinker and slowed down to make a turn. The Mercedes following behind them (again driven by Polynice) didn’t slow down enough and almost rear-ended them. Polynice, angry, began to follow them, flashed his lights at the couple, pulled up beside them while driving, and brandished his badge again, all the while screaming at them, “I’m a cop, pull over!”

They didn’t. They kept driving home, and finally arrived at their apartment building. Polynice drove up, stepped out, and yelled at the couple, “I’m with the LAPD, don’t do that again!”

He then called the woman of the couple a bitch, threatened to arrest them, got in his car, said he was going to come back, left, and eventually was arrested. The news coverage on the second instance, which included a picture of Polynice, tipped off his first victims, who came forward and claimed that he had done a similar thing to them.

Polynice was charged with and pleaded guilty to both instances. The badge that he was flashing was an honorary LAPD badge that he got when he played for the Los Angeles Clippers ten years before. Polynice testified in court that he’d thrown away the badge, paid a fine, went to anger management, and was sentenced to 130 hours of community service.

One of the Salt Lake Tribune articles mentioned that in addition to those two times he was caught, one of the district attorneys brought up a time in July of 2000 (a couple of months before the first incident) when Polynice had flashed the badge at somebody during an argument at a nightclub. 

There’s no chance he just started carrying the badge 10 years after he got it. Who knows how many times Polynice has impersonated a police officer in his life? 

In a six-week span in the year 2000, while playing for the Utah Jazz, Olden Polynice got popped for impersonating a police officer twice.

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Olden (Pol)yn(ice)

Tom Gugliotta, also known as Googs, is one of my favorite 1990s NBA players, and I think I know why. A while back, I was watching a rerun of the [Vancouver Grizzlies’ first-ever home game](https://www.basketball-reference.com/boxscores/199511050VAN.html) back in 1995, which was a super exciting victory by the Grizzlies over the Minnesota Timberwolves. (There’s this awesome buzzer-beating tip-in in overtime by a guy named Chris King— definitely worth the watch.)

Googs was playing for the Wolves at the time, starting alongside Christian Laettner, so I must have subconsciously labeled him as the “good white guy” to Laettner’s “evil white guy.”

Gugliotta was selected 6th overall by the Washington Bullets out of NC State. He played for the Bullets for two full seasons, and then right after the beginning of his third season in Washington, he was sent to the Golden State Warriors for Chris Webber, who had just forced his way off of the Warriors after just one season due to a conflict with head coach Don Nelson. Just three months after Golden State acquired Gugliotta, they traded him to the Minnesota Timberwolves where he and Kevin Garnett were a really good 1-2 punch at the two forward spots for a few years. 

Just to give you an idea of the caliber of player that Gugliotta was at his peak, in his lone all-star season, 1997, he averaged 20.6 points, 8.7 rebounds, 4.1 assists (3.6 turnovers), 1.6 steals, and 1.1 blocks per game. He shot about the same amount of long 2s as he took shots at the rim and was pretty efficient from those spots, but he was never a good 3-point shooter. So, he was solid, for sure, but had some flaws.

But his biggest flaw was that he was allergic to the bag. Gugliotta left about $26 million on the table to leave the Minnesota Timberwolves for the Phoenix Suns in free agency after the lockout in 1999, in large part due to how tired he was of hearing Wolves starting point guard Stephon Marbury talk about how much he wanted to be a New York Knick and how annoying it was that Kevin Garnett was the star and the highest-paid player on the team. 

There’s a New York Post article I found that is so candid and funny in comparison to today’s basketball media landscape. One of the reasons I love reading articles from before the advent of social media and especially before the year 2000 is because some of these guys will just say anything on the record. Gugliotta rips into Marbury in this article.

Let’s jump to December 17th, 1999. Gugliotta had been playing for Phoenix for parts of two seasons at the point. The Suns were 15-7 and had gotten a new head coach, Scott Skiles, just days beforehand because Danny Ainge stepped down as head coach.

Ainge’s resignation was completely out of nowhere for most people. There were rumors that Jerry Colangelo forced him out or that Ainge was frustrated with the way the Suns were playing— something that Jason Kidd felt was the real reason— or that Scott Skiles had done a move that I like to call “The J.B. Bickerstaff” where you go behind the head coach’s back and undermine him and then you become the head coach, but Ainge maintains that one of his teenage sons told him he was becoming too distant and that he and his siblings wanted Danny to be at home more. He’d been missing holidays and major milestones, especially in his younger kids’ lives, which made him realize that at this moment, his family needed him more than the Suns did.

“I love coaching,” said Ainge, “but anybody can coach. My wife has just one husband and my children have just one father.  Some of you may think I’m jumping ship, well I’m diving overboard to save my family.”

Even with the abrupt coaching change, the Suns hadn’t skipped a beat in the transition to Skiles, who had been the lead assistant and was described in the Arizona Republic as “the bad cop to Ainge’s good cop.”

On the night of the 17th, the Suns won a road game against the Portland Trail Blazers to move up to the 5th seed in the Western Conference. After the game, the Suns got on the team bus to head to the airport to get back to Phoenix for their game against the Sacramento Kings the next night. 

Leading up to that game, Gugliotta had said he had had trouble sleeping after games, only getting to sleep at around 3:00 or 4:00 in the morning. He complained about that to a friend from high school, who told Gugliotta about a supplement he’d heard could help.

This supplement was sold under a lot of different names (including but not limited to ReActive, Verve, SomatoPro, Blue Nitro, Regenerize, Zen, Rejuv@Nite, Ultradiol, Enliven, N-force, Liquid Gold, Soma Solutions, Amino Flex, Dormir, and Rest-Q), but they were all the same substance, something called furanone di-hydro. Furanone di-hydro is an organic compound known as a gamma Butyrolactone, abbreviated as GBL. Once it is ingested, the human body transforms the GBL into a GHB— a date rape drug.

So these substances that were marketed to Gugliotta’s friend as a sleep supplement and were marketed more heavily as a strength enhancer, the latter of which made it semi-popular among bodybuilders and wrestlers, were actually something that sleazy guys slip into women’s drinks at parties.

That’s terrifying.

But what’s more terrifying is that it was perfectly legal for these companies to sell and market this dangerous substance in a number of different ways with absolutely no evidence backing up their claims of it being a natural, herbal sleep supplement because this substance, according to the Council for Responsible Nutrition, was found in trace amounts in some nuts and some melons.

That’s true more broadly as well, but this specific compound wasn’t banned because it wasn’t the date rape drug— it was something that sometimes turned into it. GHB was banned by FDA, but its precursor was not.

These companies were allowed to do that thanks to DSHEA, the Dietary Supplement Health and Education Act of 1994, which weakened the FDA’s ability to regulate supplements. That act allowed manufacturers to sell whatever they wanted without the same FDA approval that drugs require (if they were able to make their substance meet other requirements) because dietary supplements were deemed to be food instead of a drug. The result was, as Gugliotta said, these “supplements” didn’t have to undergo the clinical trials and peer-reviewed research proving them safe or effective to get on the market like a prescription drug would need, and in order to be taken off the market, they had to be proven unsafe— with numerous or at least notable cases of severe bodily harm or death causally linked to the supplement.

(You can thank a bipartisan effort in the Senate for DSHEA.)

Gugliotta’s friend, not having heard the news of date rapes and a handful of deaths at the hands of this particular supplement within the previous year, not having heard about the FDA reaching out to the manufacturers and advising them to voluntarily recall the product (which they did not do), bought a bottle and sent it to Gugliotta. 

The first time Gugliotta took the supplement, it worked like a charm, so after the win over the Blazers, he took it again, hopped on the bus, and called his wife. While they were on the phone, Gugliotta said that he began to feel like there was electricity coursing through his body. Then he started to hear a humming noise grow louder and louder. Then his face started twitching. Then he started to feel sick.

His wife said that Gugliotta eventually just started babbling, all the while getting quieter and quieter. Gugliotta says that with his last ounce of consciousness, he tried to end the call so his wife wouldn’t be scared but he dropped the phone as his head rolled back. The sound of Gugliotta dropping his phone onto the bus floor and his abnormal posture alerted his teammates to what was happening. Toby Bailey, a rookie guard on the Suns, rushed to Gugliotta and called for strength and conditioning coach Robin Pound.

Bailey and Pound started calling for an ambulance. The bus was still right outside of Portland’s Rose Garden, so the EMTs and the Trail Blazers’ team doctor were able to get onto the bus quickly and begin treating him. As he was being loaded into the ambulance, he began to have a seizure, and on the way to the hospital, he stopped breathing.

As Gugliotta notes in an article he wrote for ESPN The Magazine, because he seized up and stopped breathing, he was very lucky that he took the supplement when he was about to get on a bus surrounded by his teammates instead of on the airplane.

If they’d been on the plane and weren’t able to hook him up to a respirator relatively quickly, he may have died right there on the plane.

If they’d been going to a different road game and he took the supplement alone in the hotel room, he likely would have been found dead in his hotel room the next morning.

But because he was surrounded by his teammates and close to the EMTs, he lived.

Another thing that helped Gugliotta out was some quick thinking by his wife: he’d been on the phone with his wife, Nikki, and she heard the commotion that ensued and the calls for an ambulance. When she heard that, she called her friend, Rex Chapman’s wife. Chapman and Gugliotta had been teammates in Washington and now were reunited in Phoenix, so Chapman was on the bus with Gugliotta.

A game of Telephone broke out. Nikki Gugliotta called Rex Chapman’s wife and told her to tell Chapman that Tom had taken the supplement and that it was in his bag somewhere. Chapman got the phone call from his wife, and relayed the information to the EMTs. They rifled through his bag, found it, and once Gugliotta got to the hospital, the doctors were able to counteract that substance and save his life.

But it didn’t end there. His road to recovery took a couple of weeks. He was on the respirator for a few hours, completely unresponsive to any external stimulus. Gugliotta had multiple spinal taps performed on him to check him for meningitis, which he didn’t have, but those multiple spinal taps gave him a headache that persisted throughout his recovery. (The headaches were what kept him out of games in the end.)

13 days later, on December 30th, Gugliotta was cleared and he returned to play on January 4th against the Charlotte Hornets. Gugliotta said that his first game back was really rough because he was in a lot of pain and was out of shape. He missed all but one of his shots but grabbed 10 rebounds in 16 minutes of playing time. It took him a while to round back into form, but he had a good February and was really turning it on in March until he, unfortunately, tore the ACL and MCL in his left knee and was never the same after that. (He was 30 years old when he blew out his knee, but that certainly exacerbated his decline.)

Gugliotta returned after eight months and play parts of four more seasons in Phoenix, but his performance in that time was pretty lacking. His playing time was halved and he was no longer a starting-quality player. He went from averaging 15 points and 8 rebounds on league average or better efficiency to 5 points and 4 rebounds on below-average shooting. That’s unfortunate, but he was alive, and that’s what was important.

Right when he returned to the court, Gugliotta said, “I’m hoping something good can come out of this other than my recovery. If anybody is even thinking about this stuff, furanone di-hydro, there is no way the positives— if there even are any— can outweigh what can happen.” 

Something good did come out of it. The FDA was able to directly link furanone di-hydro to 19 cases of people who had either had a seizure or gone into a coma immediately after taking it, as well as 6 deaths. Then, in 2002, a Justice Department survey of emergency departments in 22 major US cities turned up just over 11,000 ER visits with mentions of furanone di-hydro from 1994-2000. It’s now been classified as a Schedule 1 controlled substance. As of 2021, only three manufacturers have DEA clearance to produce it, and in order to purchase it, you have to have DEA clearance as well. Its use for human consumption has been regulated out and now it’s primarily used as an ingredient in tire and rim cleaner, among other cleaning solutions.

Yes, you read that right— 25 years ago, the stuff you can pick up at AutoZone today was going into people’s bodies.

Tom Gugliotta, also known as Googs, is one of my favorite 1990s NBA players, and I think I know why. A while back, I was watching a rerun of the Vancouver Grizzlies’ first-ever home game back in 1995, which was a super exciting victory by the Grizzlies over the Minnesota Timberwolves. (There’s this awesome buzzer-beating tip-in in overtime by a guy named Chris King— definitely worth the watch.)

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