This guy is super consistent and gets undrafted every single year. I added him again for the 2nd straight year and I love it. So what if he's boring and isn't "great" at anything. He's a decent scorer, gets a solid amount of boards, can make 3's and he doesn't hurt your percentages. Everyone is looking for lower tier C's and he doesn't have the flaws that someone like Maluach or Missi have, and people spent draft capital on these guys, at least Maluach. Nobody drafts WCJ. You can just get him for free and he will outproduce both of them.

Am I the only one a bit disappointed with Amen so far in 9CAT? Maybe I’m delusional but I expected some more stocks and less turnovers. In my draft he fell to pick 25 so I felt like it was good value. Would love to hear others’ thoughts.

I can see his role continuing to expand in LA. I wish i had picked him up. He’ll be a beast this season, and he’s definitely worth a flier right now to see how he progresses.

not confirmed but he was bothered by it during the game

https://basketnews.com/news-258207-anthony-davis-suffers-new-potential-alarming-injury-in-wizards-game.html

Anyone adding him?

Brooklyn needs a PG and Egor Demin sucks (IMO)

Ben Saraf also had some nice games late last year as the starting PG

Look, I'm so torn up abt him. In what world are u not playing ur franchise player 25+ mins. I get that the bulls have been mid asf, and there's been blowouts but cmon now. Idk if theres any experts in terms of roster rotations and that, but Splitter seems to be still figuring out rotations. That should have been done during preaseason, so if anyones got ideas I'd love to hear them below. I am holding him as we never sell a player this low, but man ts is frustrating.

I know the Rockets are looking mad good right now, for ROS who holds more value fantasy wise, fred or reed? Haven't watched rockets games. Fred is the offensive leader for the rockets but his fg% is criminal.

So for sleeper lock in if someone is playing today, I should always swap them into my starting lineup with someone not playing today right? Just so I could lock it in in case they do really good?

What is the general sentiment around Hart? I got him late around pick 90 and have enjoyed his production so far, but I think he is a sell high and an injury risk. Mikal should eat away at his stats a little bit once he gets going and his finger is a career ender if it gets reaggravated. Just wanted to hear thoughts on this since it seems a lot of people don’t share my view.

I wanted to share an article I wrote on a better way to analyze trades for 9cat fantasy basketball. If you want to read it in the format with images you can see it here:

https://ratball.ca/articles/how-to-analyze-fantasy-basketball-trades

A great way to analyze a trade in a head-to-head category league is to measure what it does to your team's chance of winning each category. This may seem obvious, but many trade analysis tools measure trades by who wins more "Z-scores", which is a very flawed way to see if you should make a trade.

This superior method evaluates the trade by representing each team with a probability distribution for each category. The probability distribution for each team is made of the probability distributions of all players on that team. You can easily compare the team level distributions to get a win % for that category.

Then, you swap the distributions of each player being traded to the teams they are being traded to, and recalculate the win %. The difference is the win % impact the trade has on your team.

The common alternative, adding up Z-scores for each side, gets this wrong in a predictable way. A Z-score total gives a player one fixed value, no matter which team he's on. But the same production is worth a lot in a category where your team is in the middle of the pack, and very little in a category you already win almost every week. Where your team stands decides what a player is worth to you, and it gets ignored by Z-scores.

A trade where both teams win

Because a player's value depends on the team, a trade between two teams isn't zero-sum. Each side can give up production it doesn't need for production it does, and both teams can come out ahead.

To find an example, I searched the same rosters for one-for-one trades between players of nearly identical overall value. One of the clearest win-wins was Alperen Sengun for Jalen Brunson. By Z-scores, the two were very even: Sengun at +1.35, Brunson at +1.36, ranked 30th and 29th (this was mid last season). When traded, according to category win%, both teams improved: +6.2% for the team that gets Sengun and +4.7% for the team that gets Brunson.

https://imgur.com/a/jCycxCc

The team that gets Sengun shows exactly why. It was winning threes 89% of the time and points 79% of the time, so giving up Brunson's scoring and shooting cost it only 10 and 8 points of win%. In return it gained 16 points in rebounds (from 49%) and 12 in blocks (from 33%). The team that gets Brunson gains in categories where it was behind: threes (from 22%), free throws (from 39%) and points (from 39%).

A Z-score total would call this trade a wash for both sides. Instead, it's a win for both.

A player's value to different teams

To demonstrate how each player gives different value to each team, I took one player, Josh Giddey, and added him to every roster in a sample league, then calculated how much each team's win% went up in each category.

Some teams gained a lot and some gained very little. For a team that was already winning points, rebounds and assists most weeks, he added +9.5% in total category win%. For a team that was behind in those categories, he added +51.7% across all categories.

https://imgur.com/a/iukx33N

Your category strengths decides what a player is worth

I repeated the same test in eight leagues, adding him to every roster. Here are some of the results:

In a category a team was already winning more than 80% of the time, he was worth less than half of his usual gain. In a category the team was winning 20% to 40% of the time, he was worth the most.

The teams' probability distributions show why; a team that already wins a category is ahead of almost everyone, so extra production helps them pass fewer teams. A team in the middle of the pack has opponents close by, and extra production moves it past many of them.

https://imgur.com/a/gFGilDB

Real matchups show the same effect

To confirm the effect holds in real matchups, I went back to 500 real head-to-head matchups from the 2025-26 season in eight leagues: 4,315 weekly category results. For each one, I calculated how many Z-scores one team was projected to be ahead in that category, using averages based on only games played before that week, and recorded who actually won.

The lead is measured in Z-scores: the projected gap between the two teams' weekly totals, divided by the category's per-game standard deviation (Z-scores). In points, one standard deviation is about 6 points, so a team projected to score 100 more points than its opponent that week leads by about 17 Z-scores.

https://imgur.com/a/mlDuAHc

When the projected lead was under 4 Z-scores, the team with the lead won only 53% of the time. With a 16 to 20 Z-score lead it won 75% of the time, and with a 36 to 40 Z-score lead, 88.5%. One more Z-score of projected lead added 1.4% to a team's chance of winning an even category, 1.0% at a 20 Z-score lead, and 0.5% at a 40 Z-score lead, about a third as much. In real results, as in the model, production is worth the most where the matchup is close.

All the data comes from eight public ESPN head-to-head category leagues from the 2025-26 season: five 9-category leagues and three 8-category leagues without turnovers.

ESPN league IDs: 312218237, 10287961, 1482931495, 1801165221, 832393914, 1382487116, 1609319867, 150

How probability distribution-based trade analysis works

This is the calculation RatBall's Trade Analyzer runs for your league.

1. Each player's single-game distributions

Every player gets a probability mass function (PMF) for each category, built from his (2025-2026) game logs: how often he scored each possible number of points, blocks, threes and so on in a single game. FG% and FT% use makes and attempts together, so a high-volume shooter moves a team's percentage more than a low-volume one.

https://imgur.com/a/AGqXi8e

2. Each team's week

A player's single-game distribution is combined with itself over the games he plays in a week. Then every player's weekly distribution on a roster is combined (convolved) into one weekly distribution per category for the whole team.

3. Win% in every category

The team's weekly distribution in each category is compared with every other team's, giving its chance of beating each one in a matchup week, with a tie counting as half a win. Averaged over every opponent, that's the team's win% in the category. It already reflects where the team stands: a team far ahead of most of the league in a category has a high win% there, and little left to gain.

4. Swap the players and compare

The traded players switch teams, both rosters are rebuilt, and the win% in every category is calculated again. The change in each category, added up across the categories your league scores, is the trade's Total Win% Change. Because each team is measured against the whole league, both teams can come out ahead.

Analyze your trades

A trade doesn't have a value of its own. It has a value to your team, in your league, and the best way to measure it is the way your matchups are decided: category win percentage. Comparing Z-score misses what's really important, and can lead to trades that make your team worse.

RatBall's Trade Analyzer runs this calculation on your own league. Connect your league, pick the players on each side, and it builds every team's weekly distributions from the rosters, swaps the players, and shows how the trade changes your win% in every category. It shows the same for the other team, and puts the Z-score comparison next to it, so you can see exactly where the two disagree.

How are we feeling about Aaron Gordon? Is he rosterable in a 10T Points league? He seems to fit in as #3 or #4 option after Murray and Jokic and gets the playing time. He's inconsistent and injury-prone but so far, he looks healthy. How would you evaluate them against someone Podz or FVV, who are somewhere in the >100

Haven't seen much discussion of Bey this year, as I don't recall his name coming up much during pre-draft analysis despite the 3-year/$55m extension indicating some level of commitment from ownership.

Final 3 months of last season: 20-5-3, 2.5 triples, 46% / 86% (on 5 FTA) in 32 mins. Good enough for top 50 in 9cat over the last 38 games, with Dejounte back in the lineup for a chunk of those.

Mathurin's arrival presented the only new threat, but he's averaging 18 mins and looks terrible. So Saddiq's mins are down (24) yet he's hanging on to late-round value thanks to high usage: 16-4-1, 2.3 triples, 50% / 83% (4 FTA). Boring safe end of bench stuff.

Now it appears Missi could be out long term, presumably forcing Pels into some smaller rotations and Bey seems like an obvious beneficiary in this scenario. Probably needs 28 mins to be a top 100 player. Am I crazy for thinking he's worth getting ahead of as a 9cat pickup?

We’ve been trashing them but looks like they took our complaints and improved the layout of the team page. We have pictures back!

The board now moves with the season. Two things changed.

1. The Live price

Every player already had two prices that never change: the IPO price (where the pre-draft boards had him) and the MARK (where he finished after his first season). The new Live price is a third one. It asks what each player would be priced at today if his class were re-ranked on this season’s games so far.

The formula is the same one that sets the MARK, run on current stats:

• Per game: PTS + 0.7×REB + 1.5×AST + 1.8×STL + 1.8×BLK − TO
• Multiplied by (games played ÷ his team’s games)^0.25, so a player who’s missed time gets a gentle haircut and not a punishing one
• Multiplied again by games played ÷ 10 if he has fewer than 10 games, so a hot two-game start can’t vault anyone to #1

Players are then ranked inside their own draft class on that class’s price ladder, where #1 = $1,000. Live never changes the IPO or MARK, so you can always see where a player started, where he finished and where he is right now. Anyone under 15 games gets a SMALL SAMPLE tag, and a player with no games yet shows a dash. The numbers refresh every morning after the previous night’s games are in.

2. 9C EPS and Per-36 are now in-season NBA numbers

These columns used to be pre-draft college and overseas production. On the quote boards they now come from this season’s NBA stats, the same data the Live price uses. (The pre-draft versions are still on each player’s page, labelled pre-draft.)

9C EPS is a nine-category z-score. For each category, a player’s per-game number is compared with the other players in his class who have played, measured in standard deviations from that group’s average. Then the categories are weighted and added up:

• Full weight (1.0) on points, rebounds, assists, steals, blocks and threes made
• 0.6 on FG%, 0.25 on FT%
• 0.15 on turnovers, flipped so fewer is better

Per-36 does the same thing on a per-36-minute basis. Each counting stat is scaled to 36 minutes first, so a bench player who produces in limited minutes isn’t buried by his role. The result is then re-centred to the same average and spread as 9C EPS, so the two columns are directly comparable.

Caveats

• We’re only a handful of games in, so everything swings a lot. Treat early numbers as a snapshot, not a verdict.
• Each class is only measured against its own players. A 9C EPS of +5 in the 2026 class and +5 in the 2021 class are not the same thing, and older classes have smaller groups.
• Players who haven’t played yet show dashes, and the incoming 2027 class keeps its pre-draft numbers.

Also cleaned up the quote board: Post-SL, PEM and LTSU are no longer columns (the PEM and LTSU gauges are still on each player page).

thedraftstockexchange.com. Feedback welcome, especially on the weights.

who yall got going crazy tonight? Im trying figure out what’s going be my team for underdog draft

Is Kuminga low-key a valuable asset in a 12T CAT league? I know his numbers look underwhelming but 12/6/3 with 2 steals and 46 FG% and 3PT% seems like too good to stay in FA, especially on a busy schedule like this week (MIN has 4 games). What do yo think?

Impressed me during that Pistons' game. Embiid did not play, but I don't think Wade's playing time is tied to whether Embiid plays or not. Lots of mouths to feed on that offense, but Wade plays with the second unit and it seems like he has a greenlight. Thoughts?

Sharpe looked like a solid breakout candidate coming into the season, with a clear path to starting minutes and strong per-minute rebounding and defensive production.

His minutes through four games are concerning:

Oct 21: 30 minutes
Oct 24: 23 minutes (ejected)
Oct 25: 16 minutes (blowout)
Oct 27: 17 minutes (OT loss)

The ejection and blowout are understandable, but 17 minutes in a competitive OT game is harder to explain.

Moritz Wagner played 22 minutes against Boston, putting up 15 points while Sharpe finished with 4 points and 6 boards. Sharpe had four fouls, but Wagner increasingly looks like legitimate competition for minutes.

At 27–30 MPG, Sharpe has plenty of fantasy appeal, particularly in points leagues. At 18–22, he’s probably waiver fodder in standard leagues.

Is this early-season rotation tinkering, a matchup issue, or the beginning of a genuine timeshare? What’s everyone expecting for his minutes and role ROS?

Can someone fill me in on wtf is going on to start the season? I drafted him in the fourth round at his ADP after hearing he’d be one of the best centers in the league but he’s getting 20 minutes a game and killing me here so far. Am I missing something with this guy? (Never paid much attention to him or Portland before)

What are we thinking about Toumani Camara this season? He’s been off to a really strong start but is it sustainable for the rest of the season? I haven’t watched Portland this season so I really don’t know much about how it’s going there

Mostly doing this post to bring back the nicknames trend in this thread, but what are your thoughts on this guy ROS?

Reminds me of RoCo. Bad FG but a monster on D. Currently averaging 2 stls and 2 blks after 4 games. Even though he’s not starting, he’s getting 30 minutes consistently. 21 years young, so hopefully his shot will improve as the season goes. Go grab him if you can stomach his FG.

Daily points league discussion, you should note how many teams are in your league when asking for advice. Please try to respond to other people’s questions if asking a question yourself.