u/Exotic_Annual6314

Over the last 31 years, here are the "statistical" NBA archetypes and their centroid values :

# A quick guide to the 54 statistical player families DBB2 keeps finding

I have been building a box-score family map from NBA player seasons. The basic idea is simple: instead of starting with player names or narratives, group seasons by statistical shape.

The five-number block below is always:

`PTS / REB / AST / STL / BLK`

So a cluster like `15.3/3.3/2.8/1.0/0.2` means the average season in that family is roughly 15 points, 3 boards, 3 assists, 1 steal, and basically no blocks.

Important caveat: these are not total player evaluations. They do not capture film, role, scheme, defense away from the box score, era context, or coaching. They are box-score families. The useful question is not "are these players identical?" The useful question is "what kind of statistical season does this resemble?"

The labels are just plain-English handles. The stable parts are the cluster ID, stat block, size, and examples.

## Guard Families

- `PG_07` — Bench scoring guard. `9.2/2.3/2.7/0.7/0.1`; n=363. Example: John Starks 2000-01.

- `PG_09` — Mid-tier scoring point. `14.4/3.0/4.5/0.9/0.2`; n=270. Example: Dennis Schroder 2018-19.

- `PG_02` — Scoring combo guard. `15.3/3.3/2.8/1.0/0.2`; n=250. Example: Wesley Matthews 2013-14.

- `PG_04` — Low-usage reserve guard. `8.1/2.8/3.0/0.9/0.2`; n=246. Example: Norris Cole 2014-15.

- `PG_06` — Efficient rotation point. `10.1/2.6/3.5/0.9/0.2`; n=243. Example: Luke Ridnour 2012-13.

- `PG_01` — High-end scoring creator. `22.5/4.0/5.9/1.2/0.3`; n=205. Example: Jason Terry 2000-01.

- `PG_05` — Defense-plus table setter. `12.0/3.9/6.3/1.6/0.3`; n=186. Example: Marcus Smart 2021-22.

- `PG_10` — Prime lead guard. `17.1/3.8/6.9/1.4/0.2`; n=179. Example: Mike Bibby 1999-00.

- `PG_08` — Big defensive combo guard. `11.9/4.0/3.0/1.2/0.5`; n=132. Example: Bobby Phills 1995-96.

- `PG_03` — Star power guard. `22.0/5.6/7.1/1.8/0.5`; n=129. Example: Steve Francis 2002-03.

## Shooting Guard / Wing Families

- `SG_07` — Movement shooter wing. `11.3/3.2/1.6/0.7/0.3`; n=134. Example: Wesley Person 1995-96.

- `SG_09` — Low-usage 3-and-D guard. `9.1/3.5/1.9/0.9/0.3`; n=118. Example: Garrett Temple 2017-18.

- `SG_06` — Secondary scoring wing. `17.1/4.4/3.4/0.9/0.3`; n=117. Example: Michael Finley 2001-02.

- `SG_08` — Deep rotation wing. `7.9/3.1/1.6/0.7/0.3`; n=86. Example: Shandon Anderson 2003-04.

- `SG_01` — Stocks-and-scoring wing. `14.2/4.6/2.6/1.4/0.6`; n=68. Example: Walt Williams 1995-96.

- `SG_04` — Big connector wing. `10.6/5.2/2.3/1.2/0.6`; n=66. Example: Josh Childress 2006-07.

- `SG_10` — Elite scoring wing. `25.0/6.0/5.2/1.3/0.5`; n=64. Example: Vince Carter 2006-07.

- `SG_05` — Defensive glue wing. `7.9/4.2/1.9/1.0/0.5`; n=46. Example: Maurice Harkless 2013-14.

- `SG_03` — Big two-way scorer. `19.5/7.4/3.0/1.6/1.1`; n=29. Example: Rudy Gay 2015-16.

- `SG_02` — Point-forward wing. `15.0/6.3/5.8/1.6/0.6`; n=21. Example: Andre Iguodala 2008-09.

## Small Forward Families

- `SF_04` — Low-usage spacing forward. `9.7/3.8/1.5/0.7/0.3`; n=271. Example: Chris Mills 1997-98.

- `SF_06` — Scoring frontcourt role player. `10.6/5.3/1.3/0.7/0.5`; n=244. Example: Shareef Abdur-Rahim 2006-07.

- `SF_01` — Classic scoring forward. `17.5/7.9/2.7/0.9/0.6`; n=202. Example: Luol Deng 2009-10.

- `SF_02` — Stretch scoring forward. `16.1/5.3/2.3/0.9/0.4`; n=187. Example: Lamond Murray 2001-02.

- `SF_03` — Low-usage glue forward. `7.2/4.2/1.5/0.8/0.5`; n=187. Example: Devean George 2001-02.

- `SF_10` — 3-and-D rebound wing. `11.5/5.5/2.2/1.3/0.6`; n=154. Example: P.J. Tucker 2013-14.

- `SF_05` — All-star scoring forward. `21.7/6.4/4.1/1.4/0.6`; n=140. Example: Paul Pierce 2004-05.

- `SF_07` — Rebound-first defensive forward. `9.4/6.9/1.5/0.8/0.8`; n=128. Example: Trevor Booker 2011-12.

- `SF_08` — Young big forward / stocks forward. `15.0/8.1/2.8/1.1/1.7`; n=80. Example: Kevin Garnett 1996-97.

- `SF_09` — Superstar point forward. `26.3/9.0/6.1/1.3/1.0`; n=54. Example: LeBron James 2015-16.

## Power Forward Families

- `PF_11` — Rotation scoring big. `10.6/6.1/1.2/0.5/0.8`; n=117. Example: Jordan Hill 2015-16.

- `PF_08` — Rim-running defense big. `8.7/7.1/1.2/0.7/1.1`; n=89. Example: Dale Davis 2002-03.

- `PF_12` — Workhorse role big. `9.7/7.5/1.4/0.8/0.8`; n=82. Example: P.J. Brown 1998-99.

- `PF_07` — Scoring/rebounding power forward. `18.3/8.8/2.3/0.8/0.9`; n=76. Example: Joe Smith 1996-97.

- `PF_03` — Passing utility big. `12.1/7.0/2.8/0.9/0.8`; n=65. Example: Brad Miller 2001-02.

- `PF_10` — Franchise two-way big. `22.0/11.2/2.6/0.9/2.1`; n=62. Example: Tim Duncan 1998-99.

- `PF_01` — Stretch role big. `9.5/4.9/1.6/0.6/0.6`; n=54. Example: Channing Frye 2013-14.

- `PF_02` — Low-usage rebound big. `6.0/6.2/1.0/0.6/0.6`; n=47. Example: Antonio McDyess 2009-10.

- `PF_09` — Shot-blocking scorer big. `13.9/8.5/1.7/0.8/2.2`; n=43. Example: Elden Campbell 1999-00.

- `PF_04` — Hub big / passing rebounder. `18.5/10.5/4.6/1.1/1.0`; n=34. Example: Domantas Sabonis 2020-21.

- `PF_06` — Rasheed-style stretch defender. `15.9/7.4/2.5/1.0/1.1`; n=30. Example: Rasheed Wallace 2004-05.

- `PF_05` — Ben Wallace defensive anchor. `8.4/10.9/1.6/1.4/2.0`; n=18. Example: Ben Wallace 2004-05.

## Center Families

- `C_08` — Backup rim protector. `6.3/6.9/0.9/0.5/1.2`; n=73. Example: Steven Adams 2014-15.

- `C_02` — Traditional scoring center. `14.0/8.1/1.6/0.5/1.0`; n=71. Example: Bryant Reeves 1995-96.

- `C_07` — Efficient rim-runner center. `9.5/7.7/0.9/0.4/1.4`; n=71. Example: Jarrett Allen 2018-19.

- `C_05` — Mid-rotation shot blocker. `8.6/5.7/1.2/0.5/1.2`; n=64. Example: Andrew Lang 1995-96.

- `C_06` — Double-double rim center. `10.7/10.2/1.1/0.7/1.7`; n=59. Example: Emeka Okafor 2010-11.

- `C_01` — Two-way starting center. `12.8/9.8/1.7/0.9/1.5`; n=53. Example: David Robinson 2002-03.

- `C_04` — High-end scoring rim protector. `18.6/9.4/1.9/0.7/1.9`; n=48. Example: Patrick Ewing 1995-96.

- `C_12` — Veteran utility center. `9.1/7.1/1.8/0.9/1.0`; n=38. Example: Horace Grant 1997-98.

- `C_10` — Jokic/Sengun passing center. `18.6/9.6/4.5/1.2/1.1`; n=37. Example: Nikola Jokic 2017-18.

- `C_09` — Elite rebounding shot blocker. `12.4/10.7/1.0/0.6/2.9`; n=30. Example: Dikembe Mutombo 1996-97.

- `C_03` — Skilled stretch center. `13.3/7.1/1.6/0.6/0.8`; n=16. Example: Arvydas Sabonis 1996-97.

- `C_11` — Shaq-tier interior force. `25.8/11.4/3.0/0.6/2.4`; n=10. Example: Shaquille O'Neal 2000-01.

The vintage angle is the fun part. Some of these are obvious: `C_11` is basically the Shaq family, `PF_10` is the Duncan family, `SF_09` is the LeBron family. But the more useful families are often the less glamorous ones: the Dale Davis / P.J. Brown / Antonio McDyess types, the Andre Iguodala connective wings, the Bobby Phills defensive guards, the Brad Miller passing bigs.

That is why I like this lens. It does not say the box score explains everything. It just gives old and new seasons a common language before the narrative takes over.

1

Over the last 31 years, here are the "statistical" NBA archetypes and their centroid values :

# A quick guide to the 54 statistical player families DBB2 keeps finding

I have been building a box-score family map from NBA player seasons. The basic idea is simple: instead of starting with player names or narratives, group seasons by statistical shape.

The five-number block below is always:

`PTS / REB / AST / STL / BLK`

So a cluster like `15.3/3.3/2.8/1.0/0.2` means the average season in that family is roughly 15 points, 3 boards, 3 assists, 1 steal, and basically no blocks.

Important caveat: these are not total player evaluations. They do not capture film, role, scheme, defense away from the box score, era context, or coaching. They are box-score families. The useful question is not "are these players identical?" The useful question is "what kind of statistical season does this resemble?"

The labels are just plain-English handles. The stable parts are the cluster ID, stat block, size, and examples.

## Guard Families

- `PG_07` — Bench scoring guard. `9.2/2.3/2.7/0.7/0.1`; n=363. Example: John Starks 2000-01.

- `PG_09` — Mid-tier scoring point. `14.4/3.0/4.5/0.9/0.2`; n=270. Example: Dennis Schroder 2018-19.

- `PG_02` — Scoring combo guard. `15.3/3.3/2.8/1.0/0.2`; n=250. Example: Wesley Matthews 2013-14.

- `PG_04` — Low-usage reserve guard. `8.1/2.8/3.0/0.9/0.2`; n=246. Example: Norris Cole 2014-15.

- `PG_06` — Efficient rotation point. `10.1/2.6/3.5/0.9/0.2`; n=243. Example: Luke Ridnour 2012-13.

- `PG_01` — High-end scoring creator. `22.5/4.0/5.9/1.2/0.3`; n=205. Example: Jason Terry 2000-01.

- `PG_05` — Defense-plus table setter. `12.0/3.9/6.3/1.6/0.3`; n=186. Example: Marcus Smart 2021-22.

- `PG_10` — Prime lead guard. `17.1/3.8/6.9/1.4/0.2`; n=179. Example: Mike Bibby 1999-00.

- `PG_08` — Big defensive combo guard. `11.9/4.0/3.0/1.2/0.5`; n=132. Example: Bobby Phills 1995-96.

- `PG_03` — Star power guard. `22.0/5.6/7.1/1.8/0.5`; n=129. Example: Steve Francis 2002-03.

## Shooting Guard / Wing Families

- `SG_07` — Movement shooter wing. `11.3/3.2/1.6/0.7/0.3`; n=134. Example: Wesley Person 1995-96.

- `SG_09` — Low-usage 3-and-D guard. `9.1/3.5/1.9/0.9/0.3`; n=118. Example: Garrett Temple 2017-18.

- `SG_06` — Secondary scoring wing. `17.1/4.4/3.4/0.9/0.3`; n=117. Example: Michael Finley 2001-02.

- `SG_08` — Deep rotation wing. `7.9/3.1/1.6/0.7/0.3`; n=86. Example: Shandon Anderson 2003-04.

- `SG_01` — Stocks-and-scoring wing. `14.2/4.6/2.6/1.4/0.6`; n=68. Example: Walt Williams 1995-96.

- `SG_04` — Big connector wing. `10.6/5.2/2.3/1.2/0.6`; n=66. Example: Josh Childress 2006-07.

- `SG_10` — Elite scoring wing. `25.0/6.0/5.2/1.3/0.5`; n=64. Example: Vince Carter 2006-07.

- `SG_05` — Defensive glue wing. `7.9/4.2/1.9/1.0/0.5`; n=46. Example: Maurice Harkless 2013-14.

- `SG_03` — Big two-way scorer. `19.5/7.4/3.0/1.6/1.1`; n=29. Example: Rudy Gay 2015-16.

- `SG_02` — Point-forward wing. `15.0/6.3/5.8/1.6/0.6`; n=21. Example: Andre Iguodala 2008-09.

## Small Forward Families

- `SF_04` — Low-usage spacing forward. `9.7/3.8/1.5/0.7/0.3`; n=271. Example: Chris Mills 1997-98.

- `SF_06` — Scoring frontcourt role player. `10.6/5.3/1.3/0.7/0.5`; n=244. Example: Shareef Abdur-Rahim 2006-07.

- `SF_01` — Classic scoring forward. `17.5/7.9/2.7/0.9/0.6`; n=202. Example: Luol Deng 2009-10.

- `SF_02` — Stretch scoring forward. `16.1/5.3/2.3/0.9/0.4`; n=187. Example: Lamond Murray 2001-02.

- `SF_03` — Low-usage glue forward. `7.2/4.2/1.5/0.8/0.5`; n=187. Example: Devean George 2001-02.

- `SF_10` — 3-and-D rebound wing. `11.5/5.5/2.2/1.3/0.6`; n=154. Example: P.J. Tucker 2013-14.

- `SF_05` — All-star scoring forward. `21.7/6.4/4.1/1.4/0.6`; n=140. Example: Paul Pierce 2004-05.

- `SF_07` — Rebound-first defensive forward. `9.4/6.9/1.5/0.8/0.8`; n=128. Example: Trevor Booker 2011-12.

- `SF_08` — Young big forward / stocks forward. `15.0/8.1/2.8/1.1/1.7`; n=80. Example: Kevin Garnett 1996-97.

- `SF_09` — Superstar point forward. `26.3/9.0/6.1/1.3/1.0`; n=54. Example: LeBron James 2015-16.

## Power Forward Families

- `PF_11` — Rotation scoring big. `10.6/6.1/1.2/0.5/0.8`; n=117. Example: Jordan Hill 2015-16.

- `PF_08` — Rim-running defense big. `8.7/7.1/1.2/0.7/1.1`; n=89. Example: Dale Davis 2002-03.

- `PF_12` — Workhorse role big. `9.7/7.5/1.4/0.8/0.8`; n=82. Example: P.J. Brown 1998-99.

- `PF_07` — Scoring/rebounding power forward. `18.3/8.8/2.3/0.8/0.9`; n=76. Example: Joe Smith 1996-97.

- `PF_03` — Passing utility big. `12.1/7.0/2.8/0.9/0.8`; n=65. Example: Brad Miller 2001-02.

- `PF_10` — Franchise two-way big. `22.0/11.2/2.6/0.9/2.1`; n=62. Example: Tim Duncan 1998-99.

- `PF_01` — Stretch role big. `9.5/4.9/1.6/0.6/0.6`; n=54. Example: Channing Frye 2013-14.

- `PF_02` — Low-usage rebound big. `6.0/6.2/1.0/0.6/0.6`; n=47. Example: Antonio McDyess 2009-10.

- `PF_09` — Shot-blocking scorer big. `13.9/8.5/1.7/0.8/2.2`; n=43. Example: Elden Campbell 1999-00.

- `PF_04` — Hub big / passing rebounder. `18.5/10.5/4.6/1.1/1.0`; n=34. Example: Domantas Sabonis 2020-21.

- `PF_06` — Rasheed-style stretch defender. `15.9/7.4/2.5/1.0/1.1`; n=30. Example: Rasheed Wallace 2004-05.

- `PF_05` — Ben Wallace defensive anchor. `8.4/10.9/1.6/1.4/2.0`; n=18. Example: Ben Wallace 2004-05.

## Center Families

- `C_08` — Backup rim protector. `6.3/6.9/0.9/0.5/1.2`; n=73. Example: Steven Adams 2014-15.

- `C_02` — Traditional scoring center. `14.0/8.1/1.6/0.5/1.0`; n=71. Example: Bryant Reeves 1995-96.

- `C_07` — Efficient rim-runner center. `9.5/7.7/0.9/0.4/1.4`; n=71. Example: Jarrett Allen 2018-19.

- `C_05` — Mid-rotation shot blocker. `8.6/5.7/1.2/0.5/1.2`; n=64. Example: Andrew Lang 1995-96.

- `C_06` — Double-double rim center. `10.7/10.2/1.1/0.7/1.7`; n=59. Example: Emeka Okafor 2010-11.

- `C_01` — Two-way starting center. `12.8/9.8/1.7/0.9/1.5`; n=53. Example: David Robinson 2002-03.

- `C_04` — High-end scoring rim protector. `18.6/9.4/1.9/0.7/1.9`; n=48. Example: Patrick Ewing 1995-96.

- `C_12` — Veteran utility center. `9.1/7.1/1.8/0.9/1.0`; n=38. Example: Horace Grant 1997-98.

- `C_10` — Jokic/Sengun passing center. `18.6/9.6/4.5/1.2/1.1`; n=37. Example: Nikola Jokic 2017-18.

- `C_09` — Elite rebounding shot blocker. `12.4/10.7/1.0/0.6/2.9`; n=30. Example: Dikembe Mutombo 1996-97.

- `C_03` — Skilled stretch center. `13.3/7.1/1.6/0.6/0.8`; n=16. Example: Arvydas Sabonis 1996-97.

- `C_11` — Shaq-tier interior force. `25.8/11.4/3.0/0.6/2.4`; n=10. Example: Shaquille O'Neal 2000-01.

The vintage angle is the fun part. Some of these are obvious: `C_11` is basically the Shaq family, `PF_10` is the Duncan family, `SF_09` is the LeBron family. But the more useful families are often the less glamorous ones: the Dale Davis / P.J. Brown / Antonio McDyess types, the Andre Iguodala connective wings, the Bobby Phills defensive guards, the Brad Miller passing bigs.

That is why I like this lens. It does not say the box score explains everything. It just gives old and new seasons a common language before the narrative takes over.

1

I’m building `StockArithm`, a public paper-trading lab where market signals compete in public instead of hiding behind backtests.

The value prop is simple: most trading signals look good until they have to survive in public. StockArithm keeps the winners and losers visible, ranks them against SPY, and shows what is actually holding up instead of only showing the nice-looking ideas.

If you’re interested in transparent research products, public scoreboards, or building trust by showing failures instead of hiding them, take a look at `stockarithm.com`.

StockArithm

https://preview.redd.it/a8am6idxdw3h1.png?width=2880&format=png&auto=webp&s=186a84aa9cb44d4f604c599abf542d951f45be3a

I've been building a public paper-trading project called StockArithm that runs sector rotation signals off alternative economic data.

Not price patterns. Not earnings calls. Stuff like TSA checkpoint counts, bankruptcy filing rates, freight rail carloads, electricity demand, Google Trends, and sentiment/activity proxies.

Everything is paper-traded. Everything is public. No cherry-picking, no hiding the body count.

Current numbers

- 215 signals running live

- 1 beating SPY on full-window alpha

- 1 beating SPY on rolling 30D

- 214 flat, collecting data, or underperforming

I'll say that again: 1 out of 215. I'm not hiding that.

With 215 signals, I fully expect some to look decent by chance in a small sample. That's part of why I keep the full board public instead of just showing the winners.

How it works

Each signal is one alternative data source wired to a fixed sector-rotation rule.

- data source fires

- algo rotates into a target sector ETF or cash

- entry and exit rules are fixed

- SPY is the benchmark

- no discretionary overrides once the rule exists

The data sources right now include FRED macro series, TSA checkpoint tables, AAR freight rail carloads, EIA electricity consumption, Port of LA TEU volume, Google Trends, and sentiment/activity proxies.

I keep two rankings on purpose:

- Force rank = full-window / since-seed total return and alpha

- Rolling 30D = recent return, Sharpe, and drawdown

That split matters because a signal can look decent over a short stretch and still have a weak long-run record.

The ones worth talking about

Best full-window result right now: Quantified Simple Monthly Rotation at 10.03% return and +1.77% alpha vs SPY.

Best rolling 30D result right now is also Quantified Simple Monthly Rotation, at 10.03% over the last 30 days. It is still trailing SPY over the same window by 0.92%.

The one people seem to remember is Biscotti (Unconditional Loyalty). It is named after my dog. Right now it is at -0.94% over the last 30 days, and still -12.21% alpha on the full window. Good stretch

earlier, bad long-run record overall. I still can't tell whether that's a real regime change signal or just noise.

Worst on the board right now: Chaos Rotation Lab at -6.2% return and -14.46% alpha.

Still running it.

If I kill a signal every time it looks bad over a short window, then the whole thing just turns into survivorship bias theater.

What I actually want feedback on

1. Is the force-rank / rolling-30D split the right way to separate long-run trust from short-term regime fit, or does it just create a second window that I can unconsciously shop for the better-looking result?

2. For low-frequency macro signals that may have only fired a few times so far, would you keep them on the leaderboard this early, or exclude them until they have a real sample of trades?

Everything is public at stockarithm.com. Winners, losers, flat names, all of it.

If you want, I can also give you a shorter version in case you want to post something tighter.