Relationships & Traits

MidKnight · 10-29-2020, 07:56 PM

At its heart, OOTP is a narrative machine. It allows us to simulate baseball games in increasingly complex ways. We can revisit the past in historical leagues, exploring fantastic "what-if" scenarios. It allows us to imagine a world in which the injury-prone superstar never loses a step or one where Willie Mays plays alongside Mike Trout. We can even create our own worlds filled with imagined players, cities, rivalries, and more.

Over time, OOTP has gotten better at helping our imaginations to craft stories. We can see the players dive for balls. We know exactly where the bloop hit to win the World Series lands. We can read generated game summaries that leverage WPA to describe pivotal moments.

Our brains are narrative machines, and they love this sort of stuff! We love stories in real life, too. Take a few real-life examples:

News articles about the Dodgers' World Series win often discuss how they were perpetual post-season disappointments in the midst of a long championship drought
Trevor Bauer has a very public feud with Alex Bregman, so we pay close attention when they play one another
Scott and Tyler Heineman, two brothers, played against each other in MLB for the first time this year
Fernando Tatis Jr. is the son of long-time player Fernando Tatis, so we're often treated to articles about how his career relates to his fathers'

We do this on our own in OOTP, imagining rivalries, feuds, and relationships. But what if that was codified in OOTP itself?

I'm suggesting the addition of two data fields for players and teams that will allow for OOTP - and its players - to build more convincing narratives. Those fields are Relationships and Traits.

Relationships
---
These can apply to players or teams and signify a relationship between two entities. They would be displayed on the player and team profiles.

Player examples:

Joe is brothers with Jim
Donovan is the son of Rolando
Jason is rivals with Will
Adrian is close friends with Masahiro
Hunter loves San Francisco
Marcus dislikes Manager Tony

Team examples:

The Giants are bitter rivals with the Dodgers
The Athletics are geographic rivals with the Giants

These relationships are hooks that can be used for storylines, game summaries, and tendencies. For example, game summaries would be very different if you knew two teams were bitter rivals. Storylines could be written about a player signing with the team his father spent most of his career with. We get joy in real-life seeing Mike Yazstremski homer at Fenway because we know the significance; If OOTP knows who his grandfather is, it too can generate content about these kinds of events. It can also influence actions; perhaps a player is more likely to sign with a team if it's run by his former manager or he can be teammates with a good friend.

Traits
---
These are similar to relationships, but are unary and change depending on performance and other actions. They're sort of like "tags" that are programatically applied to players and teams over time.

Player examples:

Post-Season Disaster (ex., Clayton Kershaw): acquired by putting up negative WAR over 10 post-season starts
Hometown Hero (ex., Brett Phillips): walk-off win in the playoffs for hometown team
Rising Star (ex., Randy Arozarena): top 50 prospect with positive WAR in the manors
Flamethrower (ex., Aroldis Chapman): fastball over 100
Contract Disapointment (ex., Chone Figgins): negative WAR in year 1 of expensive multi-year deal
Comeback Kid (ex., Daniel Bard): 30+ years old and returns to majors after 3+ years away

Team examples:

Underdogs (ex., Tampa Bay Rays): in the playoffs with bottom 5-payroll
Never the Bride (ex., Oakland A's): early exits in consecutive post-seasons
Evil Empire (ex.,New York Yankees): top-5 payroll for five consecutive years
Old School (ex., Kansas City Royals?): managerial and GM styles opposes sabermetrics, weights statistics over ratings

Similar to relationships, these are hooks for storylines, news articles, and play-by-play text. Further more, it enables us to look at a player's history and learn even more about them. After Brett Phillips post-season walk-off, one of the broadcasters said something to the effect of, "This will be in the first paragraph of his front-page obituary". Morbid? Sure! But the point there is that it was a really big, historic moment. While we can imagine those events or edit our own news articles, building a framework to capture them in the game allows stories to grow organically.

I think both of these fields could add immeasurable intricacy to the game and the stories it tells.

Anyway, thanks for coming to my TED talk.

10-29-2020, 07:56 PM	#1
MidKnight Major Leagues Join Date: Nov 2003 Location: Milwaukee, WI Posts: 396	Relationships & Traits At its heart, OOTP is a narrative machine. It allows us to simulate baseball games in increasingly complex ways. We can revisit the past in historical leagues, exploring fantastic "what-if" scenarios. It allows us to imagine a world in which the injury-prone superstar never loses a step or one where Willie Mays plays alongside Mike Trout. We can even create our own worlds filled with imagined players, cities, rivalries, and more. Over time, OOTP has gotten better at helping our imaginations to craft stories. We can see the players dive for balls. We know exactly where the bloop hit to win the World Series lands. We can read generated game summaries that leverage WPA to describe pivotal moments. Our brains are narrative machines, and they love this sort of stuff! We love stories in real life, too. Take a few real-life examples: News articles about the Dodgers' World Series win often discuss how they were perpetual post-season disappointments in the midst of a long championship drought Trevor Bauer has a very public feud with Alex Bregman, so we pay close attention when they play one another Scott and Tyler Heineman, two brothers, played against each other in MLB for the first time this year Fernando Tatis Jr. is the son of long-time player Fernando Tatis, so we're often treated to articles about how his career relates to his fathers' We do this on our own in OOTP, imagining rivalries, feuds, and relationships. But what if that was codified in OOTP itself? I'm suggesting the addition of two data fields for players and teams that will allow for OOTP - and its players - to build more convincing narratives. Those fields are Relationships and Traits. Relationships --- These can apply to players or teams and signify a relationship between two entities. They would be displayed on the player and team profiles. Player examples: Joe is brothers with Jim Donovan is the son of Rolando Jason is rivals with Will Adrian is close friends with Masahiro Hunter loves San Francisco Marcus dislikes Manager Tony Team examples: The Giants are bitter rivals with the Dodgers The Athletics are geographic rivals with the Giants These relationships are hooks that can be used for storylines, game summaries, and tendencies. For example, game summaries would be very different if you knew two teams were bitter rivals. Storylines could be written about a player signing with the team his father spent most of his career with. We get joy in real-life seeing Mike Yazstremski homer at Fenway because we know the significance; If OOTP knows who his grandfather is, it too can generate content about these kinds of events. It can also influence actions; perhaps a player is more likely to sign with a team if it's run by his former manager or he can be teammates with a good friend. Traits --- These are similar to relationships, but are unary and change depending on performance and other actions. They're sort of like "tags" that are programatically applied to players and teams over time. Player examples: Post-Season Disaster (ex., Clayton Kershaw): acquired by putting up negative WAR over 10 post-season starts Hometown Hero (ex., Brett Phillips): walk-off win in the playoffs for hometown team Rising Star (ex., Randy Arozarena): top 50 prospect with positive WAR in the manors Flamethrower (ex., Aroldis Chapman): fastball over 100 Contract Disapointment (ex., Chone Figgins): negative WAR in year 1 of expensive multi-year deal Comeback Kid (ex., Daniel Bard): 30+ years old and returns to majors after 3+ years away Team examples: Underdogs (ex., Tampa Bay Rays): in the playoffs with bottom 5-payroll Never the Bride (ex., Oakland A's): early exits in consecutive post-seasons Evil Empire (ex.,New York Yankees): top-5 payroll for five consecutive years Old School (ex., Kansas City Royals?): managerial and GM styles opposes sabermetrics, weights statistics over ratings Similar to relationships, these are hooks for storylines, news articles, and play-by-play text. Further more, it enables us to look at a player's history and learn even more about them. After Brett Phillips post-season walk-off, one of the broadcasters said something to the effect of, "This will be in the first paragraph of his front-page obituary". Morbid? Sure! But the point there is that it was a really big, historic moment. While we can imagine those events or edit our own news articles, building a framework to capture them in the game allows stories to grow organically. I think both of these fields could add immeasurable intricacy to the game and the stories it tells. Anyway, thanks for coming to my TED talk.