MLB Deserve-To-Win-O-Meter ✓

@mlb_simulator · joined 01 Jun 2024

Modeling expected outcomes to simulate MLB games, inspired by @MoneyPuckdotcom. Code: https://t.co/w2C0gUFRSE Creator: @DerekGrifka

10 871Followers

5Following

8 852Posts total

28.9KViews on collected posts

Últimas publicaciones

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator14 Sep

⚾ Mariners @ Athletics 09/13/2026 Final: Mariners 7, Athletics 8 Deserve-to-Win: Mariners 13% / Athletics 79% (Tie 8%) #MLB #TridentsUp #Athletics https://t.co/MLoH6EhcDl

550 views · 1 likes · 0 reposts · 0 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator14 Sep

⚾ Royals @ Red Sox 09/13/2026 Final: Royals 1, Red Sox 4 Deserve-to-Win: Royals 14% / Red Sox 75% (Tie 12%) #MLB #FountainsUp #DirtyWater https://t.co/lVtuI1KOmb

545 views · 1 likes · 0 reposts · 0 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator13 Sep

@mlb_simulator Wind https://t.co/MyVN7rhTKe

GIF

23 views · 0 likes · 0 reposts · 0 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator13 Sep

@mlb_simulator Always 25 views · 0 likes · 0 reposts · 0 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator13 Sep

🚨 Rangers are luck merchants! 🚨 ⚾ Rangers @ D-backs 09/13/2026 Final: Rangers 7, D-backs 6 Deserve-to-Win: Rangers 4% / D-backs 91% (Tie 5%) #MLB #AllForTX #Dbacks https://t.co/yoQZrNTkkT

840 views · 2 likes · 0 reposts · 0 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator13 Sep

@mlb_simulator Wrigley winds got the cubs. Very unfortunate 129 views · 3 likes · 0 reposts · 1 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator13 Sep

🚨 Pirates are luck merchants! 🚨 ⚾ Pirates @ Cubs 09/13/2026 Final: Pirates 4, Cubs 3 Deserve-to-Win: Pirates 18% / Cubs 71% (Tie 11%) #MLB #LetsGoBucs #Cubs https://t.co/ZgzCnS1ZCS

2.2K views · 29 likes · 0 reposts · 3 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

There's still lots more to come, but let me know what you think so far. It's mentioned in every page on the site, but I wanted to mention that the data is from MLB, while the models are created by me. Thanks. 404 views · 0 likes · 0 reposts · 0 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

The final page includes in depth explanations, but also a feedback section at the bottom for you to submit ideas https://t.co/hOZNUDjIsB

477 views · 0 likes · 0 reposts · 1 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

I field many questions about why a batted ball is scored X% home run in the simulations, so I created an interactive tool where you can edit the exit velocity and launch angle to see where a ball is likely end end up, but you can also filter to a specific field and see the actual

207 views · 1 likes · 0 reposts · 1 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

The Hitters/Pitchers page gives you information with league-average context attached https://t.co/fTMMyS4Y4c

217 views · 0 likes · 0 reposts · 1 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

In the Teams page, you can visualize features that are functions of the "deserve-to-win o'meter", but clicking in to an individual team gives you a clean deep dive with high-level / archetype information https://t.co/gXs7WA5sxS

295 views · 1 likes · 0 reposts · 1 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

The Home page provides high-level overviews of what happened in yesterday's games. You can also search for previous games from this season https://t.co/beGiZrdw9o

761 views · 2 likes · 0 reposts · 3 replies Open on X →

MLB Deserve-To-Win-O-Meter ✓@mlb_simulator9 Jul

I've working on a website that can help you seamlessly dig beyond the box score, more quickly understand what type of player someone is, and even learn how a team is structured. I'll try my best to explain below, but I encourage you to take a peak here: https://t.co/Xj9W7W334N 22.2K views · 13 likes · 3 reposts · 1 replies Open on X →

Frente a cuentas del mismo tamaño

14 publicaciones de los últimos 90 días, junto al rango de 10K–100K seguidores. alcance normal para su tamaño, reacción más débil que la mayoría.

Visualizaciones medianas440esta cuenta924mediana de 10K–100K

Alcance, %4.05%esta cuenta3.62%mediana de 10K–100K

Interacción, %0.22%esta cuenta1.52%mediana de 10K–100K

Métrica	Esta cuenta	Mediana de 10K–100K	Proporción
Visualizaciones medianas por publicación	440	924	0.48×
Alcance (visualizaciones ÷ seguidores)	4.05%	3.62%	1.12×
Tasa de interacción	0.22%	1.52%	0.15×

Otras cuentas de este rango → Comparar con otra cuenta → Cómo se construyen estas referencias →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

22.2K9 Jul

761

295

217

207

477

404

2.2K13 Sep

129

840

54514 Sep

550

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.08%9 Jul

0.66%

0.68%

0.46%

0.97%

0.21%

0.00%

1.44%13 Sep

3.10%

0.24%

0.00%

0.18%14 Sep

0.18%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes68.8%53 in total

Reposts3.9%3 in total

Replies15.6%12 in total

Bookmarks11.7%9 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

Últimas publicaciones

Frente a cuentas del mismo tamaño

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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