MLB The Show 23 – Franchise Fidelity to Reality Roster Out Now!

PSN ID: ViatorLion10
File Name: Franchise Fidelity to Reality

Description from ViatorLion10

Welcome to the second ever release of my “Franchise Fidelity to Reality” roster set! Last year was a HUGE success w/ over 5K downloads and tons of positive feedback. I am excited to bring the project back once again this year with some new wrinkles to help take it to the next level.

Meet the Team

ViatorLion10: Project creator, chief auditor, in-game editor

Sports Gaming Rosters (aka Big_Gargamel): Base roster creator, player likeness and equipment coordinator

JWDixon: MLB/MiLB data gathering, system development, in-game editor

Tiboss300: Prospect data gathering, in-game editor

GabeTODT: In-game editor

Matt Thompson: ProspectsLive collaborator

What’s New This Year

WAR integration into overall calculations

WAR and age-related positive regression-based potential system

Integration of projections into current ratings

Revamp of prospect potential system based on overall grade and age (more balance and consistency)

Behind the scenes QoL changes (should decrease human errors and allow for better fine tuning and auditing)

More details available here:

My Vision

For years, I have been trying to achieve the best possible franchise experience. Full minors rosters added enjoyment to my experience, however, they often created huge problems for franchise longevity due to unbalanced potentials amongst prospects and MLB players. I then tried out other creators who attempted re-rate both overalls and potentials for MLB and MiLB players. I give these creators a ton of credit because I now realize how much effort goes into this process. That being said, I saw a vast room for improvement in a multitude of areas, so therefore, I set out to put my own little spin on things and create the most balanced and realistic roster available.

What sets this roster apart from all the others?

One of the things I wanted to focus on the most was trying to best recreate in-game every player’s unique style and level of play. To achieve this, I needed to get testing in-game to see what attribute values could replicate what statistics.

So that’s exactly what I did. I spent hours testing how variable values of attributes would lead to different outputs for statistics. I was then able to create standard curves from this testing so I could extrapolate how a player’s real-life statistics could be quantified into an in-game rating. From what I can tell, this is a feature unique to only my roster set. Others certainly use real life statistics to generate ratings, but none that I have found try to replicate those real-life numbers in-game.

After these ratings have been generated, I also go through an auditing process. No system is perfect, and I know that. Sometimes players can fall through the cracks and be heavily over/underrated. This auditing process allows me to catch these players and to adjust them accordingly. These changes are only made to truly replicate a player’s actual value in real-life and I try to keep them at a minimum when possible.

The second aspect that I wanted to heavily focus on in the depth of prospects. I was never a fan of rosters that prioritized AAA/AA filler players over top prospects who are in the low minors. Not to mention, sometimes lesser-known prospects can often be the most intriguing, and therefore, the most fun to play with in-game. That is why I decided to include every team’s top 30 prospects. This allows for significant depth in terms of franchise management, as well as it helps to really set apart strong farm systems from weak farm systems. Again, this is the only roster to my knowledge that goes in-depth from #1 all the way to #30.

The last thing that is unique to this roster set is a tiered potential system. This is by no means something that only I do, however, my tiered system is broken up into various roles that players can fill. Players are assigned certain roles based on their level of play and projected future level of play, and thus are assigned a pertinent value.

The end result should be a roster that has a high number of “average” players in the mid-70s with decreasing numbers of guys in the 80s and 90s along w/ guys in the low-70s and even upper-60s that will be on MLB rosters at times. This should lead to long-term stability of franchises and a strong bit of realism for hardcore sim players.

Full list of features

Spoiler ·

Re-rates of all attributes, overalls, and potentials for every player on 40-man rosters and former MLB players on MiLB contracts (~1400 players)

oPowered by real-life statistics and advanced metrics (Statcast and Fielding bible)


Inclusion of every team’s top 30 prospects with the most accurate archetypes, current overalls, and potentials (900 players)

oPowered by MLB Pipeline and


Simple re-rates and potential re-works of roster filler players (~500 players)

In-depth pitch reworks for MLB players to best replicate repertoires and pitch effectiveness

oPowered by Statcast and Fangraphs


Tiered potential system to balance potentials across the league and allow for franchise longevity

Statistics from the past three seasons are gathered for every single player to be edited. I believe baseball to be a long game, and that the longer you play, the more your true ability starts to show. Therefore, I do not weight the performance of any one season over the other. A player’s average performance over a three-year period as well as projections for the upcoming season will be used to generate his attributes.

As far as potentials go, I don’t aim to have a certain percentage of players fall in certain categories. I let a player’s performance and projections determine their value alone. To determine potentials, I build off of the value a player has already demonstrated on the field and then using a standard regression curve to determine how much more they can develop based on their current age. A breakdown of roles and expected overalls can be found below:

Pos PlayersSPRPPotential
SuperstarAceElite Closer90-95
All-StarTop RotationTop Closer86-90
GreatSP 2/3High Leverage82-85
Above Avg.Mid RotationMid-Late RP78-81
Avg.SP 4/5Regular RP75-77
Role5th SPLow Leverage72-74



Position player attribute values

Contact: Batting average

oLeague average: 60


Power: ISO

oLeague average: 65


Vision: K%

oLeague average: 42


Discipline: BB%

oLeague average: 60


Clutch: BA w/ RISP

oLeague average: 60


Durability: Combination of GP and IL time

oLeague average: 67


Speed: Sprint speed

oLeague average: 50


Arm strength:

oCatchers: Pop time

oIF/OF: Arm Strength via Statcast


Arm accuracy:

oCatchers: Based on a combination of runners CS% and throwing errors

oInfielders: Based on number of throwing errors and total throwing chances

oOutfielders: Based on a combination of OF assists, throwing errors, and ARM value

oLeague average: 70



oCatchers: Runs extra strikes/Pitches

oInfielders/Outfielders: Outs above average/Opportunities (remove throwing errors from outs above average calculation)



oCatchers: Same as fielding

oInfielders: Outs above average/Opportunities (remove both throwing and fielding errors from outs above average calculation)

oOutfielders: OF jump


Blocking: Blocks/(Blocks + PB + WP)

oLeague average: 65


Stealing/BR aggressiveness: SBA/H

oLeague average: 40

Pitching attribute values

Stamina: IP/App

oLeague average for SP: 73

oLeague average for RP: ~20


Per 9 attribute: Corresponding per 9 values

oLeague average H/9: 60

oHR/9: 55

oK/9: 65

oBB/9: 65


Clutch: H/9 w/ RISP

oLeague average: 60


Pitch control: Location+ from Fangraphs

oLeague average: 60


Pitch movement: Stuff+ from Fangraphs

oLeague average: 60


Pitch considerations:

o“Sinkers” have more vertical break and “two-seam fastballs” have more horizontal break

o“Change-ups” have more vertical break and “circle change-ups” have more horizontal break

o“Splitters” are “change-ups” that have exceeded velocity maximums

o“Two-seamers” or “sinkers” are “circle change-ups” that have exceeded velocity maximums

o“12-6 curveballs” have more vertical break, “sweeping curveballs” have more horizontal break, “curveballs” have very similar vertical and horizontal break

o“Knuckle curveballs” are “curveballs” or “12-6 curveballs” that have exceeded velocity maximums

o“Slurves” are “sweeping curveballs” that have exceeded velocity maximums

Prospect editing

Attributes are determined based on scouting grades for different skills

oFor hitters: This will include a specific grade for every skill

oFor pitchers: This will only include pitch and control/command grades, which are then combined to generate per 9 grades

oFor pitchers: Pitch control is determined by control/command grades, while movement is determined by the overall pitch grade

oFinal attributes are not meant to perfectly replicate grades. Instead, each player has a specific archetype that is created. Therefore, development in franchise will be critical. Players w/ 60 hit tools are not guaranteed to be 60-grade hitters in the MLB. You actually have to develop that tool still (which is a nice little unique feature)


Current overalls are determined via a combination of MLB ETA, scouting overall (based on attribute grades and current minor league level), and performance (based on wRC+ or xFIP at certain minor league levels)

Potentials are determined based on a combination “overall” grade and current age to generate a value used for a standard curve
· Below is a rough chart of what overall grades correspond to what overalls, however, this is free-flowing and players can move up or down based on different factors

Final Comments
I want to thank each and every last one of you who download these rosters and give them a try. This project is a lot of work, but the end result makes it worth it. I am so glad to have a full team working together this year as it only helps make the final product that much better.

Come chat with us on discord:


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