MLB Prompts

Utilize these prompts by copying and pasting them into the Sports Stats Gather GPT.

Sports Stats Gather GPT Prompts

Please use these prompts in order. Ensure you read the prompt to find where to copy and paste the game in question, specifically looking for *Paste Home vs. Away Team* within the prompt.

Ensure you gather the starting line up for the game in question from the MLB Lineups and Pitchers section.

The Sports Stats Gather GPT can make mistakes. Be sure to use the thumbs down button if the prompt is incorrect to provide feedback. Ensure to complete the form to help it learn efficiently.

Prompt 1 - Persona and Game in Question:

You are a professional sports bettor specializing in making the best bet predictions and a statistical genius. I would like your advice.

I am specifically looking to the following bet types for this game in question:

Bet types:

• Moneyline  
• Spread  
• First Five Innings Winner  
• First Five Innings Spread  
• Over and Under Totals  
• Team Totals Over and Under 

Game in question:
*Paste Game in Question*

Please wait until I specifically request these predictions, as I have relevant information about the files in your knowledge and capable actions that I would like to review with you and how to use them effectively. I do not want you identifying any predictions without all the facts and potentially hallucinating. Just acknowledge my ask with a simple yes or no confirmation. Make sure to thoroughly think through and carefully consider each prompt I give you.

It is crucial to provide a comprehensive comparative analysis of both teams' statistics for the game in question, focusing strictly on the metrics I request.

Prompt 2 - Park Factors and Scenario Stats:

# Park Factors and Scenario Stats Analysis

Use the Sports Stats Gather MLB API to analyze BOTH park factors AND scenario stats for the upcoming game. It is crucial to provide information on BOTH aspects for EACH team.

## 1. Park Factors Analysis
Endpoint: https://sportsstatsgather.com/api/mlb/data/parkfactors/stadium?stadium=[Stadium Name]

Retrieve for the game's stadium:
Game,Away Team,Home Team,HR,2B/3B,1B,Runs

### Key Analysis Points:
1. Home Run Factor
   - Analyze the impact on home runs
   - Consider how this affects power hitters in both lineups

2. Extra-Base Hit Factor
   - Evaluate the impact on doubles and triples
   - Assess how this might influence gap hitters and team strategies

3. Singles Factor
   - Analyze the effect on single production
   - Consider implications for contact hitters and overall offensive approach

4. Run Scoring Environment
   - Evaluate the overall impact on run scoring
   - Assess how this might affect pitching strategies and bullpen usage

### Comparative Analysis:
1. Compare how each team's offensive strengths align with the park factors
2. Assess which team might benefit more from the ballpark's characteristics
3. Consider how park factors might influence lineup decisions and in-game strategy

## 2. Scenario Stats Analysis
Endpoint: https://sportsstatsgather.com/api/mlb/data/otherstats/team?team=[Team Name]

Retrieve for both teams:
Rank,Team,Scenario,2024,Last 3,Last 1,Home,Away,2023

Analyze all available scenarios, with a focus on:
- Stolen Bases Per Game
- Double Plays Per Game
- Errors Per Game
- Opponent Stolen Bases Per Game
- Opponent Double Plays Per Game
- Opponent Errors Per Game
- Any other relevant scenarios provided in the data

### Key Analysis Points:
1. Current Season Performance (2024)
   - Analyze each team's performance in various scenarios for the current season

2. Recent Trends
   - Compare season stats (2024) with recent performance (Last 3, Last 1)
   - Identify any significant improvements or declines

3. Home/Away Splits
   - Assess how each team's performance in these scenarios varies between home and away games
   - Consider the impact on the upcoming game based on its location

4. Year-over-Year Comparison
   - Compare 2024 performance to 2023 to identify long-term trends or improvements

5. Ranking Analysis
   - Consider each team's rank in various scenarios to gauge their strengths relative to the league

### Comparative Analysis:
1. Compare the strengths and weaknesses of each team across these scenarios
2. Identify which team has the overall advantage in these situational stats
3. Assess how these scenario stats might influence game strategy and outcome

## 3. Predictive Insights
Based on BOTH the park factors AND scenario stats analysis:
1. Predict how the ballpark characteristics might affect the game's outcome
2. Identify which team has the advantage in key situational scenarios
3. Suggest how these factors might influence game strategy, lineup decisions, and in-game management

## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Key park factors for the game's stadium and their potential impact
2. Top 3 scenario stat advantages for each team
3. Notable recent trends in scenario stats for both teams
4. Overall assessment of which team benefits more from the combination of park factors and scenario stats

Ensure this information is clearly labeled and easily retrievable for the final analysis.

## Final Thoughts
Synthesize how park factors and scenario stats might interact with other factors (e.g., team strengths, pitching matchups) to influence the game outcome. Consider how these elements might create specific opportunities or challenges for each team. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.

## Important Note
Ensure that you have provided a comprehensive analysis of BOTH the Park Factors AND Scenario Stats for EACH team. Do not skip or minimize either aspect, as both are crucial for an accurate assessment of the teams' potential performance in the upcoming game.

Before concluding your analysis, double-check that you have included:
1. A detailed park factors analysis for the game's stadium
2. A thorough scenario stats analysis for both teams, covering all provided scenarios
3. Comparative analyses that consider both park factors and scenario stats for each team

If either the Park Factors or Scenario Stats analysis is missing or incomplete, go back and add the missing information before proceeding.

Prompt 3 - Injury Report and Game Log:

# Injury Report and Game Log Analysis

Use the Sports Stats Gather MLB API to analyze BOTH the injury reports AND recent game logs for both teams in the upcoming game. It is crucial to provide information on BOTH aspects for EACH team.

## 1. Injury Report Analysis
Endpoint: https://sportsstatsgather.com/api/mlb/data/injuryreports/team?team=[Team Name]

Note: Analyze the injury report data as provided by the API. If specific fields are not available, focus on the overall injury situation for each team based on the information given.

### Key Analysis Points:
1. Current Injuries
   - Identify key players currently injured or on the IL (Injured List)
   - Assess the impact of these injuries on the team's performance

2. Injury Impact
   - Evaluate how injuries affect specific positions (e.g., starting rotation, bullpen, key batting positions)
   - Consider the quality of available replacements

### Comparative Analysis:
1. Compare the overall injury situation between the two teams
2. Assess which team is more significantly impacted by current injuries
3. Consider how injuries might influence lineup construction and in-game strategy

## 2. Game Log Performance Analysis
Endpoint: https://sportsstatsgather.com/api/mlb/data/gamelogs/team?team=[Team Name]

Retrieve for both teams:
Date,Team,Opponent,Opp Rank,H/A/N,Score

### Key Analysis Points:
1. Recent Performance
   - Analyze the team's performance in the last 5 games
   - Identify any winning or losing streaks

2. Home/Away Performance
   - Assess recent performance in home/away games (depending on the upcoming game's location)
   - Identify any significant home/away performance disparities

3. Quality of Opposition
   - Evaluate performance against opponents of different ranks
   - Consider the rank of the upcoming opponent in this context

4. Scoring Trends
   - Analyze recent scoring patterns (high-scoring games, low-scoring games, shutouts)
   - Identify any trends in run production and run prevention

5. Team Ranking Impact
   - Assess how each team performs relative to their own ranking and their opponents' rankings

### Comparative Analysis:
1. Compare the recent form of both teams over the last 5 games
2. Assess which team has performed better against similar quality opponents
3. Evaluate how each team's recent performance trends match up against the other's strengths and weaknesses

## 3. Predictive Insights
Based on BOTH the injury report AND game log analysis:
1. Predict how current injuries might affect each team's performance in the upcoming game
2. Identify which team has the momentum advantage based on recent game logs
3. Suggest how recent performance and injury situations might influence game strategy

## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. List of key players injured for each team (if available)
2. Each team's win-loss record in the last 5 games
3. Notable performance trends (e.g., strong home form, struggles against high-ranked opponents)
4. Overall assessment of which team is in better form considering injuries and recent performance

Ensure this information is clearly labeled and easily retrievable for the final analysis.

## Final Thoughts
Synthesize how the injury situations (if known) and recent performance trends might interact with other factors to influence the game outcome. Consider how the teams' and opponents' rankings have impacted recent results and how this might apply to the upcoming game. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.

## Important Note
Ensure that you have provided a comprehensive analysis of BOTH the Injury Report (to the extent information is available) AND Game Log for EACH team. Do not skip or minimize either aspect, as both are crucial for an accurate assessment of the teams' current states and potential performance in the upcoming game.

Before concluding your analysis, double-check that you have included:
1. An injury report analysis for both teams based on available information
2. A thorough game log analysis for both teams, focusing on the last 5 games
3. Comparative analyses that consider both injury situations (if known) and recent performance for each team

If either the Injury Report or Game Log analysis is missing or incomplete for either team, go back and add the missing information before proceeding.

Prompt 4 - Overall Batting Stats:

# Comprehensive Batting Analysis

Use the Sports Stats Gather MLB API to retrieve and analyze comprehensive batting statistics for the upcoming game. Focus on these key areas for the batting lineup of each team for the game in question:

## 1. Team Batting Stats
Endpoint: https://sportsstatsgather.com/api/mlb/data/advbatting?team=[Team Name]

Retrieve for both teams:
Rk,Team,Pos,Name,Age,G,PA,AB,R,H,2B,3B,HR,RBI,SB,CS,BB,SO,BA,OBP,SLG,OPS,OPS+,TB,GDP,HBP,SH,SF,IBB

### Key Insights:
- Team OPS and OPS+ as overall offensive productivity measures
- Home run and extra-base hit rates (2B, 3B, HR) for power assessment
- Walk-to-strikeout ratio (BB/SO) to gauge plate discipline
- Run production efficiency (R/PA, RBI/PA)
- Total Bases (TB) as a measure of overall hitting effectiveness
- Stolen Base success rate (SB/(SB+CS)) for baserunning impact
- Situational hitting indicators (GDP, SF, IBB) for clutch performance

## 2. Advanced Batting Metrics
Endpoint: https://sportsstatsgather.com/api/mlb/data/advbatting?team=[Team Name]

Gather for both teams:
Name,Team,Age,Batting_PA,Batting_rOBA,Batting_Rbat+,Batting_BAbip,Batting_ISO,Batting Ratios_HR%,Batting Ratios_SO%,Batting Ratios_BB%,Batted Ball_EV,Batted Ball_HardH%,Batted Ball_LD%,Batted Ball_GB%,Batted Ball_FB%,Batted Ball_GB/FB,Batted Ball_Pull%,Batted Ball_Cent%,Batted Ball_Oppo%,Win Probability_WPA,Win Probability_cWPA,Win Probability_RE24,Baserunning_RS%,Baserunning_SB%,Baserunning_XBT%

### Key Insights:
- Weighted On-Base Average (rOBA) for overall offensive value
- Batting Runs Above Average (Rbat+) to assess player value
- BABIP and its implications for sustainability of performance
- Isolated Power (ISO) to assess extra-base hit production
- Batted ball profile (LD%, GB%, FB%, Pull%, Cent%, Oppo%) and its match-up implications
- Win Probability Added (WPA) and context-neutral WPA (cWPA) for clutch performance evaluation
- Exit Velocity (EV) and Hard Hit % for quality of contact assessment
- Base Running metrics (RS%, SB%, XBT%) for overall offensive contribution

## 3. Sabermetric Batting Performance
Endpoint: https://sportsstatsgather.com/api/mlb/data/advbatting?team=[Team Name]

Collect for both teams:
Name,Team,Age,PA,Outs,RC,RC/G,AIR,BAbip,BA,lgBA,OBP,lgOBP,SLG,lgSLG,OPS,lgOPS,OPS+,OWn%,BtRuns,BtWins,TotA,SecA,ISO,PwrSpd,PosÂ Summary

### Key Insights:
- Runs Created per Game (RC/G) as a team offense predictor
- OPS+ and its reflection of performance relative to league average
- Total Average (TotA) for all-around offensive contribution
- Power-Speed Number (PwrSpd) to identify balanced offensive threats
- Batting Runs (BtRuns) and Batting Wins (BtWins) for value above average
- Secondary Average (SecA) to measure offensive contribution beyond batting average
- AIR (contextual run expectancy) to understand offensive environment
- Offensive Winning Percentage (OWn%) for individual player contribution

## Analysis Instructions:
1. Gather all data before beginning analysis.
2. Compare overall offensive capabilities of both teams using OPS+, RC/G, and rOBA.
3. Identify key players and their potential impact on the game, focusing on Rbat+, WPA, and BtWins.
4. Assess how batting matchups might influence game outcome, considering batted ball profiles and ISO.
5. Consider interaction between batting stats and opposing team's pitching strengths for the batting lineup for the game in question.
6. Evaluate recent trends and hot/cold streaks for key batters using BABIP and advanced metrics.
7. Analyze platoon splits if available in the data set.
8. Consider the impact of the ballpark on the offensive potential of each team using AIR metric.

## Final Analysis
Based on your comprehensive analysis of the stats:
1. Compare both teams and determine which one has the stronger offensive capabilities and why, using OPS+, RC/G, and rOBA as primary indicators.
2. Identify the top 3 batters to watch from each team and explain their potential impact on the game, referencing Rbat+, WPA, and key individual stats.
3. Predict which team is more likely to outperform their season averages in this specific matchup and why, considering recent BABIP trends and matchup-specific factors.
4. Highlight any key offensive mismatches that could significantly influence the game's outcome, using batted ball profiles and ISO comparisons.

Remember to use the most current data and explain any advanced metrics for accessibility to all users. Your analysis should provide clear, concise insights to support informed betting decisions.

## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Overall team offensive rankings (based on OPS+ and RC/G)
2. Top 3 batters from each team and their key stats (including Rbat+, WPA, and ISO)
3. Any significant matchup advantages based on batted ball profiles
4. Notable recent trends or hot streaks indicated by BABIP and advanced metrics
5. Key offensive mismatches identified

Ensure this information is clearly labeled and easily retrievable for the final analysis.

Prompt 5 - Home/Away Batting Splits:

# Home and Away Batting Split Analysis

Use the Sports Stats Gather MLB API to retrieve and analyze detailed home and away batting splits for the upcoming game. Focus on the batting lineup for the home team's performance at home and the away team's performance in away games.

## 1. Data Retrieval
### For Home Team:
Endpoint: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=batting&category=home&team=[Home Team Name]

### For Away Team:
Endpoint: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=batting&category=away&team=[Away Team Name]

Retrieve the following stats for both teams:
Name,Position,Team,batting_[home/away]_ab,batting_[home/away]_r,batting_[home/away]_h,batting_[home/away]_2b,batting_[home/away]_3b,batting_[home/away]_hr,batting_[home/away]_rbi,batting_[home/away]_bb,batting_[home/away]_so,batting_[home/away]_ba,batting_[home/away]_obp,batting_[home/away]_slg

## 2. Key Metrics Analysis
For each team and relevant players, analyze:

1. Slash Line (BA/OBP/SLG)
   - Compare to overall season stats to identify home/away advantages
   - Highlight significant deviations from career norms

2. Power Metrics
   - ISO (Isolated Power) = SLG - BA
   - HR Rate = HR / AB
   - XBH% (Extra Base Hit %) = (2B + 3B + HR) / H

3. Plate Discipline
   - BB% = BB / AB
   - K% = SO / AB
   - BB/K Ratio

4. Run Production
   - R/AB (Runs per At Bat)
   - RBI/AB (RBI per At Bat)

## 3. Comparative Analysis
1. Team Comparison
   - Compare home team's home performance vs. away team's road performance
   - Identify which team has a stronger statistical advantage in this matchup

2. Individual Matchups
   - Highlight players with significant home/away splits
   - Identify potential mismatches against the opposing pitcher

3. Lineup Analysis
   - Assess the strength of each lineup based on home/away performance
   - Identify any notable trends in lineup construction for home/away games

## 4. Context Considerations
1. Ballpark Factors
   - Consider how the home ballpark might influence offensive output
   - Compare team and individual stats to league averages in this ballpark

2. Recent Trends
   - If possible, analyze performance in recent home/away games for each team
   - Identify any players on hot or cold streaks in relevant contexts

## 5. Predictive Insights
Based on the home/away split analysis:
1. Predict which team has the offensive advantage in this matchup
2. Identify key players likely to over/underperform based on the game location
3. Suggest how these splits might influence overall game strategy (e.g., lineup adjustments, pinch-hitting decisions)

## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Team batting average, OBP, and SLG differentials (home vs. away) compared to league average
2. Top 3 players from each team with the most significant home/away split advantages
3. Any notable power or plate discipline discrepancies in home/away performance
4. Predicted offensive advantage based on split analysis
5. Key individual matchups that could significantly impact the game

Ensure this information is clearly labeled and easily retrievable for the final analysis.

## Final Thoughts
Synthesize how these home/away splits might interact with other factors (e.g., pitching matchups, bullpen strength) to influence the game outcome. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.

Prompt 6 - Recent Batting Performance:

# Recent Performance Batting Analysis (Last 2 and 4 Weeks)

Use the Sports Stats Gather MLB API to retrieve and analyze recent batting performance for both teams in the upcoming game. Focus on the last 2 weeks and last 4 weeks of data to identify current trends and hot/cold streaks.

## 1. Data Retrieval
### For Last 2 Weeks:
Endpoint: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=batting&category=last_2_weeks&team=[Team Name]

### For Last 4 Weeks:
Endpoint: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=batting&category=last_4_weeks&team=[Team Name]

Retrieve the following stats for both teams for both time periods:
Name,Position,Team,batting_last_[2/4]_weeks_ab,batting_last_[2/4]_weeks_r,batting_last_[2/4]_weeks_h,batting_last_[2/4]_weeks_2b,batting_last_[2/4]_weeks_3b,batting_last_[2/4]_weeks_hr,batting_last_[2/4]_weeks_rbi,batting_last_[2/4]_weeks_bb,batting_last_[2/4]_weeks_so,batting_last_[2/4]_weeks_ba,batting_last_[2/4]_weeks_obp,batting_last_[2/4]_weeks_slg

## 2. Key Metrics Analysis
For each team and relevant players, analyze:

1. Recent Performance Trends
   - Compare 2-week and 4-week stats
   - Identify players on hot or cold streaks

2. Slash Line Progression (BA/OBP/SLG)
   - Analyze changes in slash line from 4 weeks to 2 weeks
   - Highlight significant improvements or declines

3. Power Metrics
   - ISO (Isolated Power) = SLG - BA
   - HR Rate = HR / AB
   - XBH% (Extra Base Hit %) = (2B + 3B + HR) / H
   - Compare recent power numbers between 2-week and 4-week periods

4. Plate Discipline
   - BB% = BB / AB
   - K% = SO / AB
   - BB/K Ratio
   - Identify changes in approach or pitch recognition

5. Run Production
   - R/AB (Runs per At Bat)
   - RBI/AB (RBI per At Bat)
   - Assess recent run production efficiency

## 3. Comparative Team Analysis
1. Team Offensive Trends
   - Compare overall team performance in last 2 weeks vs. last 4 weeks
   - Identify which team has shown more recent improvement

2. Lineup Analysis
   - Assess how recent performance might impact lineup construction
   - Identify any players who have earned more playing time based on recent performance

3. Matchup Implications
   - Consider how recent performance trends might interact with the opposing team's pitching

## 4. Context Considerations
1. Sample Size
   - Consider the number of at-bats when evaluating performance changes
   - Give more weight to larger sample sizes when possible

2. Position-Specific Performance
   - Analyze performance trends by position
   - Identify any positional strengths or weaknesses emerging in recent weeks

3. Situational Hitting
   - If possible, infer situational hitting improvements from available stats (e.g., RBI efficiency)

## 5. Predictive Insights
Based on the recent performance analysis:
1. Predict which team has the current offensive momentum
2. Identify key players likely to continue their recent trends (hot streaks/slumps)
3. Suggest how recent performance might influence game strategy (e.g., lineup changes, pitching approach)

## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Team batting average, OBP, and SLG for last 2 weeks and last 4 weeks, highlighting significant changes
2. Top 3 "hot" hitters from each team based on recent performance
3. Any notable slumps or improvements in key players
4. Overall team offensive trajectory (improving, declining, or stable)
5. Key matchups based on recent performance trends

Ensure this information is clearly labeled and easily retrievable for the final analysis.

## Final Thoughts
Synthesize how these recent performance trends might interact with other factors (e.g., pitching matchups, home/away splits) to influence the game outcome. Consider how much weight to give recent performance vs. season-long stats in the final prediction for Prompt 12. Be cautious about overemphasizing small sample sizes, but don't ignore clear trends in player performance.

Prompt 7 - RHP/LHP Performance:

# RHP/LHP Performance Analysis

Use the Sports Stats Gather MLB API to analyze how each team performs against right-handed pitchers (RHP) and left-handed pitchers (LHP). It is crucial to provide this analysis for BOTH teams in the upcoming game.

## Data Retrieval
Endpoint: https://sportsstatsgather.com/api/mlb/data/fangraphsarms/team?team=[Team Name]

Retrieve for both teams:
Season,HandednessStat,Tm,G,PA,AB,H,1B,2B,3B,HR,R,RBI,BB,IBB,SO,HBP,SF,SH,GDP,SB,CS,AVG

Focus on these two specific contexts for each team:
1. Stats vs LHP
2. Stats vs RHP

## Key Metrics Analysis
For each team against both LHP and RHP, analyze:

1. Batting Average (AVG)
   - Compare AVG against LHP and RHP
   - Identify any significant splits that could impact the upcoming game

2. On-Base Percentage (OBP)
   - Calculate OBP: (H + BB + HBP) / (PA - SF)
   - Assess how OBP varies against LHP and RHP

3. Slugging Percentage (SLG)
   - Calculate SLG: (1B + 2B*2 + 3B*3 + HR*4) / AB
   - Evaluate power production against different pitcher types

4. OPS (On-base Plus Slugging)
   - Calculate OPS: OBP + SLG
   - Use as an overall measure of offensive production in each context

5. Isolated Power (ISO)
   - Calculate ISO: SLG - AVG
   - Assess raw power output against LHP and RHP

6. Walk Rate (BB%)
   - Calculate BB%: (BB + IBB) / PA
   - Analyze plate discipline against different pitcher types
   
7. Strikeout Rate (K%)
   - Calculate K%: SO / PA
   - Evaluate contact skills against LHP and RHP
   
8. Home Run Rate (HR%)
   - Calculate HR%: HR / PA
   - Assess power outcomes in different pitching matchups
   
9. Base Stealing Efficiency
   - Calculate SB success rate: SB / (SB + CS)
   - Analyze if base stealing strategy changes based on pitcher handedness
   
10. Run Production
    - Calculate Runs per PA: R / PA
    - Analyze overall offensive efficiency against LHP and RHP
   
## Comparative Analysis
1. LHP vs RHP Performance
   - Compare each team's performance against LHP and RHP
   - Identify which team has a stronger platoon advantage
   
2. Specific Matchup Analysis
   - Based on the handedness of the starting pitchers for the upcoming game, evaluate how each team's offense matches up
   - Consider how these splits might influence lineup decisions and in-game strategy
   
## Predictive Insights
Based on the RHP/LHP performance analysis:
1. Predict which team has the overall advantage based on the starting pitcher matchups
2. Identify key statistical areas (e.g., power, contact, plate discipline) where one team might have a significant edge
3. Suggest how these splits might influence game strategy, including potential platoon substitutions or pinch-hitting decisions
   
## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Each team's OPS against LHP and RHP
2. Notable splits in key metrics (AVG, OBP, SLG, K%, BB%) that could significantly impact the game
3. Overall assessment of which team has the advantage based on pitcher handedness matchups
4. Key strategic implications based on these splits
   
Ensure this information is clearly labeled and easily retrievable for the final analysis.
   
## Final Thoughts
Synthesize how the RHP/LHP performance splits might interact with other factors (e.g., specific pitcher strengths, ballpark factors) to influence the game outcome. Consider how these splits might affect both starting lineup construction and late-game management decisions. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.

## Important Note
Ensure that you have provided a comprehensive analysis of performance against BOTH RHP AND LHP for EACH team. Do not skip or minimize any aspect, as all are crucial for an accurate assessment of the teams' potential performance in the upcoming game.
   
Before concluding your analysis, double-check that you have included:
1. A detailed analysis of performance against LHP and RHP for both teams
2. Calculated metrics beyond what's directly provided in the data (e.g., OBP, SLG, OPS, ISO)
3. Comparative analyses that consider how these splits might influence the specific matchup in the upcoming game
   
If any part of this analysis is missing or incomplete, go back and add the missing information before proceeding.

Prompt 8 - Overall Pitching Stats:

# Comprehensive Pitching Analysis
   
Use the Sports Stats Gather MLB API to retrieve and analyze comprehensive pitching statistics for the upcoming game. Focus on the starting pitchers for the game in question only. Analyze these key areas:
   
## 1. Data Retrieval
Endpoint: https://sportsstatsgather.com/api/mlb/data/advpitching?team=[Team Name]
   
Retrieve the following stats for both teams' starting pitchers for the game in question:
Name,Team,W,L,ERA,G,GS,IP,H,R,ER,HR,BB,SO,WHIP,H9,HR9,BB9,SO9,SO/W
  
## 2. Key Metrics Analysis
For each starting pitcher, analyze:
   
1. Overall Performance
   - ERA (Earned Run Average)
   - WHIP (Walks and Hits per Inning Pitched)
   - Win-Loss Record and Win Percentage
   
2. Control and Dominance
   - SO9 (Strikeouts per 9 innings)
   - BB9 (Walks per 9 innings)
   - SO/W (Strikeout to Walk ratio)
   
3. Batted Ball Profile
   - HR9 (Home Runs per 9 innings)
   - H9 (Hits per 9 innings)
   
4. Workload
   - IP (Innings Pitched)
   - G (Games)
   - GS (Games Started)
   
## 3. Comparative Analysis
1. Pitcher vs. Pitcher Comparison
   - Compare the starting pitchers head-to-head across all available metrics
   - Identify areas where each pitcher has a significant advantage
   
2. Pitcher vs. Opposing Lineup
   - Analyze how each pitcher's strengths/weaknesses match up against the opposing team's batting tendencies
   - Consider handedness matchups if relevant
   
3. Historical Performance
   - If possible, review each pitcher's performance against the opposing team in past matchups
   - Identify any notable trends or consistently strong/weak performances
   
## 4. Context Considerations
1. Recent Form
   - Analyze each pitcher's performance in their recent starts
   - Identify any improving or declining trends
   
2. Ballpark Factors
   - Consider how the game's venue might affect each pitcher's performance
   - Adjust expectations based on known park factors
   
## 5. Predictive Insights
Based on the comprehensive pitching analysis:
1. Predict which starting pitcher has the overall advantage in this matchup
2. Identify key areas where each pitcher might struggle or excel
3. Suggest how the pitching matchup might influence overall game strategy
   
## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Each starting pitcher's ERA, WHIP, SO9, and BB9
2. Notable strengths and weaknesses of each pitcher
3. How each pitcher matches up against the opposing lineup
4. Any significant recent trends in performance
5. Predicted pitching advantage based on the analysis
   
Ensure this information is clearly labeled and easily retrievable for the final analysis.
   
## Final Thoughts
Synthesize how the pitching matchup might interact with other factors (e.g., team offensive capabilities, ballpark factors) to influence the game outcome. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.
   
## Important Note
Ensure that you have provided a comprehensive analysis of ALL listed statistics for BOTH starting pitchers. Do not skip or minimize any metric, as each provides valuable insight into pitcher performance and potential game outcomes.
   
Before concluding your analysis, double-check that you have included:
1. A detailed analysis of each listed metric for both starting pitchers
2. Comparative analyses between the two pitchers across all metrics
3. Considerations of how these pitching stats might specifically impact the upcoming game
   
If any part of this analysis is missing or incomplete, go back and add the missing information before proceeding.

Prompt 9 - Detailed Pitching Analysis:

# Detailed Pitching Analysis: Home/Away Splits and Recent Performance

Use the Sports Stats Gather MLB API to retrieve and analyze detailed pitching statistics for the starting pitchers in the upcoming game. Focus on home/away splits and recent performance (last 2 and 4 weeks).
   
## 1. Data Retrieval
### Home/Away Splits:
For Home Team: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=pitching&category=home&team=[Home Team Name]
For Away Team: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=pitching&category=away&team=[Away Team Name]
   
### Recent Performance:
Last 2 Weeks: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=pitching&category=last_2_weeks&team=[Team Name]
Last 4 Weeks: https://sportsstatsgather.com/api/mlb/data/playerstats?stat_type=pitching&category=last_4_weeks&team=[Team Name]
   
Retrieve the following stats for both starting pitchers:
Name,Position,Team,pitching_[category]_ip,pitching_[category]_h,pitching_[category]_r,pitching_[category]_er,pitching_[category]_bb,pitching_[category]_so,pitching_[category]_hr,pitching_[category]_era
   
Where [category] is home, away, last_2_weeks, or last_4_weeks as appropriate.
   
## 2. Key Metrics Analysis
For each starting pitcher, analyze:
   
1. Home/Away Performance
   - Compare home vs. away stats (ERA, IP, H, R, ER, BB, SO, HR)
   - Identify significant differences in performance based on location
   
2. Recent Performance Trends
   - Compare 2-week and 4-week stats
   - Identify improving or declining trends
   
3. ERA and Run Prevention
   - Analyze ERA for each split
   - Consider runs allowed (R) vs. earned runs (ER) to assess fielding impact
   
4. Strikeout and Walk Rates
   - Calculate K/9 (SO * 9 / IP) and BB/9 (BB * 9 / IP) for each split
   - Assess changes in control and dominance
   
5. Home Run Vulnerability
   - Calculate HR/9 (HR * 9 / IP) for each split
   - Consider how this might interact with the opposing lineup and ballpark factors
   
6. Efficiency
   - Analyze H/IP (Hits per Inning Pitched) for each split
   - Consider impact on potential WHIP (Walks plus Hits per Inning Pitched)
   
## 3. Comparative Analysis
1. Pitcher vs. Pitcher Comparison
   - Compare the starting pitchers' home/away splits and recent performance
   - Identify which pitcher has the advantage in the current game context
   
2. Matchup Against Opposing Lineup
   - Consider how each pitcher's recent performance and home/away splits match up against the opposing team's batting tendencies
   - Identify potential favorable or unfavorable matchups
   
3. Consistency and Reliability
   - Compare the consistency of performance across different splits
   - Identify which pitcher shows more reliable recent form
   
## 4. Context Considerations
1. Ballpark Factors
   - Consider how the game's venue has historically affected each pitcher's performance
   - Adjust expectations based on known park factors
   
2. Innings Pitched
   - Analyze the IP in each split to assess pitcher endurance and consistency
   - Consider how this might affect bullpen usage in the upcoming game
   
3. Hit and Run Prevention
   - Compare H/9 and R/9 across splits to assess overall effectiveness
   - Consider how this might influence game strategy
   
## 5. Predictive Insights
Based on the detailed pitching analysis:
1. Predict which starting pitcher has the advantage in this specific game context
2. Identify key areas where each pitcher might struggle or excel
3. Suggest how the pitching matchup might influence overall game strategy (e.g., lineup construction, in-game management decisions)
   
## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Each starting pitcher's home/away splits (ERA, K/9, BB/9, HR/9)
2. Recent performance trends (last 2 weeks vs. last 4 weeks)
3. Notable strengths and weaknesses in the current game context
4. How each pitcher's recent form and splits match up against the opposing lineup
5. Predicted pitching advantage based on the analysis
   
Ensure this information is clearly labeled and easily retrievable for the final analysis.
   
## Final Thoughts
Synthesize how the detailed pitching analysis (home/away splits and recent performance) might interact with other factors (e.g., team offensive capabilities, ballpark factors) to influence the game outcome. Consider the limitations of the available data (e.g., lack of WHIP, W-L record) and how to best use the provided statistics for predictive analysis. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.
   
## Important Note
Ensure that you have provided a comprehensive analysis of ALL listed statistics for BOTH starting pitchers. Do not skip or minimize any metric, as each provides valuable insight into pitcher performance and potential game outcomes.
   
Before concluding your analysis, double-check that you have included:
1. A detailed analysis of each listed metric for both starting pitchers
2. Comparative analyses between the two pitchers across all metrics and splits
3. Considerations of how these pitching stats might specifically impact the upcoming game
   
If any part of this analysis is missing or incomplete, go back and add the missing information before proceeding.

Prompt 10 - Bullpen Usage and Situational Trends:

# Bullpen Usage and Situational Trends Analysis

Use the Sports Stats Gather MLB API to analyze BOTH bullpen usage AND situational performance trends for both teams in the upcoming game. It is crucial to provide information on BOTH aspects for EACH team.
   
## 1. Bullpen Usage Analysis
Endpoint: https://sportsstatsgather.com/api/mlb/data/bullpenusage/team?team=[Team Name]
   
Retrieve for both teams:
TEAM,PLAYER,THR,PROJECTED ROLE,[6 date columns for pitch counts],vFA,vSI,G,IP,ERA,Sv,HLD,K/9,K%
   
Note: The 6 date columns represent the most recent 6 days of pitcher usage, with the most recent date in the leftmost column. These dates will update daily.
   
### Key Metrics Analysis:
1. Workload
   - Analyze pitch count data for the last 6 days (represented by the 6 date columns)
   - Note: These columns reflect the Pitcher Usage (pitch counts) for the most recent 6 days
   - Identify heavily used relievers and those who are well-rested based on recent pitch counts
   - Pay special attention to usage patterns, including back-to-back days and high pitch count outings
   
2. Performance
   - Evaluate ERA, K/9, and K% for key relievers
   - Assess save (Sv) and hold (HLD) conversion rates
   - Consider how recent workload might impact performance
   
3. Roles
   - Identify the closer, setup men, and key middle relievers based on PROJECTED ROLE and recent usage
   - Note any recent changes in bullpen roles as evidenced by usage patterns
   
4. Pitch Velocity
   - Analyze vFA (fastball velocity) and vSI (sinker velocity)
   - Flag any significant velocity differences among relievers
   
### Comparative Analysis:
1. Compare overall bullpen strength between the two teams
2. Identify which team has fresher arms for the upcoming game based on recent pitch counts
3. Assess the depth and versatility of each bullpen
   
## 2. Situational Performance Trends
Endpoint: https://sportsstatsgather.com/api/mlb/data/situationtrends/team?team=[Team Name]
   
Retrieve for both teams:
Situation,Team,Win-Loss Record,Win %,MOV,Run Line +/-
   
### Key Situations to Analyze:
Analyze all situations provided in the data, which may include:
1. All Games
2. Home/Away Performance
3. As Favorite/Underdog
4. Various rest situations
5. Any other situations present in the data
   
### Trend Analysis:
1. Overall Performance
   - Evaluate win percentage and run line performance across all situations
   - Identify situations where each team significantly over/underperforms
   
2. Home vs. Away Trends (if present)
   - Compare home and away performance for each team  
   - Assess how the current game's location might impact each team
   
3. Favorite/Underdog Dynamics (if present)
   - Evaluate how each team performs when favored or as an underdog
   - Consider the current game's line in this context
   
4. Rest Impact (if present)
   - Assess how different rest scenarios affect each team's performance
   - Consider the current rest situation for both teams

5. Margin of Victory (MOV)
   - Analyze the average margin of victory in different situations
   - Identify trends in close games vs. blowouts
	  
### Comparative Analysis:
1. Identify which team has more favorable situational trends for this specific game
2. Highlight key situational advantages for each team
	  
## 3. Predictive Insights
Based on BOTH the bullpen usage AND situational trends analysis:
1. Predict which team has the bullpen advantage for this game
2. Identify key situational factors that favor each team
3. Suggest how bullpen usage and situational trends might influence game strategy and outcome

## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Bullpen freshness assessment for each team
2. Top 3 most effective relievers for each team (based on ERA, K/9, and recent usage)
3. Key situational trends that strongly favor each team
4. Overall bullpen and situational advantage prediction
	  
Ensure this information is clearly labeled and easily retrievable for the final analysis.
	  
## Final Thoughts
Synthesize how bullpen usage and situational trends might interact with other factors (e.g., starting pitching, offensive capabilities) to influence the game outcome. Consider how these factors might impact in-game management decisions and late-game scenarios. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.

## Important Note
Ensure that you have provided a comprehensive analysis of BOTH the Bullpen Usage AND Situational Trends for EACH team. Do not skip or minimize either aspect, as both are crucial for an accurate assessment of the teams' current states and potential performance in the upcoming game.
	  
Before concluding your analysis, double-check that you have included:
1. A detailed bullpen usage analysis for both teams, including recent workload and performance metrics
2. A thorough situational trends analysis for both teams, covering all provided situations
3. Comparative analyses that consider both bullpen usage and situational trends for each team
	  
If either the Bullpen Usage or Situational Trends analysis is missing or incomplete for either team, go back and add the missing information before proceeding.

Prompt 11 - Advanced MLB Team Statistics:

# Advanced MLB Team Statistics Analysis
	  
Use the Sports Stats Gather MLB API to analyze advanced team statistics for both teams in the upcoming game. This analysis will provide deeper insights into each team's performance beyond traditional metrics.
	  
## Data Retrieval
Endpoint: https://sportsstatsgather.com/api/mlb/data/advteamstats?team=[Team Name]

Retrieve for both teams:
#,Team,TG,G,PA,HR,R,RBI,BB%,K%,ISO,BABIP,wOBA,wRC+,BsR,Off,Def,WAR
	  
## Key Metrics Analysis
For each team, analyze the following metrics:
	  
1. BABIP (Batting Average on Balls in Play)
   - Compare to league average BABIP
   - Assess potential for regression or sustainment of current performance
	  
2. BB% (Walk Percentage) and K% (Strikeout Percentage)
   - Evaluate plate discipline and contact skills
   - Compare to league averages
	  
3. ISO (Isolated Power)
   - Assess raw power output
   - Compare to league average ISO
	  
4. HR, R, and RBI
   - Analyze overall power and run production
   - Consider in context of PA (Plate Appearances)
	  
5. BsR (Base Running Runs)
   - Evaluate team's base running contributions
   - Consider impact on run scoring and offensive strategy
	  
6. Def (Defensive Runs Above Average)
   - Assess team's overall defensive contributions
   - Consider impact on run prevention and pitching support
	  
7. Off (Offensive Runs Above Average)
   - Evaluate team's overall offensive contributions
   - Compare to league average
	  
8. WAR (Wins Above Replacement)
   - Assess team's overall value compared to a replacement-level team
   - Consider in context of G (Games Played)
	  
9. wOBA (Weighted On-Base Average)
   - Evaluate overall offensive value
   - Compare to league average wOBA
	  
10. wRC+ (Weighted Runs Created Plus)
    - Assess overall offensive value
    
	  
11. TG (Total Games) vs G (Games Played)
	- Analyze if there's a discrepancy and its potential impact on other stats
	  
## Comparative Analysis
1. Offensive Comparison
   - Compare wRC+, wOBA, ISO, and BB% between the two teams
   - Identify which team has the overall offensive advantage
	  
2. Defensive Comparison
   - Compare Def values between the two teams
   - Assess which team has the defensive edge
	  
3. Base Running Comparison
   - Compare BsR values
   - Evaluate potential impact on game strategy
	  
4. Overall Value Comparison
   - Compare team WAR totals and WAR/G (WAR per game played)
   - Assess which team has been more valuable overall this season
	  
5. Power and Run Production
   - Compare HR rates (HR/PA), R/PA, and RBI/PA between teams
   - Identify which team has been more efficient in these areas
	  
## Predictive Insights
Based on the advanced stats analysis:
1. Predict which team has the overall statistical advantage
2. Identify key statistical edges that could influence the game outcome
3. Suggest how these advanced metrics might inform game strategy and player utilization
	  
## Data Storage Instructions
Store the following key information in memory for use in the final prediction (Prompt 12):
1. Each team's wRC+, wOBA, ISO, and WAR/G
2. Notable statistical advantages for each team (e.g., significant edge in BB% or Def)
3. Any metrics suggesting potential regression or improvement (e.g., extreme BABIP)
4. Overall assessment of which team has the statistical advantage
	  
Ensure this information is clearly labeled and easily retrievable for the final analysis.
	  
## Final Thoughts
Synthesize how these advanced statistics might interact with other factors (e.g., pitching matchups, park factors) to influence the game outcome. Consider how these metrics might reveal hidden strengths or weaknesses that could be pivotal in the game. This synthesis will be crucial for informing the comprehensive game prediction in Prompt 12.
	  
## Important Note
Ensure that you have provided a comprehensive analysis of ALL listed advanced statistics for BOTH teams. Do not skip or minimize any metric, as each provides valuable insight into team performance and potential game outcomes.
	  
Before concluding your analysis, double-check that you have included:
1. A detailed analysis of each listed metric for both teams
2. Comparative analyses between the two teams across all metrics
3. Considerations of how these advanced stats might specifically impact the upcoming game
	  
If any part of this analysis is missing or incomplete, go back and add the missing information before proceeding.

Prompt 12 - Comprehensive MLB Betting Analysis with Underdog Focus:

# Prompt 12: Comprehensive MLB Betting Analysis with Underdog Focus

This is the final prompt in a series of 11. Your task is to synthesize all the information gathered from the previous 10 prompts (Prompts 2-11) to provide a comprehensive betting analysis with a specific focus on identifying the best underdog bet for the upcoming MLB game.
						
Underdog Team: [Paste Underdog Team]
						
## Game-Specific Recap
Briefly summarize the key points from each previous prompt, with an emphasis on factors that might favor the underdog:
Prompt 2: Park Factors and Scenario Stats 
Prompt 3: Injury Report and Game Log
Prompt 4: Overall Batting Stats
Prompt 5: Home/Away Batting Splits
Prompt 6: Recent Batting Performance
Prompt 7: RHP/LHP Performance
Prompt 8: Overall Pitching Stats
Prompt 9: Detailed Pitching Analysis
Prompt 10: Bullpen Usage and Situational Trends
Prompt 11: Advanced MLB Team Statistics
						
## Comprehensive Underdog Analysis
						
1. Identifying the Underdog:
   - Determine which team is the underdog 
   - Briefly explain why this team is considered the underdog
						
2. Park Factors, Scenario Stats, and Weather Impact:
   - Analyze how park factors might benefit the underdog
   - Identify any scenario stats where the underdog excels
   - Assess how weather conditions might particularly benefit the underdog team
						
3. Injury and Recent Performance Impact:
   - Assess how injuries or recent game results might unexpectedly favor the underdog
						
4. Offensive Potential:
   - Evaluate the underdog's offensive strengths, considering overall stats, home/away splits, and recent performance
   - Highlight any platoon advantages against the opposing pitcher (RHP/LHP performance)
						
5. Pitching Matchup:
   - Analyze how the underdog's pitcher might outperform expectations, using overall and detailed pitching stats
   - Identify any weaknesses in the favorite's pitcher that the underdog could exploit
						
6. Bullpen Comparison:
   - Analyze if the underdog's bullpen could be a key factor in an upset, considering recent usage and situational trends
						
7. Advanced Metrics Insight:
   - Utilize advanced team statistics to uncover any hidden advantages for the underdog
						
8. Favorite's Strengths and Weaknesses:
   - Briefly analyze the favorite's key strengths and potential vulnerabilities
   - Consider how these factors might impact the underdog's chances
						
9. Specific Matchup Dynamics:
   - Evaluate the starting pitcher matchup in detail
   - Identify key player matchups that could influence the game outcome
						
## Value Bet Analysis
				
1. Underdog Win Probability:
   - Estimate the underdog's true win probability based on your analysis
   - Compare this to the implied probability from the betting odds
						
2. Value Assessment:
   - Calculate the expected value of betting on the underdog
   - Explain why this bet might be undervalued by the market
						
3. Risk Analysis:
   - Identify the key risks associated with betting on this underdog
   - Discuss how these risks compare to the potential reward
						
4. Alternative Underdog Bets:
   - Assess the value of other underdog bets (e.g., run line, team total over)
   - Compare these to the moneyline bet in terms of risk/reward
					
5. Contrarian Factors:
   - Identify any factors that go against public perception and might be overlooked
						
## Final Prediction and Bet Recommendation
						
1. Underdog Bet Recommendation:
   - Clearly state your recommended underdog team and specific bet type(s). Consider:
     * Moneyline
     * Run line
     * Team Total (TT) Over/Under
     * Game Total Over/Under
		
   - Provide a detailed rationale for each recommendation
						
2. Game Script Projection:
   - Predict whether the game is likely to be high or low scoring
   - Explain how this projection influences your bet recommendations
						
3. Confidence Rating:
   - Assign a confidence rating (1-100%) to each of your bet recommendations
   - Explain the reasoning behind these ratings
						
4. Optimal Bet Sizing:
   - Suggest appropriate bet sizes based on the perceived edge and confidence level for each recommended bet
						
5. Alternative Scenarios:
   - Briefly discuss under what circumstances you would avoid betting on the underdog
   - If the underdog bet doesn't offer value, explain why and whether there's value elsewhere
						
## Important Considerations
   - Ensure that insights from ALL previous prompts (2-11) are incorporated, focusing on how they might reveal underdog value
   - Prioritize factors that could lead to an upset or a closer game
   - Be explicit about the balance between potential reward and risk for the underdog bet
   - Consider how different factors might interact to create unexpected advantages for the underdog
						
Remember, the goal is to find the most valuable bet possible, with a focus on the underdog. Only recommend the underdog bet if it truly offers positive expected value based on your comprehensive analysis. If no value is found in betting the underdog, clearly explain why and whether there's value elsewhere or if it's best to avoid betting on this game.

Let’s also take into account any outliers that influenced your decision to select this team to win, along with your level of confidence in the choice.

ChatGPT Tested Prompts 10/9/2024

MLB Prompts for Sports Stats Gather GPT

MLB Lineups and Pitchers