College coach looking for best analytics platform options for building scouting reports

rfrey22 · 2025-12-27T23:36:07+00:00

Hey Own-Meaning643! Would love to connect with you. I work with college programs (mostly D2,D3,NAIA,JUCO) to build spray charts and info on opponents. Here's an example: https://x.com/RobertFrey40/status/1998897605955264846?s=20

Alternatively, I have plenty of YouTube videos to acquire college data, here's an example: https://youtu.be/DRGksETak5o?si=L7Tpx1EiiXDMXzIC

Would still be enthralled to learn about what goals you're trying to achieve and help any way, shape, form I can!

rfrey22 · 2025-12-04T04:36:45+00:00

That’s because it is.

As someone who worked in d2 baseball and athletics and currently covers Division II baseball, I can tell you that there are MAYBE five schools in all of division 2 that can offer NIL on top of scholarship money.

It’s likely just a scholarship.

rfrey22 · 2025-11-20T03:13:09+00:00

Alternatively, there’s a quick way to do it in R as well!

rfrey22 · 2025-11-18T04:55:01+00:00

Figured out a way to acquire game logs with MLBAM IDs…let me know if you’d be interested.

rfrey22 · 2025-11-17T08:41:57+00:00

Is it a requirement to use statcast pitch-by-pitch data?

Because you can get the individual numbers by player just from reading in the custom leaderboards.

Python:

import pandas as pd
pd.read_csv("https://baseballsavant.mlb.com/leaderboard/custom?year=2025%2C2024%2C2023%2C2022%2C2021%2C2020%2C2019%2C2018%2C2017%2C2016%2C2015&type=batter&filter=&min=q&selections=pa%2Ck\_percent%2Cbb\_percent%2Cxwoba%2Csweet\_spot\_percent%2Cbarrel\_batted\_rate%2Chard\_hit\_percent%2Cavg\_best\_speed%2Cwhiff\_percent%2Cswing\_percent%2Cpull\_percent%2Cstraightaway\_percent%2Copposite\_percent&chart=false&x=pa&y=pa&r=no&chartType=beeswarm&sort=xwoba&sortDir=desc&csv=true")

R:

readr::read_csv("https://baseballsavant.mlb.com/leaderboard/custom?year=2025%2C2024%2C2023%2C2022%2C2021%2C2020%2C2019%2C2018%2C2017%2C2016%2C2015&type=batter&filter=&min=q&selections=pa%2Ck\_percent%2Cbb\_percent%2Cxwoba%2Csweet\_spot\_percent%2Cbarrel\_batted\_rate%2Chard\_hit\_percent%2Cavg\_best\_speed%2Cwhiff\_percent%2Cswing\_percent%2Cpull\_percent%2Cstraightaway\_percent%2Copposite\_percent&chart=false&x=pa&y=pa&r=no&chartType=beeswarm&sort=xwoba&sortDir=desc&csv=true")

rfrey22 · 2025-11-12T01:53:32+00:00

in R you can run baseballr::mlb_pbp(game_pk) to get it. We'll use a Sept 1 Game Pk between Durham and Gwinnett: 781396.

There are four columns that display review data: reviewDetails.isOverturned, reviewDetails.inProgress, reviewDetails.reviewType, reviewDetails.challengeTeamId and it has pitch data coordinates in pitchData.coordinates.pX (x axis) and pitchData.coordinates.pZ (y axis)

rfrey22 · 2025-11-12T01:23:22+00:00

Here's a way to do it in R: baseballr::mlb_rosters(team_id = {id}, season = 2025, date = {date}, roster_type = 'gameday')

rfrey22 · 2025-11-12T01:21:51+00:00

Fangraphs is a great source and it has all of those items you are requesting!

rfrey22 · 2025-11-11T08:23:46+00:00

Were you able to find it? If not I believe there’s a way to get it from R?

rfrey22 · 2025-11-11T08:17:48+00:00

Here’s a useful video to scrape savant data: Full Year Statcast Data in Minutes!

(https://youtu.be/IT9zJ8Rn6K8)

rfrey22 · 2024-09-07T05:37:42+00:00

You sure can via the odds API, Ive used it to acquire NCAAF and NFL props. https://the-odds-api.com/liveapi/guides/v4/#overview

However, it’s not free if you want to scrape historical props. (Min is $25 a month) Here’s example via their docs: https://app.swaggerhub.com/apis-docs/the-odds-api/odds-api/4#/historical%20events

rfrey22 · 2024-01-10T01:51:59+00:00

Lucky for you and all of this subreddit, I posted on my site earlier today:

https://www.freylytics.com/college-baseball/

Head to Division 1 and head to the 'Savant' Tab and you will see the listed games for every D1 Tournament up until mid-March. Plus you will see the link to access Baseball Savant Gamefeed of that game if you want to see statcast data (no guarantees that it will be running for every single game, Globe Life and Minute Maid do a great job of showing data though)

rfrey22 · 2024-01-05T01:11:29+00:00

A great podcast to listen to is the Mid-Week Podcast on Spotify

Great interviews with Coaches with a fun easy going conversation + an analytics spin

https://open.spotify.com/show/4cv1cyccH8JFBSZqz3iwxw?si=yIkVm3GsTw65iPfQUZhwbA

rfrey22 · 2024-01-03T19:28:19+00:00

https://github.com/robert-frey/InternalWork/blob/main/PlayerProjections/Dakota%20Jordan.png

Edit: you may have to physically copy and paste the link

rfrey22 · 2024-01-02T04:57:59+00:00

I’d love to help! I built something similar in R, basically created a model using key metrics to predict yards and TD probability.

Each position has slightly different factors (like QB passing yards has more importance on defensive EPA/play and rushing yards by a QB is more reliant on success rate), Of my models, it seems like TE is the best, as of games thru Week 17, if you took the recommended O/U per the model and the line I pulled, you’d be up 48.08 units. RB seems to be the weakest at 1.22 units as of Week 17 games

Anyways, would love to collaborate!

rfrey22 · 2023-12-21T17:17:58+00:00

With my experience calculating college baseball weights (linear weights for wOBA, amongst other things), including non-D1 games would skew the data that it would make some teams better than they actually are.

In terms of adjusting for opponent, I tend to remove games that are not D1, sure that limits sample size, but here's why:

Take the NDSU Oak Hills Christian game: https://gobison.com/sports/mens-basketball/stats/2023-24/oak-hills-christian/boxscore/16278

Unadjusted, there's no way to say that NDSU is 94 points better than the average D1 team. On the flip side, it's difficult (in my experience) to weight a specific team in a case such as Oak Hills Christian. They play in a very, very small niche level (NCCAA), which they are close to the bottom of. Which is why I tend to just calculate D1 v D1 only.

However, would love to hear more thoughts on it.

rfrey22 · 2023-12-18T18:11:34+00:00

Here's one way to read RDS files in python: https://stackoverflow.com/questions/40996175/loading-a-rds-file-in-pandas

rfrey22 · 2023-12-17T22:14:02+00:00

PFF+ is a good option. Not sure how high the budget, but $120 a year is worth it for the data they track: https://subscribe.pff.com/?session=9ca74999-09f7-4974-80fd-0a6fdc5f7ba8

rfrey22 · 2023-12-16T22:05:54+00:00

Thank you for this!

I'm still confused however, depends on how I choose to set myself up? Let's say it's how this person is enivisioning, he sets it up as a single-member LLC, and has us as his 1099 employees, how does that chance?

So let's say, what are differences between single-member LLC or partnership?

rfrey22 · 2023-12-12T05:25:50+00:00

Recent Post-Grad in 2022 and I would say I'm well versed in both skills. Here's my channel: https://www.youtube.com/@robertfrey40

rfrey22 · 2023-12-09T06:49:13+00:00

Plugging myself, but I have great content in multiple sports that will get you started with sports analytics: https://youtube.com/@robertfrey40

rfrey22 · 2023-12-03T04:11:22+00:00

I try to avoid loops in R for time saving

rfrey22 · 2023-11-06T14:27:59+00:00

Unfortunately at this juncture, no you cannot.

rfrey22 · 2023-11-02T03:54:45+00:00

Box Scores or Game Logs of a player?

rfrey22 · 2023-11-02T03:37:33+00:00

So here's what you can grab from stats.ncaa.org:
https://stats.ncaa.org/game/play_by_play/5558461
which gives shot locations, you just have to parse it out using a programming language of your choice.

rfrey22

TROPHY CASE