Відео

Much love for Sam, Ghettobob, Nick and everyone behind the best huddle ever!

Thank you

Classic reddit just being a useless echochamber. I’ve been looking into sports analytics, seems interesting! I only have a minor in stats though (major in a business field) so i’m not sure how much of a chance i have against stats majors 😅

When yo use traditional statistical models like arima and when to do boosting

wtf, you just only explain the code with the command. IDK what can I get from your video ?

It feels like coach John Montana has a lot of red challenge flags at his disposal.

Goots

I found this tutorial very helpful and really helped a beginner/student like myself. Keep it up!

Homenick Plaza

I just found your channel and it rocks. I’ve always love sports data and didn’t realize I could deal with it for a living. Currently pursuing this career and your channel is motivating and the videos get me pumped about what I could be doing every day for a living

What do you think about the Pro Sports Career Fair? How about a path for advancement within the Sports Industry?

Deep learning perform the best for time series but it to takes an insane amount of hyper parameter optimization and much more processing power.

szns = ['2019', '2020', '2021'] target_seasons = [x for x in szn_folders if x in szns]

Nick, I just found your channel. I’ve been building weird robotics/Arduino projects for years. In fact in the last year I’ve taken a job as a robotics programming engineer as a career(no degree) due to some of my projects. Was wondering if you’d provide some insight/help for integrating twitch chat with robotics? I’d like to start streaming, and man this video was right up my avenue, probably gonna buy that arm. But my projects a bit different… includes twitch chat to Arduino to IR sender… let me know! I’d love some advice.

I have been a good Bing. 😊

That’s interesting on strike’s review. A pitcher is out of the heart zone. How do u get a pitcher with “the potential “ to get some of those balls to be more strikes. Knowing he can’t throw a strike when asked too… interesting

I see u did not opt pd.option… was it because the level of your target or is it bad practice

@4:01 - create a list of the seasons you want to include and do a nested list comprehension using any. this helps too so if you ever want to add more seasons, you just edit the variable value instead of changing the code in the list comp desired_seasons = ['2019', '2020', '2021'] target_seasons = [season for season in seasons if any(target in season for target in desired_seasons )]

This was Herbert second season so a big jump not surprising. Adding some sort of age curve to this might also be smart

Great video. For anyone that cares Matt Stafford no only switched teams but also played in the super bowl that year giving him 4 additional games. This model would be significantly better if you limited it to regular season only and maybe strip out players who switched teams

how do you get the data?

27:11 Thank you for the hello. Hello.

It’s a shame you don’t respond to anyone in here asking questions for support. Not a good strategy for building a following!

Explained very well thanks bro

Does this only work with csv? Or can this be an Excel sheet

25:42 Can we like put colors to the top 5 Preds so if we are like looking to "buy" a new quarterback we can go for the top 5... I don't think you need all the 20 seasons, usually a player play at the top level 5-7 seasons..

15:02 Previous interceptions has nothing to do with the "next year touchdowns" because, the interceptions might be fault of the offensive player that did not catch the ball... or did not read the play very well and the defend just got the ball on the go... for newbies... we see that the correlation is so weak in that graphs "touchdowns and interceptions_prev" the line blue is not so high.

14:43 I have never understood the scatter plot graph.... what means when the points are together? what means when the points are far away... I can see a blue line and then a gray line together with the blue line......... ------- ANSWER ----------- Points Close Together: When the points on a scatter plot are close together, it indicates that the variables have a strong relationship or correlation. The closer the points are to forming a straight line (whether upward or downward), the stronger the relationship between the two variables. Points Far Apart: If the points on the scatter plot are spread out widely, it implies a weak relationship or correlation between the two variables. A wide spread of points that do not form a clear line suggests that other variables might be influencing the outcome, or there might be a low correlation between the two variables being plotted. Blue Line (Trend Line): Often, a scatter plot will include a trend line, usually in blue or another distinct color, which shows the overall direction or pattern of the data. If the trend line is upward (from left to right), it indicates a positive correlation between the variables; if it's downward, it indicates a negative correlation. The trend line is a mathematical model (often a linear regression line) that best fits the data points. Gray Line: The gray line could represent a few different things, but commonly, it might indicate a confidence interval or prediction interval around the trend line. This shows the range within which we expect future data points to fall with a certain level of confidence. Alternatively, if there are two lines (blue and gray), the gray line might represent another data set for comparison or a different model's predictions.

13:56 maybe you can get rid of all nan values.... just dropping it or fill those NaN with the mean..

Thanks for posting this! Was lost for most of it but I liked hearing you talk through some of the processes!

I am a 35 year old intern starting a career in analytics. Thank you for this

Are these pursuit curves individual to the player? I am curious if the pursuit path is using the max game running speed for the individual, as a static measurement (i.e, 40 yard dash), or something else?

You need Scott Miller on your team next time.

How can I get this type of CSV from 2023-2024 season?

That Sam guy would be great choice as intern!

Thank you, kind sir.

That Big Data Bowl team better get their stuff together... the deadline is in 4 weeks.

I've just watched week 5 but couldn't comment there because you turned off the comments, just wanted to say that as a junior data scientist student really enjoy your videos and I've been taking your free data science Bootcamp and it's fabulous, thanks for that. BTW it would be really interesting to see you working on soccer projects also.

Subscribed!

What's up Hai Davaii Nation!!!

Holly: First.

legendary

lmao amazing

Hi Nick, is there a way to implement machine learning into pooled OLS regression, fixed effect and random effect regressions too?

Bring back Sliced! Bring back Sliced!! Bring back Sliced!!! We need more slices 😃

"chicken feed"

Poor Andy

Well... did you send it?

Bruh

Best video on UA-cam today, made my day. Thanks