Division Strengths

[Rob]

Hi Ed,

I think this is very interesting, but I have a question. Please let me start by saying that I have a general idea how the math for this works, but I am not overly mathematically inclined so the details elude me.

My thought is that since the set of data that a teams performance is being calculated from comes from single events (each event having a set of teams), that the results of that data are best used to compare to other teams at the same event.

To properly compare one team from the midwest against a team from southern California, those teams would have had to compete at the same event.

Am I totally off base here of is there some validity to my assumption?

For example, if the MI state event had all great teams, could that not adversely impact the performance numbers of the top teams. Good teams score on you more (you get worse DPR) and are harder to score on (you get lower OPR).

I am not trying to invalidate your data, I think it is an amazing tool. I just have a hunch that it is most useful for comparing teams at the same events together. To compare teams globally they would have to be at the same events together (I think)

Now the top teams should still have good performance numbers no matter where they compete, but I think the numbers can only tell so much.

Sorry for the lengthy post, and thanks for making this data available, it does help quite a bit even if my understanding of it is limited!

[ScottOliveira]

Originally Posted by Rob

Hi Ed,

I think this is very interesting, but I have a question. Please let me start by saying that I have a general idea how the math for this works, but I am not overly mathematically inclined so the details elude me.

My thought is that since the set of data that a teams performance is being calculated from comes from single events (each event having a set of teams), that the results of that data are best used to compare to other teams at the same event.

To properly compare one team from the midwest against a team from southern California, those teams would have had to compete at the same event.

Am I totally off base here of is there some validity to my assumption?

For example, if the MI state event had all great teams, could that not adversely impact the performance numbers of the top teams. Good teams score on you more (you get worse DPR) and are harder to score on (you get lower OPR).

I am not trying to invalidate your data, I think it is an amazing tool. I just have a hunch that it is most useful for comparing teams at the same events together. To compare teams globally they would have to be at the same events together (I think)

Now the top teams should still have good performance numbers no matter where they compete, but I think the numbers can only tell so much.

Sorry for the lengthy post, and thanks for making this data available, it does help quite a bit even if my understanding of it is limited!

You definitely have a valid point, the data could be skewed by overall team quality at a given competition. However, it is generally safe to assume that the average team quality at all of the regional competitions is comparable. Consider that a lot of the good teams travel to multiple regionals, helping to balance things between.

Also consider that given the limited data available, this is roughly as accurate as you can get. There are too many variables for a perfect set of data. You could also consider that performances at regionals later in the season might be different, as those teams have had more time to code/practice, and are more likely to have already competed in a regional.

Yes, the data isn't perfect and there are many variables that could affect the rankings, but it's as good as is possible.

[Ed Law]

Hi Rob,

You are absolutely correct. However it is still good to compare teams who attend different regionals. I can not believe there is such a big difference in terms of competitiveness among most of the regionals. I am sure there may be a few that are particularly weak.

After we come back from Atlanta, may be during the summer months when I suffer from FRC withdrawal symptom, I will try to assemble all the teams and all the matches into one giant 1674 X 1674 matrix. Then all the interactions will be taken into account. There are quite a few Michigan teams that went to other regionals also. Since I don't invert the matrix to solve for OPR and CCWM, it should not even take that long to solve.

Ed

[LWakefield]

What is OPR?

[Collin Fultz]

Originally Posted by LWakefield

What is OPR?

From this thread...

Originally Posted by Lil' Lavery

Offensive Power Ranking

It is a calculated quantity based on your and your alliance partners match scores. It is designed to figure out each team's individual contributions to the final score of the match.

[Rob]

Thanks for the clarification Ed. I am sure that you are correct in that most regional events have similar strength. These numbers are a great way to begin preliminary scouting efforts. The ability of your sheet to update in real time is very valuable as well.

Originally Posted by LWakefield

What is OPR?

In post #1 of this thread Ed has a link to a paper explaining what these numbers mean.

Thanks

[cziggy343]

i would like to know how the OPR was calculated this year. it seems like it would be very hard to keep up with...

[Lil' Lavery]

Originally Posted by cziggy343

i would like to know how the OPR was calculated this year. it seems like it would be very hard to keep up with...

Same way it's calculated every year. A augmented matrix is created by inputting every match score and each team that competed in that match. Each "team" is essentially a variable that is solved for, giving the OPR for that team.
The "DPR" can be created by using the opposing alliance's score in the augmented column.

[Huskie65]

Originally Posted by Rob

Hi Ed,


For example, if the MI state event had all great teams, could that not adversely impact the performance numbers of the top teams. Good teams score on you more (you get worse DPR) and are harder to score on (you get lower OPR).

I am not trying to invalidate your data, I think it is an amazing tool. I just have a hunch that it is most useful for comparing teams at the same events together. To compare teams globally they would have to be at the same events together (I think)

I totally agree with this. With all good teams there are alot less blowouts. Harder to score. Your defensive and offensive ratings naturally go down by playing better teams.

[Ed Law]

Originally Posted by Huskie65

I totally agree with this. With all good teams there are alot less blowouts. Harder to score. Your defensive and offensive ratings naturally go down by playing better teams.

That is why I used the OPR and CCWM numbers before the MI State Championship for MI teams. After the Championship, about half of the teams' CCWM went down because even if all the teams are good, about half of them are going to get positive CCWM and half of them are going to get negative CCWM.

Ed

[IKE]

While the divisions overall may be reasonably even, if you look at the top 24 (those likely to play in Elims), there is a pretty considerable discrepancy.

Taking the top 2 and the 24th of each divsion, I can see a bit more of a discrepancy. Curie and Galileo look quite a bit stronger than Newton and Archimedes. There is also a big gap in abilities on the top two in Curie and Galileo which could be inferred as a better odds at one of those two making it to the top seed.

IKE

[Katie_UPS]

So while this thread is really cool, and the numbers are kinda helpful, and I can see the competitiveness of the devisions and all the wotnot, I just have to ask...

Where do you find the time?

From what you said, my basic idea is that you make a matrix for each team and then average it out. Thats.. what? 400 teams?

[Ed Law]

Originally Posted by Katie_UPS

So while this thread is really cool, and the numbers are kinda helpful, and I can see the competitiveness of the devisions and all the wotnot, I just have to ask...

Where do you find the time?

From what you said, my basic idea is that you make a matrix for each team and then average it out. Thats.. what? 400 teams?

All the data was mined from the usfirst.org website. Nothing was done by hand. It was all done in an Excel spreadsheet. This spreadsheet was posted for all FRC teams to use. I just rearranged the numbers to create the graphs. It probably took me about 15 minutes to do it. However the spreadsheet took me over 100 hours to do over a span of a few months. It is a way for me to give back to the FIRST community.

Ed

[ScottOliveira]

Originally Posted by Ed Law

All the data was mined from the usfirst.org website. Nothing was done by hand. It was all done in an Excel spreadsheet. This spreadsheet was posted for all FRC teams to use. I just rearranged the numbers to create the graphs. It probably took me about 15 minutes to do it. However the spreadsheet took me over 100 hours to do over a span of a few months. It is a way for me to give back to the FIRST community.

Ed

And definitely something we appreciate .