Rank these following critieria from most important, to least important for field scouting, in your humble opinion
Balls Score
Balls Shot
Scoring percentage (Balls Scored/Balls Shot)
Human Player Balls scored
Human Player Balls Shot
Human Player Scoring percentagae
Balls in own trailer
Speed
Traction
Strength
Autonomous Balls Scored
Empty Cell transported
Super Cell Scored
Driving Skill
Feel free to add anything you i might have overlooked. I listed these in no real order
a mix of scoring percentage and driver skill/control (the driver could be great, but if the robot doesn’t do what its told, its not good)
3 Scoring percentage (Balls Scored/Balls Shot)
6 Human Player Scoring percentagae
1 Balls in own trailer
9 Speed
8 Traction
10 Strength
7 Autonomous Balls Scored
5 Empty Cell transported
4 Super Cell Scored
2 Driving Skill
1 = most critical
10 = least critical
I think that the most important thing is the difference between the team’s score and how much it is scored on, since that is it’s overall effect on the match.
I think that traction will be the most valuable skill in this competition.
Balls Score - Very Important Typically, how many game pieces a robot scores on average is a good indicator if a robot is draftable
Balls Shot - Sort of Important
Scoring percentage (Balls Scored/Balls Shot) - Sort of Important
Human Player Balls scored - Very Important Human player results can differ drastically, and adding their game pieces scored to the robot total should give you a good idea about how the team performs as a whole each match
Human Player Balls Shot - Sort of Important
Human Player Scoring percentagae - Sort of Important
Balls in own trailer - Important This is a good indicator of the evasiveness of the robot and the skill of the driver.
Speed - Not Important Not a field scouting item
Traction - Not Important Not a field scouting item
Strength - Not Important Not a field scouting item
Autonomous Balls Scored - Sort of Important For this game, it is just good to know what your opponents do in autonomous period.
Empty Cell transported - Important You need to know how a robot spends its time during a match, and manipulating empty cells takes away from harvesting and scoring time.
Super Cell Scored - Important However, depending on how the game plays out, the super cell may end up acting just like another moon rock in robots’ mechanisms.
Driving Skill - Not Important A much better indicator of driving skill than a subjective field is analyzing the other data fields mentioned above.
Add also:
Team Moon Rocks/Super Cells scored (Robot + Human Player)
team compatablity (how well your team gets along with the other)
Driving Skill
ball pick up from floor
Balls Score
Balls Shot
Autonomous Balls Scored
Scoring percentage (Balls Scored/Balls Shot)
Human Player Balls Shot
Human Player Scoring percentagae
Balls in own trailer
Speed
Traction
(in order per me)
The one thing that no one ever list in scouting but is one of the most important factors is reliability. I don’t care if the robot scores a hundred balls a match if I can’t count on you being out there for the next three because it’s a fragile as china.
While all exterior data should be recorded, especially given the random pairing of opponenets and allies in qualifications, there is ultimately only one stat that matters.
In hockey terms, “+/-”. How many points did they score (counting their human player) and how many were scored on them?
Assuming an evened schedule (of not only the “quality” of teams, but the play styles as well), this will show what teams are the best.
Now, given a 7-12 match sample size, it’s unlikely that a perfectly balanced schedule will be constructed. So, keep track of who the opponents and allies were, what their play styles were, and how they complimented/detracted eachother.
Look for outliers, and note the factors. Did a bot break down (on either alliance)? Did they have an alliance partner pin the opponent to help them score? Did they get pinned?
Note these outliers to see what play styles will best complimented their abilities, and use that knowledge to your advantage.
At the end of the day, these are really the only three that matter:
10 Balls Scored
0 Balls Shot (who cares how many they shoot, so long as they score?)
0 Scoring percentage (Balls Scored/Balls Shot)
0 Human Player Balls scored (this depends on how many balls they are fed)
0 Human Player Balls Shot (depends on how many balls they are fed)
10 Human Player Scoring percentage (you want the human player to score everything they are fed, especially supercells)
10 Balls in own trailer (if they score a lot but are scored on a lot, they are not useful)
0 Speed (if their speed is a problem, it will show in their balls scored and balls-in-own stats)
0 Traction (see comment for speed)
0 Strength (see comment for speed)
5 Autonomous Balls Scored (it might be useful to be able to score in this period, but at the end of the day, its balls scored throughout the match that counts)
5 Empty Cell transported (if they can do it, its handy)
0 Super Cell Scored (covered by HP%)
0 Driving Skill
Reliability is important to note because it might predict failures that could be preventable. If a robot has a preventable failure during a match, it might be a good idea to discount the +/- for that match.
I’ll separate these out into relevant vs totally non-relevant. Past there, the ranking will be different for each team depending on their strategy. We’ll also assume reliability & ability to communicate with their alliance is up there, as those are an ‘every year’ kind of thing.
Relevant attributes:
Balls Scored
Human Player Balls scored
Empty Cell transported
Traction (gives the ability to push/pin vs other robots)
The rest are irrelevant or are a result of performing something from the list above:
Autonomous Balls Scored (strategy dependent)
Balls in own trailer - this is an iffy one – it’s extremely difficult to control how well your opponents perform, especially with the pinning nature of this game
Balls Shot
Scoring percentage (Balls Scored/Balls Shot)
Human Player Balls Shot
Human Player Scoring percentagae
Speed
Strength
Super Cell Scored
Driving Skill
He gets it! 
All the random other stats (speed, traction, driving skill, etc) will be shown in the stats that actually matter, SCORING!
That being said, they should still be noted to determine play-style and strategy. If you know a team you’re going to play in the eliminations is good at pinning other bots, you’ll want fast partners who can avoid being pinned. Or if you know an opponent is good at picking off the floor, you’ll want bots who don’t miss much to reduce their effectiveness. Ultimately, those stats will matter less than the ones that actually change the outcome of the match.
It’s important to remember that you’re scouting with volunteer labor (typically anyways). If you make them record minute details, your scouts will get bored, which will affect their accuracy on the statistics that matter, and may simply rebel and stop recording period. We use mostly parents as round scouts (we’re a small team, students are busy keeping the robot running!), and most of them aren’t involved much with the game, so we keep it simple.
I’ll second this. Reliability is one of the most important things we take into account for our scouting. We watch every match a team has, and if they are having a lot of mechanical failures that is often one of the first teams removed from our list.
…and yet how do you quantify reliability? If not quantified, how do you assure that you’re making non-biased decisions?
There are ways.
Let’s say that a team is scoring 30-40 points per match, and then suddenly, for a match or two, they go down to 10-20. Then they go back up to 30-40 for a match or two, then down, then up. That’s an almost surefire indicator that they are not reliable. It may be that it’s different drive teams, or it may be something much more serious. Track me so far?
If a team is consistently getting broken, your scouts can also note that. The team’s performance will suffer if they can’t fix their robot for the next match.
There are a number of ways to do this, but you can almost certainly do it with the data you already collect.
For me, my biggest concerns this year are: 1: reliability; 2: points scored; 3: points scored on; 4: presence (or not) of an automode. 5 would be collected vs scored; 6, the HP. Other than that, where do they load up?
Simple. You create a “range” of scores you deem to be reliable (say, a range of +/-15 points from average). You see how many scores fall within that range of their average score and how many do not. You can then rank teams by reliability.
Aka standard deviation. The range of scores from (mean - 1 std. dev) to (mean + 1 std dev.) should hold 75% of all of the data points for a team. The smaller this number, the more consistency there is in the scoring. The great thing about it is that standard deviation is independent of the actual value of the mean (aka average). So if a team consistently scores +/- 15 points from an mean of 20 points per match (i.e. the range is a 5 point match low score to a 35 point match high score), that team will have the same standard deviation as a team who’s mean is way up there at 80 who also has a +/- 15 point range.
Then of course, it will be up to the scouts who are watching to eliminate out any outliers from the data. Outliers are matches in which (for example) both of your alliance partners did not work, which is not typical of a match your team is capable of, hence the reason for the very low score.
I agree with what Sean is saying.
However, there is/will be a type of robot that does not score, but may produce scoring attempts. The “little box on wheels” bot, that will be able to (try) and pin an opponent in hopes that their teammates can come and score on said opponent.
On a robot like this, speed/traction/driving skill/effectiveness/reliability will all be the MAIN factors, not the irrelevant ones.
That’s where you look at the “+/-” of the alliance (which can direct equate to score, but might not if you chose to eliminate penalties and/or super cells from the scouting data for this aspect) rather than the individual robot.
While this introduces additional variables (who were their partners), those variables should be able to be defined by the other data you have collected.
For example. Boxbot A is paired with Scorebot A.
If Boxbot A’s alliance +/- is considerably higher than usual, it’s likely that Scorebot A played a role in that.
If Scorebot A’s individual +/- is considerably higher than usual, it’s likely that Boxbot A played a role in that.
Reality will be more complex (you’d have to look at how good the opponents are at defense, the 3rd partner, etc), but you get the idea.