JO Stats and their meaningfulness

I’m moving this to a new thread.

I pulled the data from 18U Platinum. Peter S, was pretty dominant regardless of how you look at it. I looked at shooting % for players with at least 10 goals.

Team Player Name Games Goals Shots Shooting %
Greenwich Peter Saunders 6 33 43 77%
SD Dons Eamon Bruhn 7 16 21 76%
Lamo tristan tucker 5 12 17 71%
Trojan flynn guenther 6 18 27 67%
Pride Joshua Coxford 6 22 34 65%
SOCAL Aiden Sexton 4 11 17 65%
Trojan Caleb Yost 6 21 33 64%
SD Dons Diego Dantas 7 28 45 62%
SD Shores Aidan Johnson 5 12 20 60%
LA Premier Lukas Kovacevic 6 19 32 59%
Newport Tyler Anderson 7 16 27 59%
Atherton Claiborne Carrington 6 19 33 58%
SD Dons Kenly Axline 7 16 28 57%
Pride Yuri Davtyan 6 12 21 57%
Diablo Dane Fox 4 10 18 56%
Aetos DAVID GREENFIELD 6 16 29 55%
CIU Seniors wyatt williamson 6 19 35 54%
VNI Black Kyle Franks 5 13 24 54%
CIU B Nathan Rippe 5 12 23 52%
Stanford Chase Krupitzer 5 13 25 52%
CCU Ellis Culleton 5 14 27 52%
LJU Dexter Black 5 15 29 52%
Newport Kai Kaneko 7 18 35 51%
Aetos Evan Wu 6 19 37 51%
Norcal Nace Štromajer 5 24 48 50%
Atherton Oliver Marcin 6 15 30 50%
SD Shores hunter danko 5 14 28 50%
Imperial Jake Maniscalco 5 12 24 50%
Mission Joseph Wraith 6 12 24 50%
Atherton Edward Eiref 6 11 22 50%
Aetos Brahman Davis 6 10 20 50%
CCU William Maguy 5 14 29 48%
Pride jack lansing 6 10 21 48%
SFWPC Isaac Nikfar 5 13 28 46%
SD Dons JETT TAYLOR 7 12 26 46%
CIU B Lucas Neushul 5 10 22 45%
Diablo Sloan Brown 4 10 22 45%
Trojan Marcus Wooler 6 10 22 45%
Greenwich jackson shaw 6 25 57 44%
LJU Quinn Daniels 5 14 32 44%
Newport connor ohl 7 17 39 44%
Greenwich Roland Balazs Csendes 6 18 42 43%
CDM William Weir 5 23 54 43%
CIU B Grant Nelson 5 11 26 42%
CIU Seniors Darion Wang 6 10 24 42%
Imperial Isaac Squires 5 10 24 42%
Atherton Gates Gamble 6 20 49 41%
SD Dons Maximus Bruhn 7 18 46 39%
LA Premier Bence Fabian 6 24 62 39%
LJU ORIOL SANCHEZ CARRILLO 5 10 26 38%
SFWPC Nikita Alekhin 5 10 26 38%
SFWPC andrew wallace 5 11 29 38%
CIU Seniors Kane Fogg 6 10 27 37%
LA Premier Asher Chemerinski 6 10 27 37%
Aetos Tanner Gorman 6 10 28 36%
CIU B Brayden Rodriguez 5 10 28 36%
Newport Mason Netzer 7 12 37 32%
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I’ve been pretty interested in the value of shooting percentage and chastised 6-8 for not penalizing low percentage shooters.

This shows that for the most part, low shooting percentage leads to unfavorable results but higher doesn’t necessarily lead to better results. I suspect this data is skewed by the level of the competition and any shootouts (this could be significant as 8 goals on 9 shots in a long shootout can be impactful. 5 of the top 6 shooting teams had at least 1 shootout).

Lamo is a huge outlier.

Finish Team Games Avg Goals Avg Shots Shooting%
13 TROJAN 6 14.2 25.0 57%
1 SD DONS 7 15.1 29.6 51%
11 PRIDE 6 14.0 27.8 50%
12 GREENWICH 6 16.2 32.7 49%
19 VNI BLACK 5 13.4 27.2 49%
5 CCU 5 15.4 32.2 48%
4 STANFORD 5 10.4 23.0 45%
9 ATHERTON 6 12.5 27.7 45%
2 NEWPORT 7 13.4 29.9 45%
14 CIU SENIORS 6 12.5 27.8 45%
6 SD SHORES 5 11.4 25.8 44%
10 AETOS 6 12.7 29.0 44%
3 LAMO 5 11.8 27.8 42%
7 LJU 5 11.8 28.0 42%
17 LA PREMIER 6 13.7 32.7 42%
24 SHAQ 4 11.5 27.5 42%
20 SOCAL 4 11.3 27.3 41%
23 CIU B 5 11.6 28.2 41%
21 CDM 5 10.8 26.8 40%
15 SFWPC 5 10.6 26.4 40%
8 NORCAL 5 12.2 31.4 39%
22 DIABLO 4 9.3 24.0 39%
18 IMPERIAL 5 9.4 25.4 37%
16 MISSION 6 8.5 26.5 32%
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It is important to split the universe by ‘skill set.’ I ran the following analysis in order to understand what was a more important factor: defense of offense. When running the analysis as one sample, i.e., top 24 the results shows Offense was a more important factor


However, when I split the universe to three groups top 8 , next 8 and bottom 8 the results started to make sense where for top teams, when they play with each other, defense is a more important factor.

Expanding the analysis to the data @Gibson looked at, shows similar pattern, the more elite the team is, its placement correlates with its placement when you separate the data. First, the entire sample then splitting it into three groups.


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As for the importance of multiple scoring threats. This shows the scoring and shooting contribution by the top 3 scorers for each team. wp2024 can do his fancy regression analyses. :innocent:

1st 2nd 3rd Top 2 Top 3
Finish Team Goals Shots Goals Shots Goals Shots Goals Shots Goals Shots
1 SD DONS 26% 22% 17% 22% 15% 14% 43% 44% 58% 57%
2 NEWPORT 19% 17% 18% 19% 17% 13% 37% 35% 54% 48%
3 LAMO 20% 12% 15% 17% 12% 17% 36% 29% 47% 46%
4 STANFORD 25% 22% 15% 10% 12% 8% 40% 32% 52% 40%
5 CCU 18% 18% 18% 17% 12% 11% 36% 35% 48% 46%
6 SD SHORES 25% 22% 21% 16% 11% 12% 46% 37% 56% 50%
7 LJU 25% 21% 24% 23% 17% 19% 49% 44% 66% 62%
8 NORCAL 39% 31% 13% 17% 13% 16% 52% 48% 66% 64%
9 ATHERTON 27% 30% 25% 20% 20% 18% 52% 49% 72% 67%
10 AETOS 25% 21% 21% 17% 13% 16% 46% 38% 59% 54%
11 PRIDE 26% 20% 14% 13% 12% 13% 40% 33% 52% 46%
12 GREENWICH 34% 22% 26% 29% 19% 21% 60% 51% 78% 72%
13 TROJAN 25% 22% 21% 18% 12% 15% 46% 40% 58% 55%
14 CIU SENIORS 25% 21% 13% 16% 13% 14% 39% 37% 52% 51%
15 SFWPC 25% 21% 21% 22% 19% 20% 45% 43% 64% 63%
16 MISSION 24% 15% 18% 16% 18% 11% 41% 31% 59% 42%
17 LA PREMIER 29% 32% 23% 16% 12% 14% 52% 48% 65% 62%
18 IMPERIAL 26% 19% 21% 19% 11% 9% 47% 38% 57% 47%
19 VNI BLACK 19% 18% 13% 8% 12% 10% 33% 26% 45% 35%
20 SOCAL 24% 16% 18% 14% 16% 10% 42% 29% 58% 39%
21 CDM 43% 40% 15% 14% 13% 16% 57% 54% 70% 70%
22 DIABLO 27% 23% 27% 19% 8% 9% 54% 42% 62% 51%
23 CIU B 21% 16% 19% 18% 17% 20% 40% 35% 57% 55%
24 SHAQ 20% 19% 17% 17% 17% 12% 37% 36% 54% 48%
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Thank you Gibson, this is a good analysis. I think the stat that will separate teams by skill level, and ultimately determine their final placement, is 6-on-5 offense and defense, particularly 6-on-5 defense.

What are the bottom two charts on shot volume vs % telling us?

It just took the two factors you included in the table. the number of goal, mathematically, is just the product of Shooting Volume * Shooting % and it used both of them to explain the final placement. It just says that for the more skilled teams (high placement) the % is more important and for the lower end the volume as the % does not explain much.

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Yeah, there’s a lot more we could do with more details. You could go game by game and count all the exclusions and then see the PGs and PPGs, but that would be a pain to do and also only approximate.

Thank you for sharing this analysis. It is really difficult to draw a conclusion on the importance of defense vs offense. I have always felt that the defense makes or breaks a game. Then again, my son is a goalkeeper so there you go. The plots show a weak relationship so I would not draw any conclusions here. Interesting none the less.

Just curious. How does USWP determine 1st team, 2nd team, honorable mention for all American JO recognition. Do they use stats, talk to coaches, select only top 10 team platinum athletes etc.? Thanks

Each team from 1st through 15th in Platnium will get x number of spots to select players. From there each coach will select players from their club based on the number of spots allowed.

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This data is interesting. If I’m a coach in the bottom half of the rankings for average goals scored per game, I’d be foolish not to make offense my top priority. On the other hand, if I’m already in the top half in scoring but my overall ranking doesn’t reflect that, then it’s obviously time to hone in on defense.

Too many American coaches get carried away with defense and fail to recognize that offensive deficiencies are just as much of a liability. If you want to be a top-five team, you have to build a relentlessly good offense first. Once that’s established, then you can fine-tune your defense. Otherwise, you end up stuck in the bottom half of this list.

Defense can absolutely win games. But at the highest level, the coaches who consistently win are the ones who adapt their offense to break down equally good defenses. That’s ultimately what separates the best teams from everyone else.

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Hmmm :thinking:. This is an interesting perspective. Is this opinion implied for just waterpolo or all sports? Respectfully

The only other sports that would be comparable would be lacrosse and (to a lesser extent) hockey. Lacrosse is more comparable because the volume of offensive possessions/shots would be similar. Hockey less so for two reasons: even though possessions are more similar, the lack of control of the puck; and the size of the goal relative to the goalie makes for decreased offensive efficacy.

But I would agree with that analysis.

I’d offer team handball, but no one in the US actually knows what that is.

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I was actually going to mention handball, but did not for this exact reason! I always watch it during the Olympics and it’s often referred to as “water polo on land”!

Sure, the kids used to play it against the garage door. :wink:

Gotta give credit to @gibson (for so many contributions!), who makes my point exactly.

Was it regulation size garage door?

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