So we run Golden Stateās offense?
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Iām looking at the chart and Iām not seeing how the conclusion is drawn, or how pace is seen to be an important factor. The ātrapezoidā is essentially just teams above a certain NET ranking (adjusted for opponent), minus one very fast team and one very slow team. Looks like you could just ignore pace and say that higher-ranked NET teams do well?
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Yeah that chart isnāt doing much for me. It is basically showing that there isnāt much of a relationship between pace and efficiency, which is still true if you look at all D1 teams, not just tournament teams.
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In other words, good teams are good so itās good to be good
All in all, Iād prefer a faster pace than DFL (or close), but my takeaway lesson from 2019 is you need to be able to win in multiple ways. High score games, low score games, etc. Itād be nice to be a team that can run because itās another weapon, but the key is some variability over at least a few factors. Not necessarily all of them
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Makes sense that itās valuable to be able to play slow and fast and adjust to different style opponents. Iād like us to be able to do that.
None of that is indicated by the chart though, and this ability is probably already baked into efficiency metrics, which are based on you playing a variety of teams
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If you donāt understand the trapezoid of excellence now, then you never will.
Post brought to you by Geometric Greatness Industries 
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An interesting chart would be net efficiency game-by-game vs pace of the game. And then you could see if some teams had more or less variability in performance by pace.
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In the 15 years of the Bennett tenure, Virginia has been sped up, what, a handful of times?
UNC tries it every time they play, but it never works.
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Yeah, thatās the flip side. Thereās value in being able to impose your pace so that you donāt have to be able to play both slow and fast.
But it would still be nice if we could play fast when weāre 10 points behind at the under 4!
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Not to post mortem this thing, but this year, it felt like the issue was more that we couldnāt speed up when we needed to
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Oh wait you can do this on Torvikās site:
Youāll have to set one axis as Tempo, the other as G-Score (Torvikās game-level performance metric). Our fastest game (Memphis) was bad, our second fastest game (Florida) was good. Our slowest game (Wisconsin) was bad, our second slowest games (tie between second ND game and the ACCT game against BC) were fine.
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But I also feel that pace of play is an overrated stat when trying to determine a teamās quality. Just doing a quick eyeball of adjusted tempo on kenpom, the remaining 16 teams are pretty much all over the board. Alabama and Arizona are among the 20 fastest teams in the country. But UConn and Houston are 315 and 347. Soā¦ ĀÆ_(ć)_/ĀÆ
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Or we were just bad this year. But I see your point, being able to go faster would be a nice tool to have.
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Then again, did this ever happen? I think we were always aheadā¦ or behind by 20+ lol
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Itās a piece of junk chart. If there were any connection between pace and NET rating, then youād see a general linear trend in where teams fell in NET relative to pace. Also nothing about that chart speaks to be adaptable with respect to pace. If 67 is the average tempo for D1 this year, then maybe all of Purdueās games are clustered right around that. That doesnāt demonstrate adaptability, it just means that they tend to play at an average pace.
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That was cool. Also led me to read this older post:
Prioritizing almost any other physical trait in recruiting ā height, wingspan strength, athleticism, speed ā comes with a trade-off to shooting.
Some good anecdotes to illustrate this from when he was on NMSUās staff.
Also some wise words at the end.
To bring this full circle, letās again remember the Houston, Cincinnati, and Syracuse category of teams ā strong defenses with poor shot selection. At the margins, itās wise for those teams to eliminate mid-range shots as much as possible.
Maybe itās emphasizing that a ball screener pops an extra step further to generate three-point attempts. Maybe itās adding in set plays to generate deep post pins instead of simply throwing the ball into post players off of the block.
Those marginal improvements, thanks to math, will increase efficiency. But when we start going beyond just marginal improvements, thatās when things get much murkier. If a shooter isnāt cracking a teamās rotation, there is likely a reason why.
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I donāt love the specific chart that the dude created, but the tool that he used is pretty cool. The site has team shot charts, among other things as well.
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OMG, thatās spectacular.
Edit - The trapezoid of excellence is dumb, though.
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