Season Trends

Madeline Gates – 2019 Stanford University

Interactive Dashboard:

Is your team getting better or worse as the season progresses? Are your players developing and performing stronger as the year goes on?

In the chart above, we take a look at Madeline Gates, the middle from Stanford. We’re looking at a rolling average of her hitting efficiency, in this case, rolling over 100 attempts. As you can see, she has a fine start to the year, hitting around 0.250 on average. This slowly rises through October and November – and then she freaking turns it on in the NCAA Tournament. Good lord. The former UCLA Bruin seems to have figured something out come tournament time, because she skyrockets into the rarefied air of 0.500+ territory. Pretty impressive stuff.

With regard to the colors – we use a bit of statistics to determine the expectation for a player, given her variation in performance. So the yellow is the average, plus or minus one standard deviation. The Yellow chunk means we expect 68% of outcomes to fall in this range. In the Green zone, one standard deviation above the mean, we expect 16% of outcomes to land this high, making them the upper echelon of performance for that player or team (whatever you’ve filtered for). And then the same deal for the Red zone, we expect the final 16% of outcomes to fall into this bucket – meaning it’s below average performance for that player/team and uncharacteristic. I’ve added a visual aid below. The μ (pronounced mu or mew if you’re a Pokemon fan) is the mean. I know it looks like an incorrect u…but the Greeks are weird. And then the WWI cannon-looking thing is sigma – it just means standard deviation. So for you nerds, our chart is really just showing μ +/- σ. Now you have something to talk about at the next party you go to in 2022…you’re welcome.

Personally, I think this is a pretty neat dashboard. You can look at any team, any player, any skill to see how they trended throughout the 2019 season. Keep in mind that I’ve only included teams in the top 100 RPI, so if you played a team outside that rating, that data will not show up.

If you’re curious about where the “expected values” come from, check out some of the previous posts where we detail exactly how we’re calculating all that stuff!

Hopefully this helps answer old – or stimulates new questions for you. It’s all about getting things down to a single number. In my opinion, that’s Expected Value (eV) and/or Point Win Probability (PWP).