Category: predictive


Conference Tournaments 2017 – Final Results

March 16th, 2017 — 10:01pm

Quick post today as the big tournament has started, but time to wrap up the Conference Tournament prediction contest. For the first time, Ken Pomeroy takes home the title. Team Rankings still leads with 2 overall titles and my own rankings have 1 title as does KenPom now.

Team Rankings came in a close 2nd while it was a tough year for Predict the Madness, who came in a distant third.

The spreadsheet with this year’s results can be found here.

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Conference Tournament Predictions 2017 – Late Tournaments

March 8th, 2017 — 7:01pm

Last week, I posted the predictions for the 13 early tournaments. Now the other 19 (that’s right, the Ivy League has joined the party) tournaments are set and most are underway, so I’ve updated the Google spreadsheet with all the predictions. KenPom is off to the early lead and looking for his first ever victory in the prestigious Conference Tournament Predictions contest that he doesn’t know he’s in. TeamRankings, the two-time champion, is in 2nd place, while my predictions (the reigning champs!) are trailing the pack.

Cinderella Index – Early Tournaments

In last week’s post, I introduced the Cinderella Index as a way to try and quantify which teams to root for during chamionship week. Let’s see where we stand with those Cinderellas: Continue reading »

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Conference Tournament Predictions 2017 – Early Tournaments and the Cinderella Index

March 4th, 2017 — 7:44am

Thirteen of the conference tournaments kick off early and are all under way. With the lone exception of the America East tournament, they will conclude early as well beginning with the Ohio Valley on Saturday and ending with the Patriot league title on Wednesday. The rest of the tournaments kick off next Monday or after and conclude either next Saturday or on Selection Sunday itself including the first ever Ivy League tournament.

As I’ve done in years past (2013, 2015, 2016), I’ll be tracking my conference tournament predictions against those of both KenPom and Team Rankings. The predictions for the early tournaments are up here on Google drive and I’ll add the remaining tournaments in once their brackets are set.

But while we wait and see how the projections will fare, I want to explain what my rooting interests will be during Championship Week.

Introducing the Cinderella Index

Continue reading »

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Conference Tournament Predictions 2016 – Final Results

March 14th, 2016 — 12:28am

Today is Selection Sunday, representing the start of the NCAA Tournament, but it also marks the end of the conference tournament season.

Earlier, I recapped how my projection system fared in 2015 with conference tournament predictions against Ken Pomeroy and Team Rankings predictions. Unfortunately for myself, the results were the same as when I tracked these in 2013–a 3rd place finish behind 2nd place KenPom and 1st place Team Rankings.

This year, things were finally different and my projections scored a resounding victory over the other two competitors, while Team Rankings edged out KenPom for 2nd place honors. The full results are in a google spreadsheet here. My projections had a strong showing, “winning” over half of the 31 conference tournaments–in 16 conferences I had the lowest cumulative score by conference, with 9 2nd place finishes and 6 3rd places. Team Rankings actually had more last place finishes than KenPom (13-12) but had twice as many 1st places (10-5) which was enough to secure the 2nd place overall finish for TR.

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Conference Tournament Predictions 2015 – Final Results

March 3rd, 2016 — 11:52pm

Three years ago, I compiled predictions for the conference tournaments from three sources–my own, Ken Pomeroy, and Team Rankings. When the dust settled, Team Rankings had narrowly edged out KenPom for the title as I lagged behind a distant third.

I didn’t get around to it in 2014 (though perhaps I can find time to go back and gather predictions from that season), but last year I did track things. Unfortunately, I’m just now getting around to posting it. The results were the same, though this time, Team Rankings won comfortably over KenPom and my own predictions. I’ve posted the full spreadsheet on Google docs, which you can find here. I discuss the scoring system in this post. Since we are posting advancement odds, we don’t have predictions for each individual matchup. Instead, predictions are essentially a rolled up version of all possible matchups. To score them, I use the log of each team’s predictions to get exactly to the round they did. For instance, my predictions for Montana in the Big Sky tournament were 81%/61%/43%, meaning an 81% chance of winning the 1st round and advancing to the semifinals, 61% of reaching the final, and 43% of winning the title. Another way of looking at it is that Montana had a 19% chance to lose in the 1st round (that’s 100% minus the 81% chance to win in the 1st round), a 20% chance of winning one game and then losing in the semis, an 18% chance of winning twice and losing in the final, and, of course, the 43% chance to win it all. Those are the probabilities that are scored.

This year is under way. If I get around to it, I may post the predictions for each of the three systems, but either way, I’ll be back in a couple weeks with the final results. Good luck to Ken Pomeroy and Team Rankings; I hope to be able to at least climb out of the cellar this year.

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NCAA Tournament Predictions – 2013

March 21st, 2013 — 2:29pm

With the tournament under way, I wanted to post my NCAA Tournament predictions. Things didn’t go so well for me with my Conference Tournament predictions, so hopefully the big dance will provide some sort of redemption.

I really hate the traditional bracket with normal scoring rules, as the best bracket ends up just being pretty much chalk and, well, what’s the fun in that? However, I’m guessing most people want to see my “bracket” so I’ll provide it. It’s really unexciting: only two double-digit seeds are favored by my system in the first round–11-seeds St. Mary’s and Minnesota–and there are only a couple more mild upsets along the way.

2013 March Madness Bracket

There’s a lot of information in predictive systems like mine, but this bracket shows virtually none of it. A better way to display all of the information is with advancement odds, like I did for conference tournaments. Here is the likelihood of each team advancing to each round of the tournament.

RgSdTeamRtgRkRd of 32Sweet 16Elite 8Final 4Champ GameChamp
31Indiana98.0198.287.670.759.439.626.4
11Louisville97.5299.376.261.145.128.515.7
23Florida97.4396.771.055.736.620.812.5
41Gonzaga96.9498.562.341.226.715.67.8
24Michigan96.7593.071.850.728.014.47.8
42Ohio State96.1691.668.446.824.012.85.8
45Wisconsin96.1773.960.829.517.69.34.2
12Duke94.5994.057.934.614.86.52.4
48Pittsburgh95.8871.931.118.610.75.52.4
21Kansas94.01193.666.328.811.94.61.8
34Syracuse93.61394.663.418.211.24.31.6
46Arizona93.81275.048.522.68.93.81.3
13Michigan State93.61475.244.722.89.03.61.2
32Miami (FL)92.31990.957.235.310.23.51.2
211Minnesota94.41073.624.415.37.32.91.2
22Georgetown92.31892.756.117.26.82.30.8
33Marquette91.52176.652.527.87.52.40.7
14Saint Louis92.22077.045.413.66.42.30.7
111Saint Mary's (CA)92.61670.036.917.56.32.30.7
17Creighton92.51758.926.413.64.91.80.5
18Colorado State92.81555.514.28.24.01.50.5
43New Mexico91.12482.038.514.54.51.50.4
25Virginia Commonwealth91.32272.222.210.63.51.10.3
37Illinois89.23460.427.314.53.30.90.2
15Oklahoma State90.32956.628.57.22.90.90.2
47Notre Dame90.62659.119.29.02.70.90.2
27San Diego State90.62765.331.38.32.90.80.2
35Nevada-Las Vegas90.03069.328.45.92.90.80.2
19Missouri91.22344.59.75.12.20.70.2
110Cincinnati89.63241.115.16.51.90.50.1
36Butler85.84265.628.111.02.00.40.1
412Mississippi89.63326.116.24.11.50.40.1
112Oregon87.73543.419.24.01.40.30.1
28North Carolina87.63655.119.15.21.30.30.1
38North Carolina State87.13856.97.62.81.20.30.1
49Wichita State89.93128.16.62.60.90.30.1
310Colorado84.44539.614.26.11.00.20.0
410Iowa State87.03940.910.54.00.90.20.0
44Kansas State85.64357.514.42.80.80.20.0
29Villanova85.24444.913.73.20.70.10.0
16Memphis84.44630.010.02.80.60.10.0
39Temple83.65243.14.61.40.50.10.0
411Belmont83.55325.09.92.40.40.10.0
114Valparaiso82.85624.88.32.20.40.10.0
210Oklahoma83.75034.711.81.90.40.10.0
26UCLA85.94126.44.31.60.40.10.0
413La Salle81.55942.58.61.30.30.10.0
311Bucknell75.98034.49.92.50.30.00.0
314Davidson76.67823.49.52.50.30.00.0
312California79.96830.77.60.90.30.00.0
212Akron80.26727.84.41.20.20.00.0
113New Mexico State78.17323.06.90.80.20.00.0
414Harvard69.39918.03.10.40.00.00.0
415Iona69.4988.41.80.30.00.00.0
213South Dakota State68.51007.01.50.30.00.00.0
315Pacific54.41439.11.30.20.00.00.0
216Western Kentucky51.81556.40.90.10.00.00.0
115Albany (NY)52.31536.00.60.10.00.00.0
215Florida Gulf Coast48.51697.30.80.00.00.00.0
313Montana45.31845.40.60.00.00.00.0
214Northwestern State56.11403.30.30.00.00.00.0
316James Madison48.31711.80.30.00.00.00.0
416Southern32.22311.50.00.00.00.00.0
116North Carolina A&T21.82730.70.00.00.00.00.0

The table is fully searchable, sortable, and filterable. I added in the region and seed so you can sort and look at best/worst teams by seed and region.

For now, it’s time to finally enjoy the games.

 

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Winners and Losers from Selection Sunday

March 19th, 2013 — 12:20am

Despite what many television analysts might say, seeding does have an enormous impact on a team’s chances to advance in the tournament. Every seed line you move up increases your chances of going further in the tournament. But the seeds don’t always play out that way, and so when the bracket is released we can see exactly what matchups each team will face on their path through the tournament.

WINNERS

Indiana has a clear path to the Final Four

The Hoosiers head the easiest of the four regions. Their 2nd round opponent will be the easiest of the 8/9 matchups (NC State or Temple). In the Sweet 16, Syracuse could provide a stiff test but each other region has a 4 or 5 seed as good or better than the Orange. And the bottom half of Indiana’s bracket is by far the easiest of any region: Miami is the worst 2-seed, Marquette is the worst 3-seed (along with New Mexico) and none of the other teams provide much of a threat. Nobody is ever a shoo-in for the Final Four, there’s too many games against too many good teams, but Indiana definitely increased their odds on Sunday with the path they were dealt.

Also benefiting from this easy bracket is 6-seed Butler, who has a relatively easy path to the Elite 8. Could they shock the world…again…and make it to the Final Four? Continue reading »

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The Achievement S-Curve – 2013 Final

March 18th, 2013 — 9:51pm

Selection Sunday 2013 is in the books. Time to release the final Achievement S-Curve of 2013 and see how it compares to the actual bracket.

The 2013 Achievement S-Curve (click twice to embiggen):

Achievement S-Curve 130318 Continue reading »

2 comments » | College Basketball, descriptive, March Madness, predictive, review, team evaluation

Conference Tournament Predictions – Final Results

March 18th, 2013 — 5:13pm

Last time, I laid out the method by which I would grade the conference tournament predictions.

The tournaments are over so it’s time to present the results…and it’s not pretty for my predictions.

TeamRankings: -317.53

KenPom: -317.87

Predict The Madness (me): -321.26

Yeah, the latter half of the conference tournaments did not go so well for my system. It’s not the biggest sample, but around 300 games gives us some indication. Perhaps next year I’ll grade all regular season predictions.

And now, it’s time for the real tournament. Enjoy the madness.

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Conference Tournament Predictions – Update 3/14/2013

March 14th, 2013 — 1:17am

As I laid out in my introductory post, I am laying out my conference tournament predictions in order to compare them to other predictions out there. The two that I know of are Ken Pomery’s Log5 predictions and TeamRankings predictions.

In that first post, I proposed a sum of squared errors measure to score each system. After talking with multiple people much smarter and more well-versed in this area than me, I settled on using a logarithmic scoring rule. One way to grade each system’s predictions would be to apply the log to the “winning” probability of each game (for instance if the winning team was given a 75% chance to win, the score for that game would be the log(.75); if the other team were to win, the score would instead be log(.25)). However, each set of predictions simply gives the probability of each team advancing to each round, so we don’t have individual game probabilities. As a replacement, I decided to grade each team based on the predicted odds that they would go exactly as far as they did. Say Team A won their 1st round and quarterfinal games but lost in the semifinals. If the prediction said they had a 75% to make it to the semifinals and a 50% chance to win in the semifinals, then the chance that they win the quarters but lose the semis is 75% – 50% = 25%. Thus, the score for Team A is log(.25). This double counts games, but it double counts every game, so there shouldn’t be a bias. Continue reading »

5 comments » | College Basketball, Conference Tournament predictions, predictive, review, simulation, team evaluation

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