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Written Thursday October 22nd, 2020 at 2 p.m. Eastern Time (spreads/odds may have changed) This week we’ve got just our second 5-star play of the 2020 season! The only other one was Arizona +7 against the 49ers in Week #1, a bet that easily covered since the Cards won the game straight up by a margin of four points. Such picks rated 5 stars have done very well since I started this “Professor MJ” brand a few years ago. That being said, I’m not suggesting to bet your house on it. You’ll never hear me talk about “the lock of the century” or “100% guaranteed winner” or any similar bull$$hit. There is always risk involved. Bet at your own risk and never bet an amount that you cannot afford to lose. PICK #1 (5 STARS): NEW YORK JETS +13 VS BUFFALO BILLS Wow, picking the lowly Jets as a five-star play is pretty bold, isn’t it? Adam Gase’s team is 0-6 both straight up (SU) and against the spread (ATS) this year. Since 1985, six teams have started the season with six straight losses both SU and ATS. How did these teams fare in the remainder of their season? They went 34-24 ATS, a 58.6% win rate. I like the Jets for many other reasons. The rest factor is in favor of New York since the Bills are coming off a Monday night game. Also, NFL teams tend to do very well in the rematch against a division rival after losing the first meeting of the season. In this case, Buffalo won 27-17 in Week #1, which makes the Jets a good play based on this betting angle. Finally, the Bills have been struggling a lot recently. They blew a 25-point lead against the Rams before escaping with the win, thanks to a questionable pass interference penalty on fourth down in the final drive. They got hammered 42-16 against a depleted Titans team two weeks ago. Last week, losing 26-17 against the Chiefs may not look bad on paper, but if you watched the game you know what I’m talking about. The Bills were out of sync on offense, where Josh Allen looked more like the 2018 or 2019 version of himself. And their defense was gashed on the ground by allowing 5.3 yards per carry. This unit was supposed to be among the league’s best, but they an average of 28 points per game. Meanwhile, Sam Darnold has a shot to be back under center. He is a big improvement over Joe Flacco, and he would finally have some weapons around him with Jamison Crowder, Breshad Perriman and maybe rookie Denzel Mims who could make his NFL debut. Some bookies have already lowered their spread to 12, but at the time I’m making this video BetOnline still has 13. This is where I placed my bet. I really like New York to cover in this one. PICK #2 (3 STARS): KANSAS CITY CHIEFS -9.5 AT DENVER BRONCOS Over the last nine meetings between these two clubs, Kansas City holds an 8-1 record ATS. If you focus on games played in Denver only, the Chiefs have beaten the spread on six consecutive occasions. Sure, Kansas City loses one day of rest after playing the Monday nighter. But in my opinion, elite teams fare well when facing adversity. They are a well-coached team and it won’t affect them that much. The Broncos are coming off a nice upset win in New England. Quarterback Drew Lock made two incredibly bad decisions that almost gave the game away, but he should be thankful that his defense saved the day. Denver’s offense struggled most of the day and couldn’t score more than 18 points despite the Pats turning the ball over three times. They won’t be able to keep up with KC’s offense, who are unlikely to take them lightly, considering it’s a divisional game. PICK #3 (3 STARS): LAS VEGAS RAIDERS +4 VS TAMPA BAY BUCS I feel like the public is getting overexcited following Tampa’s convincing win over the Packers. It was indeed an impressive outing where emotions were high, which makes this non-conference matchup a trap game for them. Las Vegas is also coming off their bye week, which is always a nice advantage. Tampa’s top three receivers (Evans-Godwin-Miller) are all likely to play, but are nursing injuries. On the defensive side of the ball, the loss of nose tackle Vita Vea for the rest of the year was a big blow and is an underrated loss for this squad. They also have three good guys on defense who are listed as questionable: LB Lavonte David and DEs Jason Pierre-Paul and William Gholston. The Raiders have beaten the Chiefs, the Saints and the Panthers, while losing to Buffalo and New England. In other words, there wasn’t a single easy opponent (Carolina was expected to be weak, but they are off to a nice start). I’m taking the Raiders as home underdogs here. PICK #4 (1 STAR): SEATTLE SEAHAWKS -3 AT ARIZONA CARDINALS Seattle is coming off their bye week, while the Cards lose one day of preparation after playing the Monday night game. Arizona also had to travel on three straight weeks prior to this week, which isn’t easy. I’m pretty sure the Seahawks remember the last time they faced Kliff Kingsbury’s squad: a 27-13 home loss in Week #16 that hurt their chances of clinching a first-round bye. Payback time! Over the last 11 meetings between these two rivals, the road team has a 9-1-1 record ATS. Please note that the “under” was a winning bet in each of the last five matchups. As mentioned last week, I also like to back road favorites coming off a bye week. A reminder that such teams showed a jaw-dropping 15-1-2 ATS record over four seasons (they went 1-1 last week though). Best of luck with your plays and I’ll see you again next week! Professor MJ https://www.youtube.com/c/ProfessorMJ/featured Twitter: @DavidBeaudoin79 FB: ProfessorMJ www.professormj.com
Tennis Data Analysis
PJC_83 posted a topic in Betting Systems & StrategyI've always been a football man, but I find my judgment clouded at times by gut instinct, rather than what the stats say (I know stats aren't everything). I'm a big fan of data analysis, and the patterns that they show, so I decided to apply them to a game I'm less up-to-date with, and that's Tennis. I know the rules of tennis, the patterns of play, the fundamentals, but my knowledge of the actual players isn't great. I could probably name 50 of both genders combined, maximum. Another thing that interests me about tennis betting is that there has to be a result. An underdog cannot play for a draw in tennis like they can in football. Football can have overwhelming domination by a favourite, yet finish 0-0. In Tennis, there has to be a result, therefore each set someone will reach at least 6 games (barring retirement). I analysed all the match data from 2019, looking only at matches that completed. 1117 Men's matches, and 1016 Women's. I'm an over/unders man, and a short odds gambler, so I am specifically looking at the number of games in the 2nd set. Looking at the 2nd set I find more consistent, because you can analyse the 1st set performance and take that into account. If someone was smashed 6-0 in the 1st set, then the likelihood of a 2nd set finishing 7-6 is a lot less than had the 1st set been much closer. The specific market I'm looking at is Over 7.5 games in the 2nd set, so essentially the set finishing any score other than 6-0 or 6-1. The data made quite interesting reading: The total number of games having Over 7.5 in the 2nd Set: Men's: 993/1117 - 88.9% Women's: 829/1016 - 81.59% Men's data breaks down further as follows: Over 7.5, 2nd set, clay courts: 395/451 - 87.58% Over 7.5, 2nd set, hard courts: 598/666 - 89.79% and Women's: Clay: 308/365 - 84.38% Hard: 521/651 - 80.03% So, on the face of this, it indicates that men's games on hard courts tend to be a lot closer than any other match type. I then looked at taking the pre-match odds into consideration. I looked at matches where the favourite was priced 1.5 or shorter, and also looked at games where both players were priced between 1.50 - 2.50 (therefore, you'd imagine, closer matches). Men's: Under 1.5 Favourite, All Games: 512/586 Over 7.5 2nd set - 87.37% Under 1.5 Favourite, Clay: 184/216 Over 7.5 2nd set - 85.19% Under 1.5 Favourite, Hard: 328/370 Over 7.5 2nd set - 88.65% 1.5 - 2.5 Odds, All Games: 426/469 - 90.83% 1.5 - 2.5 Odds, Clay: 187/208 - 89.90% 1.5 - 2.5 Odds, Hard: 239/261 - 91.57% Women's: Under 1.5 Favourite, All Games: 431/536 Over 7.5 2nd set - 80.41% Under 1.5 Favourite, Clay: 146/179 Over 7.5 2nd set - 81.56% Under 1.5 Favourite, Hard: 285/357 Over 7.5 2nd set - 79.83% 1.5 - 2.5 Odds, All Games: 354/429 - 82.52% 1.5 - 2.5 Odds, Clay: 148/170 - 87.06% 1.5 - 2.5 Odds, Hard: 206/259 - 79.54% Conclusions at this stage: Men's hard court matches with more even odds have a higher chance of going over 7.5 games in the 2nd set than any other conditions. I then drilled down even further, to look at the chances of over 7.5 games in the 2nd set, depending on the number of games in the 1st set. These are the highlights of the findings: In men's matches, with odds 1.5-2.5, on Hard courts, and where the 1st set finished 7-6, there is a 93.75% chance of the next set having over 7.5 games. However, this is a fairly small field.. In men's matches, 1.5 - 2.5 odds, Hard courts, 1st set had 9+ games. 2nd set chance of over 7.5 is 91.41%. Although this is a decrease from the line above, it does have a larger field (it has occurred 199 times this year from a sample of 217 games). Taking implied odds into account, 1.09 has implied probability of 91.74%, and 1.1 has implied odds of 90.91%, so any odds 1.1 or longer for over 7.5 2nd set games is value. Hope this makes sense, I'll add more as I go.
if you want data
liero1 posted a topic in Betting Systems & StrategyGoogle just launched a new search engine, for databases Pretty cool if you want to crunch through more data, just search for 'betting odds' or related. https://toolbox.google.com/datasetsearch/search?query=betting odds
Hello. I'm really excited to finally start my own thread after working on developing my betting model. I aim to constantly post my predictions and picks. From time to time, I will also monitor the accuracy of my picks compared to the market So, here are some brief details about my model and picks. About the model(s) Why logistic picks? Because the model that generates the probabilities for the outcomes is a multinomial logistic regression. It combines Elo ratings with with my own ratings developed with data from whoscored and data about injuries and suspensions. The sample used was last seasons from 2009 to 2015 for all covered leagues. There are two models that I use: the main difference between them is that the second one uses data about injuries and suspensions from whoscored. Because of that, the "Preview" page of the game needs to be available before generating predictions. Therefore, any prediction that is more than two days into the future is generated without injuries and suspensions data and from my tests they have lower accuracy (as measured by AUC metric). Bet selection I will post my model predictions and my picks. I will try not to have a rigid approach, say bet when the odds value is above X, I will also study a bit the games before placing bets. From my cross-validation tests, my optimal results where when probability difference between was at least 4-5% or the expected value of the bet was at least 10-15%. Usually, the second is my threshold, but I could make some exceptions from time to time. Leagues covered For now, I cover the top 5 European leagues and Championship. In the future I would like to add more leagues though. Odds The market odds are from Pinnacle as they are very easy to get from their API. However, I will try to look for higher odds at other bookmakers before placing the bets So, these are my predictions for the upcoming fixtures. Also, my first bets. Staking plan Not 100% sure, in principle level stakes. I might do exceptions for long shot games as they pose the greatest threat to the bank.