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Love comes in many forms. Still, it can be argued that there are two basic, essentially different kinds of romantic love in this world. There is the one that happens against all odds, between people who are vastly different, who do not belong together but are drawn to each other nonetheless. The impossible love that is as beautiful as it is painful. And then there is the seemingly ordinary kind of love that happens between people who like the same things, have same expectations, live by the same moral guidelines, have the same view of life, religion and other important matters.

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The first kind is a perfect inspiration for books, poems and movies and it is beautiful when observed from a distance, but it is also bound to reach a tragic end, as it mostly does in these sorts of love stories. On the other hand, the second kind is one that does not often inspire artists to create works that will delight their audience, but does give meaning to the lives of the people who are blessed with it, fills their lives with harmony and joy and more often than not, lasts until the end of their days and beyond. That is because it is not based on a temporary rush and a desire to taste the forbidden fruit, but has a more spiritual nature, as it grows between people who understand its divine origin and see it as a link to the God above and something to be cherished.

Adventist Singles Connect: Adventist Match is designed for Adventist singles who are looking for Christian dating, love and romance, and friendships through chat and email. Unlike more general Christian dating sites, we are dedicated specifically to helping SDA singles connect with other Seventh Day Adventists throughout the world.

1. Being matched based on key areas of Adventist faith is the difference between our service and that of traditional Adventist dating sites, and it is the main driver of our matching success. Based on your match preferences we narrow the field from thousands of Adventist singles to match you with a select group of compatible Adventist men or women.
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If you are an Adventist seeking for this kind of unbreakable bond, but haven’t had the chance to meet someone religious, kind and lovely enough to share it with, you have come to the right place. In this text, we will explain how the wonders of the modern world can help you make your dream come true. Welcome to our guide to the amazing online places especially designed to help Adventist soul mates find each other.

What To Look For In An Adventist Christian Dating Site

Adventist dating sites all have the same noble purpose of allowing Adventist singles get to know other people of the same faith who are looking for lasting love. However, some of them are more successful in their endeavors than others. We’ve taken the time to help you recognize the major signs that you have chosen the best dating site for Adventists.

It has a large membership base. This means that you will have the chance to meet many different singles of your denomination and it is highly likely that at least some of them will suit your likings and that the one that is meant for you will be among them.

It is a pleasant and cozy place. This is highly important when it comes to dating sites of any kind, because it sets the right mood and lets you feel more relaxed, more keen on meeting new people and gives you greater courage to pursue your love interest.

It offers a lot of information about its members. Detailed profiles are highly useful when you are choosing the people you want to get it touch with. If the profile itself contains many photos, lets you know what this person likes and wants from life and allows you to find out a lot of personal information including age, gender, education, occupation, living situation and other crucial details, it will be easier for you to determine whether this person is worth your time and could potentially become your partner.

It allows you to easily search for your perfect match. If the site offers advanced tools for searching for a specific kind of people and allows you to filter them based on their interests and various personal characteristics, you can instantly find out whether there is someone who is everything you want your partner to be.

It lets you communicate with other members in several ways. Everyone’s approach to romantic interactions is different, which is why the best Adventist dating sites let you get in touch with other members in numerous ways, from sending flirts in order to let the other person be the one who starts the conversation, to instant messaging, live chat, video chat, as well as chat rooms for public discussions and making a lot of friends at the same time.

Our Recommended Websites

We know that searching for the right site can take a while, even if you know exactly what you should be looking for. That is why our experts have decided to help you. They scoured the Internet searching for the best of the best. These are the sites that made their top 5 list.

Adventist Christian Loving Review

Adventist Christian Loving is one of the liveliest Adventist dating communities on the web. It is predominantly populated by young Adventist singles who enjoy chatting, flirting, and making new acquaintances on a daily basis.

Simply put, Adventist Christian Loving is a place where you can find someone amazing to talk to at any time of the day. What brings these open-hearted singles together is their common faith and desire to meet their soulmates. However, that does not mean that conversations on this dating platform are limited to these two topics. By exchanging private messages with your favorite members and having group talks in chat rooms, you can share your every thought, tell others what your day was like, and simply enjoy pleasant conversations with people who share your worldview.

Of course, Adventist Christian Loving’s primary goal is to help you find your ideal partner, which is why it uses specialized search systems to help you find exactly the kind of person you wish to date. As incredible as it may seem, finding love on this platform can take mere minutes. With fast registration and instant refined search results, you can find someone truly special in just a couple of clicks and start a romance that may last a lifetime.

Adventist Online Dating Review

Although it doesn’t boast a huge member base, as it caters to a highly specific population, the diversity of its members and a wide variety of useful features make this site one of the best options for Adventist singles who are looking for love. Finding your perfect match is made easy with the possibility of applying various criteria to your search, ranging from basic characteristics, such as age, gender and location, to those related to education, job and living situation and various interests.

As a member of Adventist Online Dating, you’ll get plenty of options for getting to know the interesting Adventist singles you find appealing. You can like someone’s profile, send a flirt or exchange private messages and enjoy long romantic talks with your love interest. If you are a fan of lively discussions with a large group of people, the site lets you join chat rooms, where Adventist singles get to talk about their day and enjoy meaningful conversations about faith, love and everything in between.

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If you are looking for a comfortable place where you can meet quite a few singles who are not only wonderful people and members of your denomination, but are also highly enthusiastic about meeting someone like you, Adventist Online Dating is a great choice.

Black Adventist Singles Review

Seventh Day Adventist Dating Free

If you are looking for someone who is black, a firm believer in the imminent Second Advent and also wonderfully available, this is a perfect site for you, since its membership base is exclusively limited to the people who meet all of these criteria. You can also search for members who, on top of that, share your interests, have the same level of education and possess various physical attributes and other qualities you deem crucial, thanks to the advanced search. All of this means that you will find a great match in no time and that you can start dating just the kind of person you want to be with right away.

When it comes to communication options, apart from sending flirts and messages to the members you find interesting and having fun in the chat rooms, Black Adventist Singles also offers you the possibility to enjoy private video chat, which is possibly the best way to truly get to know someone before you decide to meet in person and let your romance bloom in the real world.

Adventist Dating Service Review

From the moment you lay eyes on the lovely design and the photo of the beautiful couple on this site’s welcome page, you’ll have the great feeling that this is the place where you could meet the love of your life. The member base is quite large, especially for a site that is exclusively dedicated to bringing Adventist singles together, so you will have no problem finding someone you’ll really like.

The profiles of the members are highly detailed and appear right on the home page of the site, so you can get browsing as soon as you join. If you are looking for a particular kind of person, you can use the excellent search tool and apply various filters related to age, gender, ethnicity, location, interests and a lot of other important characteristics.

Once you find someone you want to get in touch with, you can send a flirt or a private email and start what can turn into a beautiful friendship or a romance of a lifetime. The site also lets you know who is currently online, so you can contact them and begin a conversation right away. If you are a people’s person and want to get to know as many lovely, like-minded people as possible, you can join chat rooms and make a lot of great friends.

Adventist Chat City Review

Adventist Chat City is an increasingly popular Adventist dating site that can help you find whatever is missing from your social life. Whether you are looking for friends, a loving companion or someone who understands you better than you understand yourself, the chances are you can realize your dreams and desires in this amazing dating community.

The site’s member base is filled with good-looking Adventist singles, and according to Adventist Chat City representatives, thousands of new members join daily, so you can easily find at least a few ladies or gents you would like to meet and potentially date. You can browse and see if someone interesting pops up or you can use advanced search and find someone just right in seconds.

Once you find someone you are interested in dating or just meeting, you can like his or her profile, send a flirt or start a private conversation and see if the feeling is mutual. If you prefer group talks, you can search for love in one of the many vibrant chat rooms. Either way, you are sure to have a blast and enjoy every minute you spend on this site.

Conclusion

Hopefully, you now possess all the information you need in order to successfully navigate the world of Adventist online dating. The sites we have chosen for you are certainly the best on the web, which is why you are only left with the task of picking the one that you like most.

Trying something new is never easy and it is completely understandable if you are having doubts and you don’t feel so sure that this is the way to go. But the truth is, you can never be sure about anything in this world, except for the fact that God loves us all and steers us ever so subtly in the right direction. You need to trust your heart and take a leap of faith.

Adventist online dating gives you an opportunity you can never get in the real world – to spend time with only the most wholehearted, true Adventists who dream about meeting someone just like you. Away from all the problems of the outside world, you get to let your love grow unbound and unburdened and savor every sweet second of your blooming romance.

Abstract

The objective of this paper is to use data from the highest level in men’s tennis to assess whether there is any evidence to reject the hypothesis that the two players in a match have a constant probability of winning each set in the match. The data consists of all 4883 matches of grand slam men’s singles over a 10 year period from 1995 to 2004. Each match is categorised by its sequence of win (W) or loss (L) (in set 1, set 2, set 3,...) to the eventual winner. Thus, there are several categories of matches from WWW to LLWWW. The methodology involves fitting several probabilistic models to the frequencies of the above ten categories. One four-set category is observed to occur significantly more often than the other two. Correspondingly, a couple of the five-set categories occur more frequently than the others. This pattern is consistent when the data is split into two five-year subsets. The data provides significant statistical evidence that the probability of winning a set within a match varies from set to set. The data supports the conclusion that, at the highest level of men’s singles tennis, the better player (not necessarily the winner) lifts his play in certain situations at least some of the time.

• Using grand slam men’s singles data, the probability of winning a set has been shown to vary from set to set.

• The data provides statistical evidence that the better player (not necessarily the winner) in some matches is able to lift his play in certain situations. This result gives encouragement to the better player when in difficulties in a match.

• The authors found no evidence that the weaker player was able to lift his play. The weaker player, when ahead in a match, should be on his guard for his opponent to have a real capacity to lift his game.

Introduction

Several authors have carried out probabilistic analyses of tennis (Carter and Crews, 1974; Miles, 1984). A common assumption is that player A has a constant probability PA of winning a point on his/her service and that player B also has a constant probability PB of winning a point on service. Under this assumption and the assumption that points are independent, it can be shown that the better player does not always win and that each player has a constant probability of winning each set, no matter who serves first in the set (Pollard, 1983). Player A is the better player if PA is greater than PB.

There is little published research on testing whether players do have constant probabilities on service, that points (and hence games and sets) are independent and identically distributed (iid). A ‘first game effect’ in a match, namely that fewer breaks occur in the first game of the match, has been identified (Magnus and Klaassen, 1999). However, it would appear that any non-iid effects such as the ‘hot- hand effect’ (in which winning a point, game or set increases ones chances of winning the next point, game or set) and the opposite effect, the ‘back- to-the-wall effect’, are small when analyzing large data sets (Klaassen and Magnus, 2001).

Many players believe, and commentators often state, that the winner of a set of tennis is not infrequently determined by merely a couple of points within that set. Given that a set lasts about (say) 60 points on average, and the couple of critical points can occur almost anywhere in the set, it would appear to be difficult to use statistical methods to identify a couple of non-iid points amongst approximately 60 other iid points. It would be like ‘searching for a needle in a haystack’.

In this paper we focus on sets rather than points. If sets are not iid, it follows that points and games cannot be strictly iid, even if only a very small percentage of points contribute to the non-iid nature of the data. The data consists of ten years (1995 to 2004) of the four major annual tournaments for men’s singles. These tournaments are the Australian Open, the French Open, Wimbledon and the US Open, are known as the Grand Slam tournaments, and are played on different types of surfaces. Using W to represent a set won by the eventual winner of the match and L to represent a set lost by the eventual winner, there are several possible match categories from WWW to LLWWW. Each of the 4883 singles matches for this period were classified into the relevant categories, and the frequencies of the categories were analysed to check for lack of independence of set outcomes.

Methods

Assuming without loss of generality that player A is the better player, the results of a best-of-five sets singles match can be recorded as WWW, WWLW, WLWW, LWWW, WWLLW, WLWLW, WLLWW, LWWLW, LWLWW, LLWWW, and LLL, LLWL, LWLL, WLLL, LLWWL, LWLWL, LWWLL, WLLWL, WLWLL and WWLLL where W represents a set won by player A, and L represents a set lost by player A. When we do not know who the better player is, a win in three sets for example (WWW or LLL above) is simply a win WWW to the winner of the match (not necessarily player A). Thus, when we do not know who the better player is, the above twenty outcomes reduce to the ten mutually exclusive outcomes WWW, WWLW, WLWW, LWWW, WWLLW, WLWLW, WLLWW, LWWLW, LWLWW and LLWWW where W represents a set won by the eventual winner of the match and L represents a set lost by the eventual winner.

The data consisted of ten years of men’s singles grand slam results. There were 4883 matches in total, and spurious data such as matches where one player ‘retired’ (presumably injured) before the match was finished were omitted. The number of matches in each of the above categories was:

WWW 2330; WWLW 503; WLWW 487; LWWW 609; WWLLW 151; WLWLW 135; WLLWW 186; LWWLW 138; LWLWW 156; LLWWW 188

The first model fitted involved a constant probability, p, of player A (the notionally or theoretically better player) winning each set. A short and simple search using a spreadsheet showed that the value of p which minimized Chi-Squared was 0.769, and the results are given in Table 1. For example, the expected value for the row WWW in Table 1 is 4883*(0.769*0.769*0.769 + 0.231*0.231*0.231) = 2280.77, allowing for both a win and a loss by the theoretically better player.

Table 1.

Match outcomes when the probability player A wins each set is 0.769.

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The value of Chi-Squared was 38.68 with 8 degrees of freedom, so the fit is a poor one. This is not surprising as a constant p-value for all matches is clearly unrealistic. It can be seen from the Obs-Exp column in Table 1 that there was a greater number of three sets and five sets results observed than was expected under this model. Also, for the four sets matches, this model underestimated the number of LWWW matches, and overestimated the other two categories. Similarly, for the five sets matches, the model underestimated the number of WLLWW and LLWWW matches.

In order to attempt to overcome the shortage of three and five sets matches expected under the above model, it was decided to model the data using two p values, one greater than 0.769 and the other less than it, and combine the results. The value greater than 0.769 would increase the proportion of three set matches, and the value less than 0.769 would increase the proportion of five set matches. Thus, for simplicity, the data was modeled as consisting of 2 types of matches-‘close’ matches (with p less than 0.769) and ‘not- so- close’ matches (with p greater than 0.769).

Half the matches were assumed to be ‘close’, and half ‘not- so- close’. Symmetric values about 0.769, p1 and p2, were considered, and the two p values which minimized Chi-Squared were identified. These two values were p1 = 0.705 and p2 = 0.833. The results for this model are given in Table 2. For example, the expected value for row 4 (LWWW) of Table 2 is given by 4883(0.5*((1-p1)*p1*p1*p1 + p1*(1-p1)*(1-p1)*(1-p1)) + 0.5*((1-p2)*p2*p2*p2 + p2*(1-p2)*(1-p2)*(1-p2))) = 541.71, allowing for both a win and a loss by the theoretically better player.

Table 2.

Set outcomes when player A has in half the matches a probability of 0.705 of winning a set and in half the matches a probability of 0.833 of winning a set.

The value of Chi-Squared for this model was 35.59 with 7 degrees of freedom, so the fit is again a poor one. Whilst this is a better fit with respect to the proportion of three and five set matches, the number of LWWW matches is still underestimated under this model, as is the number of WLLWW and LLWWW matches.

It is noted here as an aside that if we remove the restriction that exactly half of the matches have a p-value of p1 and half of them have the value p2 whilst keeping p1 = 0.705 and p2 = 0.833, a slightly smaller value of chi-squared can be obtained. The lowest Chi-Squared value obtained was 34.35 with 6 degrees of freedom when the proportion of matches with p1 = 0.705 was 0.53, and the proportion of matches with p2 = 0.833 was 0.47. Thus, for this model (and indeed for the others considered in this paper), modifying the proportion of ‘close’ and ‘not- so- close’ matches had negligible effect on the Chi-Squared values. For this reason, no further reports on this modification are given in this paper.

It can be seen from Table 2 that, under this model, the expected number of matches in each of the 3 four sets categories are equal. Correspondingly, the expected number of matches in each of the 6 five sets categories are also equal. It is clear that this characteristic remains true even if we fitted more (or even many many more!) than just two p values to the data. Further, it follows that if the p-value is constant for each set within each match (but possibly different for each of the 4883 matches) the expected number of matches in each of the 3 four set categories would be equal, and that the expected number of matches in each of the 6 five set categories would also be equal. It is possible to fit the best-fitting model to this data such that the 3 four set categories have equal expected values and the 6 five set categories also have equal expected values. Note that this is simply a data fitting exercise, and that there is no assumed underlying p-value(s) such as in the above analyses. When this is done, the expected values for the three, four and five set categories are 2322.2, 534.0, and 159.8 respectively, and the Chi-Squared value is 33.17 with 7 degrees of freedom. Again the fit is not a good one and we conclude that the p-values for each set (within each match) are not constant.

It can be seen from Table 2 that the (Obs-Exp) value was positive for the categories LWWW, WLLWW, LWLWW and LLWWW. These categories represent situations in which the winner (typically, but not always, the better player, player A) was behind (in sets) at some stage in the match. Thus, the data suggests that the better player might ‘try harder’ or ‘lift his game’ in situations in which he is behind. In order to address this ‘trying harder when behind’ effect, it was assumed that player A lifted his probability of winning a set by D1 when he was behind in the set score. A closer look at the data also suggests that player A might be ‘on- a- roll’ when he has just won a set and as a consequence lifts his probability of winning the next set. In order to address this ‘on- a- roll’ effect, it was assumed that player A lifted his probability of winning a set by D1 when he won the previous set. The categories WLLWW and LLWWW noted above represent situations in which the winner (probably more often player A) lost two sets in a row. These are situations in which player A has a real need to make an extra special effort to lift his game. Thus, it was further assumed that player A lifted his probability of winning a set by an amount D2 (anticipated to be somewhat bigger than D1) for the remainder of the match immediately after having lost two sets in a row (there are 3 such match categories). It is for reasons of simplicity that the parsimonious model with only two lifted levels was tested.

Given that p1 and p2 are increased by D1 or D2 in certain situations, it seemed appropriate, in order to get a reasonable overall fit, to lower both their ‘starting’ values (ie, those for set1) from those in Table 2. Given this, the notion of symmetric p-values about 0.769 also seemed irrelevant. The values of p1 and p2, D1 and D2 which minimized Chi-Squared were p1 = 0.704 and p2 = 0.798, D1 = 0.035 and D2 = 0.110, and the results are given in Table 3. For example, the expected value for the number of LLWWW matches is 4883 (0.5 * ((1-p1) * (1-p1-D1) * (p1+D2) * (p1+D2) * (p1+D2) + p1 * (p1+D1) * (1-p1-D1) * (1-p1) * (1-p1-D2)) + 0.5 * ((1-p2) * (1-p2-D1) * (p2+D2) * (p2+D2) * (p2+D2) + p2 * (p2+D1) * (1-p2-D1) * (1-p2) * (1-p2-D2))) = 186.68.

Table 3.

Match outcomes when p1 and p2 are 0.704 and 0.798 respectively, D1 = 0.035 and D2 = 0.110.

The value of Chi-Squared was 1.83 with 5 degrees of freedom, so the fit is a good one indicating that the model fits the data well.

In order to carry out a simple check on the model, it was decided to break the data into two time periods (1995-1999 and 2000-2004), and check for consistency across the periods (Table 4). The above parameter values or estimates for p1, p2, D1 and D2 based on the full 10 year period 1995 to 2004 were used ‘as estimates’ for the period 1995 to 1999 (2448 matches) and for the period 2000-2004 (2435 matches). The fits were surprisingly good, with Chi-Squared values of 1.81 and 3.00 respectively. ( It is clearly quite likely that lower values of Chi-Squared could be obtained by fitting p1, p2, D1 and D2 values specific to each period, but there is little point in doing this.

Table 4.

Observed match outcomes for the periods 1995-1999 and 2000-2004.

There appeared to be no evidence in the data that the weaker player could lift his game in situations where it would have been useful for him to do so.

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Results

The 4883 completed men’s singles matches at grand slam tournaments for the period 1995-2004 have been analysed to test the hypothesis that the probability of winning a set within a match is constant. This hypothesis was rejected.

A model which fits the data well has been found. It is a model in which the better player lifts his probability of winning a set in certain situations. These situations are

(i)when he is behind in the set score, needs to lift his game, and lifts his probability of winning the next set by (on average) 0.035,

(ii)when he has just won a set, is ‘on-a-run’’, and lifts his probability of winning the next set by (on average) 0.035, and

(iii)when he has just lost two sets in a row, desperately needs to lift his game, and lifts his probability of winning each remaining set by (on average) 0.110.

Discussion

The results of this study are quite encouraging for the better player, but perhaps somewhat discouraging for the weaker player. The findings indicate that the weaker player needs to be ‘on his guard’ for a change in fortunes when the match is ‘going well’ for him.

The results of the analysis in this paper show that often the better player can increase his probability of winning a set by quite a substantial amount when it is really necessary to do so in order to reduce his probability of losing the match. A set can often be won rather than lost by winning just one, two, or a few particular important points (Morris, 1977). Thus, it would appear from the analysis in this paper that the better player is more able to lift his play on particularly important points than is the weaker player.

Further studies might include whether women’s matches (although only best-of-three sets) have comparable characteristics or whether there are gender differences in this regard.

It would appear that the methodology used in this paper has a range of sporting applications, particularly for the often occurring situation in which the better player or team does not always win a match, or the ‘best’ player or team does not always win a series of matches. Another area of application might be assessment in which the ‘best’ student (or persons being assessed) does not always come first.

Conclusions

The conclusion is that matches turn around in favour of the better player significantly more often than would be expected under the usual randomness/independence assumptions of probability. As each point is a ‘zero-sum’ situation for the two players, it is not strictly possible to tell from just the statistical records whether this ‘turn-around’ characteristic is because the better player lifts his play or because the weaker player lowers his play. Nevertheless, it is useful for both players to know of the existence of this phenomenon as any player (except the best player in the world) should sometimes be the better player and sometimes the weaker on the court. The better player can take advantage of it, and the weaker player needs to guard against it.

Biographies

Graham POLLARD

Employment

Emeritus Professor, University of Canberra.

Degree

PhD in Statistics from the Australian National University

Research interests

Probability applications in sports scoring systems and in assessment, optimal learning.

E-mail:ua.moc.mahsluof@maharg

Rod CROSS

Employment

A/Prof, Sydney University.

Research interests

Physics of sport.

E-mail:ua.ude.dysu.scisyhp@ssorc

Denny MEYER

Employment

Senior lecturer, Swinburne University of Technology, Australia.

Research interests

Sport Statistics, Time series analysis and data mining.

E-mail:ua.ude.niws.esiwpuorg@reyeMD

References

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